A wireless sensor network for urban traffic characterization and trend monitoring.

PubMed

Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A

2015-10-15

Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.

Carbon emissions tax policy of urban road traffic and its application in Panjin, China

PubMed Central

Yang, Longhai; Fang, Lin

2018-01-01

How to effectively solve traffic congestion and transportation pollution in urban development is a main research emphasis for transportation management agencies. A carbon emissions tax can affect travelers’ generalized costs and will lead to changes in passenger demand, mode choice and traffic flow equilibrium in road networks, which are of significance in green travel and low-carbon transportation management. This paper first established a mesoscopic model to calculate the carbon emissions tax and determined the value of this charge in China, which was based on road traffic flow, vehicle speed, and carbon emissions. Referring to existing research results to calibrate the value of time, this paper modified the traveler’s generalized cost function, including the carbon emissions tax, fuel surcharge and travel time cost, which can be used in the travel impedance model with the consideration of the carbon emissions tax. Then, a method for analyzing urban road network traffic flow distribution was put forward, and a joint traffic distribution model was established, which considered the relationship between private cars and taxis. Finally, this paper took the city of Panjin as an example to analyze the road traffic carbon emissions tax’s impact. The results illustrated that the carbon emissions tax has a positive effect on road network flow equilibrium and carbon emission reduction. This paper will have good reference value and practical significance for the calculation and implementation of urban traffic carbon emissions taxes in China. PMID:29738580

Carbon emissions tax policy of urban road traffic and its application in Panjin, China.

PubMed

Yang, Longhai; Hu, Xiaowei; Fang, Lin

2018-01-01

How to effectively solve traffic congestion and transportation pollution in urban development is a main research emphasis for transportation management agencies. A carbon emissions tax can affect travelers' generalized costs and will lead to changes in passenger demand, mode choice and traffic flow equilibrium in road networks, which are of significance in green travel and low-carbon transportation management. This paper first established a mesoscopic model to calculate the carbon emissions tax and determined the value of this charge in China, which was based on road traffic flow, vehicle speed, and carbon emissions. Referring to existing research results to calibrate the value of time, this paper modified the traveler's generalized cost function, including the carbon emissions tax, fuel surcharge and travel time cost, which can be used in the travel impedance model with the consideration of the carbon emissions tax. Then, a method for analyzing urban road network traffic flow distribution was put forward, and a joint traffic distribution model was established, which considered the relationship between private cars and taxis. Finally, this paper took the city of Panjin as an example to analyze the road traffic carbon emissions tax's impact. The results illustrated that the carbon emissions tax has a positive effect on road network flow equilibrium and carbon emission reduction. This paper will have good reference value and practical significance for the calculation and implementation of urban traffic carbon emissions taxes in China.

A Survey on Urban Traffic Management System Using Wireless Sensor Networks.

PubMed

Nellore, Kapileswar; Hancke, Gerhard P

2016-01-27

Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research.

A Survey on Urban Traffic Management System Using Wireless Sensor Networks

PubMed Central

Nellore, Kapileswar; Hancke, Gerhard P.

2016-01-01

Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research. PMID:26828489

Potential of dynamic spectrum allocation in LTE macro networks

NASA Astrophysics Data System (ADS)

Hoffmann, H.; Ramachandra, P.; Kovács, I. Z.; Jorguseski, L.; Gunnarsson, F.; Kürner, T.

2015-11-01

In recent years Mobile Network Operators (MNOs) worldwide are extensively deploying LTE networks in different spectrum bands and utilising different bandwidth configurations. Initially, the deployment is coverage oriented with macro cells using the lower LTE spectrum bands. As the offered traffic (i.e. the requested traffic from the users) increases the LTE deployment evolves with macro cells expanded with additional capacity boosting LTE carriers in higher frequency bands complemented with micro or small cells in traffic hotspot areas. For MNOs it is crucial to use the LTE spectrum assets, as well as the installed network infrastructure, in the most cost efficient way. The dynamic spectrum allocation (DSA) aims at (de)activating the available LTE frequency carriers according to the temporal and spatial traffic variations in order to increase the overall LTE system performance in terms of total network capacity by reducing the interference. This paper evaluates the DSA potential of achieving the envisaged performance improvement and identifying in which system and traffic conditions the DSA should be deployed. A self-optimised network (SON) DSA algorithm is also proposed and evaluated. The evaluations have been carried out in a hexagonal and a realistic site-specific urban macro layout assuming a central traffic hotspot area surrounded with an area of lower traffic with a total size of approximately 8 × 8 km2. The results show that up to 47 % and up to 40 % possible DSA gains are achievable with regards to the carried system load (i.e. used resources) for homogenous traffic distribution with hexagonal layout and for realistic site-specific urban macro layout, respectively. The SON DSA algorithm evaluation in a realistic site-specific urban macro cell deployment scenario including realistic non-uniform spatial traffic distribution shows insignificant cell throughput (i.e. served traffic) performance gains. Nevertheless, in the SON DSA investigations, a gain of up to 25 % has been observed when analysing the resource utilisation in the non-hotspot cells.

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

Variable speed limit strategies analysis with link transmission model on urban expressway

NASA Astrophysics Data System (ADS)

Li, Shubin; Cao, Danni

2018-02-01

The variable speed limit (VSL) is a kind of active traffic management method. Most of the strategies are used in the expressway traffic flow control in order to ensure traffic safety. However, the urban expressway system is the main artery, carrying most traffic pressure. It has similar traffic characteristics with the expressways between cities. In this paper, the improved link transmission model (LTM) combined with VSL strategies is proposed, based on the urban expressway network. The model can simulate the movement of the vehicles and the shock wave, and well balance the relationship between the amount of calculation and accuracy. Furthermore, the optimal VSL strategy can be proposed based on the simulation method. It can provide management strategies for managers. Finally, a simple example is given to illustrate the model and method. The selected indexes are the average density, the average speed and the average flow on the traffic network in the simulation. The simulation results show that the proposed model and method are feasible. The VSL strategy can effectively alleviate traffic congestion in some cases, and greatly promote the efficiency of the transportation system.

A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring

PubMed Central

Fernández-Lozano, J.J.; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A.

2015-01-01

Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach. PMID:26501278

An Intelligent Cooperative Visual Sensor Network for Urban Mobility

PubMed Central

Leone, Giuseppe Riccardo; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea

2017-01-01

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities. PMID:29125535

An Intelligent Cooperative Visual Sensor Network for Urban Mobility.

PubMed

Leone, Giuseppe Riccardo; Moroni, Davide; Pieri, Gabriele; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea; Marino, Francesco

2017-11-10

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.

Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hong; Aziz, H M Abdul; Young, Stan

Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections.more » In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.« less

Assessment of traffic noise levels in urban areas using different soft computing techniques.

PubMed

Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D

2016-10-01

Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.

Simulation of traffic control signal systems

NASA Technical Reports Server (NTRS)

Connolly, P. J.; Concannon, P. A.; Ricci, R. C.

1974-01-01

In recent years there has been considerable interest in the development and testing of control strategies for networks of urban traffic signal systems by simulation. Simulation is an inexpensive and timely method for evaluating the effect of these traffic control strategies since traffic phenomena are too complex to be defined by analytical models and since a controlled experiment may be hazardous, expensive, and slow in producing meaningful results. This paper describes the application of an urban traffic corridor program, to evaluate the effectiveness of different traffic control strategies for the Massachusetts Avenue TOPICS Project.

Spatial and temporal trends from an air quality sensor network near a heavily trafficked intersection

NASA Astrophysics Data System (ADS)

Orlando, P.; Vo, D.; Giossi, C.; George, L.

2017-12-01

With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.

Operations and safety of Super 2 corridors with higher volumes.

DOT National Transportation Integrated Search

2011-06-01

As traffic volumes increase, in both urban and rural areas, the demand on the highway network also : increases. Specifically, as rural traffic volumes rise in Texas, the pressure on the states network of two-lane : highways rises accordingly. Prev...

Fixed Point Learning Based Intelligent Traffic Control System

NASA Astrophysics Data System (ADS)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

Comparative analysis of the performance of One-Way and Two-Way urban road networks

NASA Astrophysics Data System (ADS)

Gheorghe, Carmen

2017-10-01

The fact that the number of vehicles is increasing year after year represents a challenge in road traffic management because it is necessary to adjust the road traffic, in order to prevent any incidents, using mostly the same road infrastructure. At this moment one-way road network provides efficient traffic flow for vehicles but it is not ideal for pedestrians. Therefore, a proper solution must be found and applied when and where it is necessary. Replacing one-way road network with two-way road network may be a viable solution especially if in the area is high pedestrian traffic. The paper aims to highlight the influence of both, one-way and two-way urban road networks through an experimental research which was performed by using traffic data collected in the field. Each of the two scenarios analyzed were based on the same traffic data, the same geometrical conditions of the road (lane width, total road segment width, road slopes, total length of the road network) and also the same signaling conditions (signalised intersection or roundabout). The analysis which involves two-way scenario reveals changes in the performance parameters like delay average, stops average, delay stop average and vehicle speed average. Based on the values obtained, it was possible to perform a comparative analysis between the real, one-way, scenario and the theoretical, two-way, scenario.

Gis-Based Route Finding Using ANT Colony Optimization and Urban Traffic Data from Different Sources

NASA Astrophysics Data System (ADS)

Davoodi, M.; Mesgari, M. S.

2015-12-01

Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

Traveler oriented traffic performance metrics using real time traffic data from the Midtown-in-Motion (MIM) project in Manhattan, NY.

DOT National Transportation Integrated Search

2013-10-01

In a congested urban street network the average traffic speed is an inadequate metric for measuring : speed changes that drivers can perceive from changes in traffic control strategies. : A driver oriented metric is needed. Stop frequency distrib...

Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation

NASA Astrophysics Data System (ADS)

Chen, Jingxu; Li, Zhibin; Jiang, Hang; Zhu, Senlai; Wang, Wei

2017-02-01

In recent years, many bicycle lanes on urban streets are replaced with vehicle parking places. Spaces for bicycle riding are reduced, resulting in changes in bicycle and vehicle operational features. The objective of this study is to estimate the impacts of on-street parking on heterogeneous traffic operation on urban streets. A cellular automaton (CA) model is developed and calibrated to simulate bicycle lane-changing on streets with on-street parking. Two types of street segments with different bicycle lane width are considered. From the simulation, two types of conflicts between bicycles and vehicles are identified which are frictional conflicts and blocking conflicts. Factors affecting the frequency of conflicts are also identified. Based on the results, vehicle delay is estimated for various traffic situations considering the range of occupancy levels for on-street parking. Later, a numerical network example is analyzed to estimate the network impact of on-street parking on traffic assignment and operation. Findings of the study are helpful to policies and design regarding on-street vehicle parking to improve the efficiency of traffic operations.

Encapsulating urban traffic rhythms into road networks.

PubMed

Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

2014-02-20

Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.

Encapsulating Urban Traffic Rhythms into Road Networks

PubMed Central

Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

2014-01-01

Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution. PMID:24553203

Understanding the topological characteristics and flow complexity of urban traffic congestion

NASA Astrophysics Data System (ADS)

Wen, Tzai-Hung; Chin, Wei-Chien-Benny; Lai, Pei-Chun

2017-05-01

For a growing number of developing cities, the capacities of streets cannot meet the rapidly growing demand of cars, causing traffic congestion. Understanding the spatial-temporal process of traffic flow and detecting traffic congestion are important issues associated with developing sustainable urban policies to resolve congestion. Therefore, the objective of this study is to propose a flow-based ranking algorithm for investigating traffic demands in terms of the attractiveness of street segments and flow complexity of the street network based on turning probability. Our results show that, by analyzing the topological characteristics of streets and volume data for a small fraction of street segments in Taipei City, the most congested segments of the city were identified successfully. The identified congested segments are significantly close to the potential congestion zones, including the officially announced most congested streets, the segments with slow moving speeds at rush hours, and the areas near significant landmarks. The identified congested segments also captured congestion-prone areas concentrated in the business districts and industrial areas of the city. Identifying the topological characteristics and flow complexity of traffic congestion provides network topological insights for sustainable urban planning, and these characteristics can be used to further understand congestion propagation.

The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios.

PubMed

Tian, Bin; Hou, Kun Mean; Zhou, Haiying

2016-06-21

The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination.

The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios

PubMed Central

Tian, Bin; Hou, Kun Mean; Zhou, Haiying

2016-01-01

The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination. PMID:27338393

Implementing and Simulating Dynamic Traffic Assignment with Intelligent Transportation Systems in Cube Avenue

NASA Technical Reports Server (NTRS)

Foytik, Peter; Robinson, Mike

2010-01-01

As urban populations and traffic congestion levels increase, effective use of information and communication tools and intelligent transportation systems as becoming increasingly important in order to maximize the efficiency of transportation networks. The appropriate placement and employment of these tools within a network is critical to their effectiveness. This presentation proposes and demonstrates the use of a commercial transportation simulation tool to simulate dynamic traffic assignment and rerouting to model route modifications as a result of traffic information.

Understanding characteristics in multivariate traffic flow time series from complex network structure

NASA Astrophysics Data System (ADS)

Yan, Ying; Zhang, Shen; Tang, Jinjun; Wang, Xiaofei

2017-07-01

Discovering dynamic characteristics in traffic flow is the significant step to design effective traffic managing and controlling strategy for relieving traffic congestion in urban cities. A new method based on complex network theory is proposed to study multivariate traffic flow time series. The data were collected from loop detectors on freeway during a year. In order to construct complex network from original traffic flow, a weighted Froenius norm is adopt to estimate similarity between multivariate time series, and Principal Component Analysis is implemented to determine the weights. We discuss how to select optimal critical threshold for networks at different hour in term of cumulative probability distribution of degree. Furthermore, two statistical properties of networks: normalized network structure entropy and cumulative probability of degree, are utilized to explore hourly variation in traffic flow. The results demonstrate these two statistical quantities express similar pattern to traffic flow parameters with morning and evening peak hours. Accordingly, we detect three traffic states: trough, peak and transitional hours, according to the correlation between two aforementioned properties. The classifying results of states can actually represent hourly fluctuation in traffic flow by analyzing annual average hourly values of traffic volume, occupancy and speed in corresponding hours.

An optimal general type-2 fuzzy controller for Urban Traffic Network.

PubMed

Khooban, Mohammad Hassan; Vafamand, Navid; Liaghat, Alireza; Dragicevic, Tomislav

2017-01-01

Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles. In this study, a combination of the general type-2 fuzzy logic sets and the Modified Backtracking Search Algorithm (MBSA) techniques are used in order to control the traffic signal scheduling and phase succession so as to guarantee a smooth flow of traffic with the least wait times and average queue length. The parameters of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges

NASA Astrophysics Data System (ADS)

Ren, Yihui; Ercsey-Ravasz, Mária; Wang, Pu; González, Marta C.; Toroczkai, Zoltán

2014-11-01

Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

PubMed Central

Zhang, Lun; Zhang, Meng; Yang, Wenchen; Dong, Decun

2015-01-01

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity. PMID:25802512

Self-control of traffic lights and vehicle flows in urban road networks

NASA Astrophysics Data System (ADS)

Lämmer, Stefan; Helbing, Dirk

2008-04-01

Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks, we propose a self-organization approach to traffic light control. The problem can be treated as a multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as 'green waves' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes.

Hybrid Optimization in Urban Traffic Networks

DOT National Transportation Integrated Search

1979-04-01

The hybrid optimization problem is formulated to provide a general theoretical framework for the analysis of a class of traffic control problems which takes into account the role of individual drivers as independent decisionmakers. Different behavior...

[Emission Characteristics of Vehicle Exhaust in Beijing Based on Actual Traffic Flow Information].

PubMed

Fan, Shou-bin; Tian, Ling-di; Zhang, Dong-xu; Qu, Song

2015-08-01

The basic data of traffic volume, vehicle type constitute and speed on road networks in Beijing was obtained fly modei simulation and field survey. Based on actual traffic flow information and. emission factors data with temporal and spatial distribution features, emission inventory of motor vehicle exhaust in Beijing was built on the ArcGIS platform, meanwhile, the actual road emission characteristics and spatial distribution of the pollutant emissions were analyzed. The results showed that the proportion of passenger car was higher than 89% on each type of road in the urban, and the proportion of passenger car was the highest in suburban roads as well while the pickup truck, medium truck, heavy truck, motorbus, tractor and motorcycle also occupied a certain proportion. There was a positive correlation between the pollutant emission intensity and traffic volume, and the emission intensity was generally higher in daytime than nighttime, but the diurnal variation trend of PM emission was not clear for suburban roads and the emission intensity was higher in nighttime than daytime for highway. The emission intensities in urban area, south, southeast and northeast areas near urban were higher than those in the western and northern mountainous areas with lower density of road network. The ring roads in urban and highways in suburban had higher emission intensity because of the heavy traffic volume.

Using recorded sound spectra profile as input data for real-time short-term urban road-traffic-flow estimation.

PubMed

Torija, Antonio J; Ruiz, Diego P

2012-10-01

Road traffic has a heavy impact on the urban sound environment, constituting the main source of noise and widely dominating its spectral composition. In this context, our research investigates the use of recorded sound spectra as input data for the development of real-time short-term road traffic flow estimation models. For this, a series of models based on the use of Multilayer Perceptron Neural Networks, multiple linear regression, and the Fisher linear discriminant were implemented to estimate road traffic flow as well as to classify it according to the composition of heavy vehicles and motorcycles/mopeds. In view of the results, the use of the 50-400 Hz and 1-2.5 kHz frequency ranges as input variables in multilayer perceptron-based models successfully estimated urban road traffic flow with an average percentage of explained variance equal to 86%, while the classification of the urban road traffic flow gave an average success rate of 96.1%. Copyright © 2012 Elsevier B.V. All rights reserved.

Performance Evaluation of a Prototyped Wireless Ground Sensor Network

DTIC Science & Technology

2005-03-01

the network was capable of dynamic adaptation to failure and degradation. 14. SUBJECT TERMS: Wireless Sensor Network , Unmanned Sensor, Unattended...2 H. WIRELESS SENSOR NETWORKS .................................................................... 3...zation, and network traffic. The evaluated scenarios included outdoor, urban and indoor environments. The characteristics of wireless sensor networks , types

Classification of Traffic Related Short Texts to Analyse Road Problems in Urban Areas

NASA Astrophysics Data System (ADS)

Saldana-Perez, A. M. M.; Moreno-Ibarra, M.; Tores-Ruiz, M.

2017-09-01

The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media's publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

Alternative approaches to condition monitoring in freeway management systems.

DOT National Transportation Integrated Search

2002-01-01

In response to growing concerns over traffic congestion, traffic management systems have been built in large urban areas in an effort to improve the efficiency and safety of the transportation network. This research effort developed an automated cond...

Roadway usage patterns : urban case studies - final report

DOT National Transportation Integrated Search

1996-01-01

The Orlando Test Network Study was one of a series of investigations conducted as part of the TravTek operational test of an advanced traveler information and traffic management system (ATIS/ATMS). The TravTek system consisted of the Orlando Traffic ...

Optimizing Energy Consumption in Vehicular Sensor Networks by Clustering Using Fuzzy C-Means and Fuzzy Subtractive Algorithms

NASA Astrophysics Data System (ADS)

Ebrahimi, A.; Pahlavani, P.; Masoumi, Z.

2017-09-01

Traffic monitoring and managing in urban intelligent transportation systems (ITS) can be carried out based on vehicular sensor networks. In a vehicular sensor network, vehicles equipped with sensors such as GPS, can act as mobile sensors for sensing the urban traffic and sending the reports to a traffic monitoring center (TMC) for traffic estimation. The energy consumption by the sensor nodes is a main problem in the wireless sensor networks (WSNs); moreover, it is the most important feature in designing these networks. Clustering the sensor nodes is considered as an effective solution to reduce the energy consumption of WSNs. Each cluster should have a Cluster Head (CH), and a number of nodes located within its supervision area. The cluster heads are responsible for gathering and aggregating the information of clusters. Then, it transmits the information to the data collection center. Hence, the use of clustering decreases the volume of transmitting information, and, consequently, reduces the energy consumption of network. In this paper, Fuzzy C-Means (FCM) and Fuzzy Subtractive algorithms are employed to cluster sensors and investigate their performance on the energy consumption of sensors. It can be seen that the FCM algorithm and Fuzzy Subtractive have been reduced energy consumption of vehicle sensors up to 90.68% and 92.18%, respectively. Comparing the performance of the algorithms implies the 1.5 percent improvement in Fuzzy Subtractive algorithm in comparison.

Multilane Traffic Flow Modeling Using Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina

2018-02-01

The paper deals with the mathematical modeling of traffic flows on urban road networks using microscopic approach. The model is based on the cellular automata theory and presents a generalization of the Nagel-Schreckenberg model to a multilane case. The created program package allows to simulate traffic on various types of road fragments (T or X type intersection, strait road elements, etc.) and on road networks that consist of these elements. Besides that, it allows to predict the consequences of various decisions regarding road infrastructure changes, such as: number of lanes increasing/decreasing, putting new traffic lights into operation, building new roads, entrances/exits, road junctions.

Link state relationships under incident conditions : using a CTM-based linear programming dynamic traffic assignment model.

DOT National Transportation Integrated Search

2010-03-01

Urban transportation networks, consisting of numerous links and nodes, experience traffic incidents such as accidents and road : maintenance work. A typical consequence of incidents is congestion which results in long queues and causes high travel ti...

Link State Relationships Under Incident Conditions: Using a CTM-Based Linear Programming Dynamic Traffic Assignment Model

DOT National Transportation Integrated Search

2010-03-01

Urban transportation networks, consisting of numerous links and nodes, experience traffic incidents such as accidents and road maintenance work. A typical consequence of incidents is congestion which results in long queues and causes high travel time...

Optimal signal timing design for urban street networks under user equilibrium based traffic conditions : final report.

DOT National Transportation Integrated Search

2016-09-20

In the ever-growing travel demand, traffic congestion on freeways and expressways : recurs more frequently at a higher number of locations and for longer durations with : added severity. This becomes especially true in large metropolitan areas. Parti...

SATURN (Situational Awareness Tool for Urban Responder Networks)

DTIC Science & Technology

2012-07-01

timeline. SATURN is applicable to a broad set of law enforcement, security, and counterterrorism missions typically addressed by urban responders...Keywords-video analytics; sensor fusion; video; urban responders I. INTRODUCTION Urban authorities have a broad set of missions . Duties vary in...both the frequency of occurrence and in the complexity of execution. They include everyday public safety missions such as traffic enforcement as

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

PubMed

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

PubMed Central

2018-01-01

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884

Monitoring and assessing global impacts of roads and off-road vehicle traffic

USDA-ARS?s Scientific Manuscript database

Rapid increases in the number of vehicles, urban sprawl, exurban development and infrastructure development for energy and water have led to dramatic increases in both the size and extent of the global road network. Anecdotal evidence suggests that off-road vehicle traffic has also increased in many...

Output power distributions of terminals in a 3G mobile communication network.

PubMed

Persson, Tomas; Törnevik, Christer; Larsson, Lars-Eric; Lovén, Jan

2012-05-01

The objective of this study was to examine the distribution of the output power of mobile phones and other terminals connected to a 3G network in Sweden. It is well known that 3G terminals can operate with very low output power, particularly for voice calls. Measurements of terminal output power were conducted in the Swedish TeliaSonera 3G network in November 2008 by recording network statistics. In the analysis, discrimination was made between rural, suburban, urban, and dedicated indoor networks. In addition, information about terminal output power was possible to collect separately for voice and data traffic. Information from six different Radio Network Controllers (RNCs) was collected during at least 1 week. In total, more than 800000 h of voice calls were collected and in addition to that a substantial amount of data traffic. The average terminal output power for 3G voice calls was below 1 mW for any environment including rural, urban, and dedicated indoor networks. This is <1% of the maximum available output power. For data applications the average output power was about 6-8 dB higher than for voice calls. For rural areas the output power was about 2 dB higher, on average, than in urban areas. Copyright © 2011 Wiley Periodicals, Inc.

Road traffic injuries in Colombia.

PubMed

Rodríguez, Deysi Yasmin; Fernández, Francisco José; Acero Velásquez, Hugo

2003-01-01

Road traffic injuries are a leading public health problem in Colombia. Pedestrians are the most vulnerable road users, especially in the main urban centers of Bogotá, Medellin and Cali. Data analyzed in this report include official statistics from the National Police and the National Institute of Legal Medicine and Forensic Sciences for 1996-2000, and results of a study conducted at the National University of Colombia in 2000. Methods from the Highway Capacity Manual were used for determining physical and technical variables, and a Geographical Information System tool was used for the location and spatial analysis of the road traffic crashes. Pedestrians accounted for close to 32% of injuries and 40% of the deaths from road traffic crashes. The problem of road traffic crashes existed predominately in urban areas. In the main urban centers, pedestrians constituted nearly 68% of road traffic crash victims. The high level of risky road use behaviors demonstrated by pedestrians and drivers, and inadequate infrastructure for safe mobility of pedestrians in some sections of the road network were the main contributing factors. Major improvements were achieved in Bogotá following enhancements to the municipal transport system and other policies introduced since 1995. In conclusion, policies and programs for improving road safety, in particular pedestrian safety, and strengthening urban planning are top priority.

Safety analysis of urban arterials at the meso level.

PubMed

Li, Jia; Wang, Xuesong

2017-11-01

Urban arterials form the main structure of street networks. They typically have multiple lanes, high traffic volume, and high crash frequency. Classical crash prediction models investigate the relationship between arterial characteristics and traffic safety by treating road segments and intersections as isolated units. This micro-level analysis does not work when examining urban arterial crashes because signal spacing is typically short for urban arterials, and there are interactions between intersections and road segments that classical models do not accommodate. Signal spacing also has safety effects on both intersections and road segments that classical models cannot fully account for because they allocate crashes separately to intersections and road segments. In addition, classical models do not consider the impact on arterial safety of the immediately surrounding street network pattern. This study proposes a new modeling methodology that will offer an integrated treatment of intersections and road segments by combining signalized intersections and their adjacent road segments into a single unit based on road geometric design characteristics and operational conditions. These are called meso-level units because they offer an analytical approach between micro and macro. The safety effects of signal spacing and street network pattern were estimated for this study based on 118 meso-level units obtained from 21 urban arterials in Shanghai, and were examined using CAR (conditional auto regressive) models that corrected for spatial correlation among the units within individual arterials. Results showed shorter arterial signal spacing was associated with higher total and PDO (property damage only) crashes, while arterials with a greater number of parallel roads were associated with lower total, PDO, and injury crashes. The findings from this study can be used in the traffic safety planning, design, and management of urban arterials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks

PubMed Central

Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing

2016-01-01

Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring.

PubMed

Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio

2016-12-29

One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps' generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work.

Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring

PubMed Central

Alsina-Pagès, Rosa Ma; Hernandez-Jayo, Unai; Alías, Francesc; Angulo, Ignacio

2016-01-01

One of the main priorities of smart cities is improving the quality of life of their inhabitants. Traffic noise is one of the pollutant sources that causes a negative impact on the quality of life of citizens, which is gaining attention among authorities. The European Commission has promoted the Environmental Noise Directive 2002/49/EC (END) to inform citizens and to prevent the harmful effects of noise exposure. The measure of acoustic levels using noise maps is a strategic issue in the END action plan. Noise maps are typically calculated by computing the average noise during one year and updated every five years. Hence, the implementation of dynamic noise mapping systems could lead to short-term plan actions, besides helping to better understand the evolution of noise levels along time. Recently, some projects have started the monitoring of noise levels in urban areas by means of acoustic sensor networks settled in strategic locations across the city, while others have taken advantage of collaborative citizen sensing mobile applications. In this paper, we describe the design of an acoustic low-cost sensor network installed on public buses to measure the traffic noise in the city in real time. Moreover, the challenges that a ubiquitous bus acoustic measurement system entails are enumerated and discussed. Specifically, the analysis takes into account the feature extraction of the audio signal, the identification and separation of the road traffic noise from urban traffic noise, the hardware platform to measure and process the acoustic signal, the connectivity between the several nodes of the acoustic sensor network to store the data and, finally, the noise maps’ generation process. The implementation and evaluation of the proposal in a real-life scenario is left for future work. PMID:28036065

WSN system design by using an innovative neural network model to perform thermals forecasting in a urban canyon scenario

NASA Astrophysics Data System (ADS)

Giuseppina, Nicolosi; Salvatore, Tirrito

2015-12-01

Wireless Sensor Networks (WSNs) were studied by researchers in order to manage Heating, Ventilating and Air-Conditioning (HVAC) indoor systems. WSN can be useful specially to regulate indoor confort in a urban canyon scenario, where the thermal parameters vary rapidly, influenced by outdoor climate changing. This paper shows an innovative neural network approach, by using WSN data collected, in order to forecast the indoor temperature to varying the outdoor conditions based on climate parameters and boundary conditions typically of urban canyon. In this work more attention will be done to influence of traffic jam and number of vehicles in queue.

Comparison of classical statistical methods and artificial neural network in traffic noise prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nedic, Vladimir, E-mail: vnedic@kg.ac.rs; Despotovic, Danijela, E-mail: ddespotovic@kg.ac.rs; Cvetanovic, Slobodan, E-mail: slobodan.cvetanovic@eknfak.ni.ac.rs

2014-11-15

Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. Themore » output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.« less

A research of the community’s opening to the outside world

NASA Astrophysics Data System (ADS)

Xu, Lan; Liu, Xiangzhuo

2017-03-01

Closed residential areas, called community, the traffic network and result in various degrees of traffic congestion such as amputating, dead ends and T-shaped roads. In order to reveal the mechanism of the congestion, establish an effective evaluation index system and finally provide theoretical basis for the study of traffic congestion, we have done researches on factors for traffic congestion and have established a scientific evaluation index system combining experiences home and abroad, based on domestic congestion status. Firstly, we analyse the traffic network as the entry point, and then establish the evaluation model of road capacity with the method of AHP index system. Secondly, we divide the condition of urban congestion into 5 levels from congestion to smoothness. Besides, with VISSIM software, simulations about traffic capacity before and after community opening are carried out. Finally, we provide forward reasonable suggestions upon the combination of models and reality.

Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

NASA Astrophysics Data System (ADS)

Hamdan, H. G. Muhammad; Khalifah, O. O.

2017-11-01

Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.

Traffic Congestion Detection System through Connected Vehicles and Big Data

PubMed Central

Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo

2016-01-01

This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur. PMID:27136548

Traffic Congestion Detection System through Connected Vehicles and Big Data.

PubMed

Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo

2016-04-28

This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.

Estimated long-term outdoor air pollution concentrations in a cohort study

NASA Astrophysics Data System (ADS)

Beelen, Rob; Hoek, Gerard; Fischer, Paul; Brandt, Piet A. van den; Brunekreef, Bert

Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods. Long-term exposure to nitrogen dioxide (NO 2), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO 2) was estimated. Exposure at each home address ( N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated. The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO 2, NO, BS, and SO 2 concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO 2, NO, BS and SO 2, respectively. We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations.

Resistance and resilience of floating mat fens in interior Alaska following airboat disturbance

Treesearch

Amy Zacheis; Kate Doran

2009-01-01

The floating mat fens of the Tanana Flats in interior Alaska are productive wetlands near the urban center of Fairbanks. Airboat traffic has created a network of trails through the floating vegetation mats. We established protected areas along established trails, which allowed for measurement of plant community resistance to airboat traffic and resilience following...

Assessment of ultrafine particles and noise measurements using fuzzy logic and data mining techniques.

PubMed

Fernández-Camacho, R; Brito Cabeza, I; Aroba, J; Gómez-Bravo, F; Rodríguez, S; de la Rosa, J

2015-04-15

This study focuses on correlations between total number concentrations, road traffic emissions and noise levels in an urban area in the southwest of Spain during the winter and summer of 2009. The high temporal correlation between sound pressure levels, traffic intensity, particle number concentrations related to traffic, black carbon and NOx concentrations suggests that noise is linked to traffic emissions as a main source of pollution in urban areas. First, the association of these different variables was studied using PreFuRGe, a computational tool based on data mining and fuzzy logic. The results showed a clear association between noise levels and road-traffic intensity for non-extremely high wind speed levels. This behaviour points, therefore, to vehicular emissions being the main source of urban noise. An analysis for estimating the total number concentration from noise levels is also proposed in the study. The high linearity observed between particle number concentrations linked to traffic and noise levels with road traffic intensity can be used to calculate traffic related particle number concentrations experimentally. At low wind speeds, there are increases in noise levels of 1 dB for every 100 vehicles in circulation. This is equivalent to 2000 cm(-3) per vehicle in winter and 500 cm(-3) in summer. At high wind speeds, wind speed could be taken into account. This methodology allows low cost sensors to be used as a proxy for total number concentration monitoring in urban air quality networks. Copyright © 2015 Elsevier B.V. All rights reserved.

Trip-oriented travel time prediction (TOTTP) with historical vehicle trajectories

NASA Astrophysics Data System (ADS)

Xu, Tao; Li, Xiang; Claramunt, Christophe

2018-06-01

Accurate travel time prediction is undoubtedly of importance to both traffic managers and travelers. In highly-urbanized areas, trip-oriented travel time prediction (TOTTP) is valuable to travelers rather than traffic managers as the former usually expect to know the travel time of a trip which may cross over multiple road sections. There are two obstacles to the development of TOTTP, including traffic complexity and traffic data coverage.With large scale historical vehicle trajectory data and meteorology data, this research develops a BPNN-based approach through integrating multiple factors affecting trip travel time into a BPNN model to predict trip-oriented travel time for OD pairs in urban network. Results of experiments demonstrate that it helps discover the dominate trends of travel time changes daily and weekly, and the impact of weather conditions is non-trivial.

Carbon dioxide emission and bio-capacity indexing for transportation activities: A methodological development in determining the sustainability of vehicular transportation systems.

PubMed

Labib, S M; Neema, Meher Nigar; Rahaman, Zahidur; Patwary, Shahadath Hossain; Shakil, Shahadat Hossain

2018-06-09

CO 2 emissions from urban traffic are a major concern in an era of increasing ecological disequilibrium. Adding to the problem net CO 2 emissions in urban settings are worsened due to the decline of bio-productive areas in many cities. This decline exacerbates the lack of capacity to sequestrate CO 2 at the micro and meso-scales resulting in increased temperatures and decreased air quality within city boundaries. Various transportation and environmental strategies have been implemented to address traffic related CO 2 emissions, however current literature identifies difficulties in pinpointing these critical areas of maximal net emissions in urban transport networks. This study attempts to close this gap in the literature by creating a new lay-person friendly index that combines CO 2 emissions from vehicles and the bio-capacity of specific traffic zones to identify these areas at the meso-scale within four ranges of values with the lowest index values representing the highest net CO 2 levels. The study used traffic volume, fuel types, and vehicular travel distance to estimate CO 2 emissions at major links in Dhaka, Bangladesh's capital city's transportation network. Additionally, using remote-sensing tools, adjacent bio-productive areas were identified and their bio-capacity for CO 2 sequestration estimated. The bio-productive areas were correlated with each traffic zone under study resulting in an Emission Bio-Capacity index (EBI) value estimate for each traffic node. Among the ten studied nodes in Dhaka City, nine had very low EBI values, correlating to very high CO 2 emissions and low bio-capacity. As a result, the study considered these areas unsustainable as traffic nodes going forward. Key reasons for unsustainability included increasing use of motorized traffic, absence of optimized signal systems, inadequate public transit options, disincentives for fuel free transport (FFT), and a decline in bio-productive areas. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative analysis of quantitative efficiency evaluation methods for transportation networks

PubMed Central

He, Yuxin; Hong, Jian

2017-01-01

An effective evaluation of transportation network efficiency could offer guidance for the optimal control of urban traffic. Based on the introduction and related mathematical analysis of three quantitative evaluation methods for transportation network efficiency, this paper compares the information measured by them, including network structure, traffic demand, travel choice behavior and other factors which affect network efficiency. Accordingly, the applicability of various evaluation methods is discussed. Through analyzing different transportation network examples it is obtained that Q-H method could reflect the influence of network structure, traffic demand and user route choice behavior on transportation network efficiency well. In addition, the transportation network efficiency measured by this method and Braess’s Paradox can be explained with each other, which indicates a better evaluation of the real operation condition of transportation network. Through the analysis of the network efficiency calculated by Q-H method, it can also be drawn that a specific appropriate demand is existed to a given transportation network. Meanwhile, under the fixed demand, both the critical network structure that guarantees the stability and the basic operation of the network and a specific network structure contributing to the largest value of the transportation network efficiency can be identified. PMID:28399165

Comparative analysis of quantitative efficiency evaluation methods for transportation networks.

PubMed

He, Yuxin; Qin, Jin; Hong, Jian

2017-01-01

An effective evaluation of transportation network efficiency could offer guidance for the optimal control of urban traffic. Based on the introduction and related mathematical analysis of three quantitative evaluation methods for transportation network efficiency, this paper compares the information measured by them, including network structure, traffic demand, travel choice behavior and other factors which affect network efficiency. Accordingly, the applicability of various evaluation methods is discussed. Through analyzing different transportation network examples it is obtained that Q-H method could reflect the influence of network structure, traffic demand and user route choice behavior on transportation network efficiency well. In addition, the transportation network efficiency measured by this method and Braess's Paradox can be explained with each other, which indicates a better evaluation of the real operation condition of transportation network. Through the analysis of the network efficiency calculated by Q-H method, it can also be drawn that a specific appropriate demand is existed to a given transportation network. Meanwhile, under the fixed demand, both the critical network structure that guarantees the stability and the basic operation of the network and a specific network structure contributing to the largest value of the transportation network efficiency can be identified.

Trends of NOx, NO2 and O3 concentrations at three different types of air quality monitoring stations in Athens, Greece

NASA Astrophysics Data System (ADS)

Mavroidis, I.; Ilia, M.

2012-12-01

This work presents a systematic analysis and evaluation of the historic and current levels of atmospheric pollution in the Athens metropolitan region, regarding nitrogen oxides (NOx = NO + NO2), ozone (O3) and the NO2/NOx and NO/NO2 concentration ratios. Hourly, daily, monthly, seasonal and annual pollutant variations are examined and compared, using the results of concentration time series from three different stations of the national network for air pollution monitoring, one urban-traffic, one urban-background and one suburban-background. Concentration data are also related to meteorological parameters. The results show that the traffic affected station of Patission Street presents the higher NOx values and the lower concentrations of O3, while it is the station with the highest number of NO2 limit exceedances. The monitoring data suggest, inter alia, that there is a change in the behaviour of the suburban-background station of Liossia at about year 2000, indicating that the exact location of this station may need to be reconsidered. Comparison of NOx concentrations in Athens with concentrations in urban areas of other countries reveal that the Patission urban-traffic station records very high NOx concentrations, while remarkably high is the ratio of NO2 concentrations recorded at the urban-traffic vs. the urban-background station in Athens, indicating the overarching role of vehicles and traffic congestion on NO2 formation. The NO2/NOx ratio in the urban-traffic station appears to be almost constant with time, while it has been increasing in other urban areas, such as London and Seoul, suggesting an increased effect of primary NO2 in these areas. Diesel passenger cars were only recently allowed in Athens and, therefore, NO2 trends should be carefully monitored since a possible increase in primary NO2 may affect compliance with NO2 air quality standards.

Understanding re-distribution of road deposited particle-bound pollutants using a Bayesian Network (BN) approach.

PubMed

Liu, An; Wijesiri, Buddhi; Hong, Nian; Zhu, Panfeng; Egodawatta, Prasanna; Goonetilleke, Ashantha

2018-05-08

Road deposited pollutants (build-up) are continuously re-distributed by external factors such as traffic and wind turbulence, influencing stormwater runoff quality. However, current stormwater quality modelling approaches do not account for the re-distribution of pollutants. This undermines the accuracy of stormwater quality predictions, constraining the design of effective stormwater treatment measures. This study, using over 1000 data points, developed a Bayesian Network modelling approach to investigate the re-distribution of pollutant build-up on urban road surfaces. BTEX, which are a group of highly toxic pollutants, was the case study pollutants. Build-up sampling was undertaken in Shenzhen, China, using a dry and wet vacuuming method. The research outcomes confirmed that the vehicle type and particle size significantly influence the re-distribution of particle-bound BTEX. Compared to heavy-duty traffic in commercial areas, light-duty traffic dominates the re-distribution of particles of all size ranges. In industrial areas, heavy-duty traffic re-distributes particles >75 μm, and light-duty traffic re-distributes particles <75 μm. In residential areas, light-duty traffic re-distributes particles >300 μm and <75 μm and heavy-duty traffic re-distributes particles in the 300-150 μm range. The study results provide important insights to improve stormwater quality modelling and the interpretation of modelling outcomes, contributing to safeguard the urban water environment. Copyright © 2018 Elsevier B.V. All rights reserved.

Evaluation of Deployment Challenges of Wireless Sensor Networks at Signalized Intersections

PubMed Central

Azpilicueta, Leyre; López-Iturri, Peio; Aguirre, Erik; Martínez, Carlos; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2016-01-01

With the growing demand of Intelligent Transportation Systems (ITS) for safer and more efficient transportation, research on and development of such vehicular communication systems have increased considerably in the last years. The use of wireless networks in vehicular environments has grown exponentially. However, it is highly important to analyze radio propagation prior to the deployment of a wireless sensor network in such complex scenarios. In this work, the radio wave characterization for ISM 2.4 GHz and 5 GHz Wireless Sensor Networks (WSNs) deployed taking advantage of the existence of traffic light infrastructure has been assessed. By means of an in-house developed 3D ray launching algorithm, the impact of topology as well as urban morphology of the environment has been analyzed, emulating the realistic operation in the framework of the scenario. The complexity of the scenario, which is an intersection city area with traffic lights, vehicles, people, buildings, vegetation and urban environment, makes necessary the channel characterization with accurate models before the deployment of wireless networks. A measurement campaign has been conducted emulating the interaction of the system, in the vicinity of pedestrians as well as nearby vehicles. A real time interactive application has been developed and tested in order to visualize and monitor traffic as well as pedestrian user location and behavior. Results show that the use of deterministic tools in WSN deployment can aid in providing optimal layouts in terms of coverage, capacity and energy efficiency of the network. PMID:27455270

Evaluation of Deployment Challenges of Wireless Sensor Networks at Signalized Intersections.

PubMed

Azpilicueta, Leyre; López-Iturri, Peio; Aguirre, Erik; Martínez, Carlos; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2016-07-22

With the growing demand of Intelligent Transportation Systems (ITS) for safer and more efficient transportation, research on and development of such vehicular communication systems have increased considerably in the last years. The use of wireless networks in vehicular environments has grown exponentially. However, it is highly important to analyze radio propagation prior to the deployment of a wireless sensor network in such complex scenarios. In this work, the radio wave characterization for ISM 2.4 GHz and 5 GHz Wireless Sensor Networks (WSNs) deployed taking advantage of the existence of traffic light infrastructure has been assessed. By means of an in-house developed 3D ray launching algorithm, the impact of topology as well as urban morphology of the environment has been analyzed, emulating the realistic operation in the framework of the scenario. The complexity of the scenario, which is an intersection city area with traffic lights, vehicles, people, buildings, vegetation and urban environment, makes necessary the channel characterization with accurate models before the deployment of wireless networks. A measurement campaign has been conducted emulating the interaction of the system, in the vicinity of pedestrians as well as nearby vehicles. A real time interactive application has been developed and tested in order to visualize and monitor traffic as well as pedestrian user location and behavior. Results show that the use of deterministic tools in WSN deployment can aid in providing optimal layouts in terms of coverage, capacity and energy efficiency of the network.

Quantifying travel time variability in transportation networks.

DOT National Transportation Integrated Search

2010-03-01

Nonrecurring congestion creates significant delay on freeways in urban areas, lending importance : to the study of facility reliability. In locations where traffic detectors record and archive data, : approximate probability distributions for travel ...

Investigation of the impact of low cost traffic engineering measures on road safety in urban areas.

PubMed

Yannis, George; Kondyli, Alexandra; Georgopoulou, Xenia

2014-01-01

This paper investigates the impact of low cost traffic engineering measures (LCTEMs) on the improvement of road safety in urban areas. A number of such measures were considered, such as speed humps, woonerfs, raised intersections and other traffic calming measures, which have been implemented on one-way, one-lane roads in the Municipality of Neo Psychiko in the Greater Athens Area. Data were analysed using the before-and-after safety analysis methodology with large control group. The selected control group comprised of two Municipalities in the Athens Greater Area, which present similar road network and land use characteristics with the area considered. The application of the methodology showed that the total number of crashes presented a statistically significant reduction, which can be possibly attributed to the introduction of LCTEMs. This reduction concerns passenger cars and single-vehicle crashes and is possibly due to the behavioural improvement of drivers of 25 years old or more. The results of this research are very useful for the identification of the appropriate low cost traffic engineering countermeasures for road safety problems in urban areas.

A dense Black Carbon network in the region of Paris, France: Implementation, objectives, and first results

NASA Astrophysics Data System (ADS)

Sciare, Jean; Petit, Jean-Eudes; Sarda-Esteve, Roland; Bonnaire, Nicolas; Gros, Valérie; Pernot, Pierre; Ghersi, Véronique; Ampe, Christophe; Songeur, Charlotte; Brugge, Benjamin; Debert, Christophe; Favez, Olivier; Le Priol, Tiphaine; Mocnik, Grisa

2013-04-01

Motivations. Road traffic and domestic wood burning emissions are two major contributors of particulate pollution in our cities. These two sources emit ultra-fine, soot containing, particles in the atmosphere, affecting health adversely, increasing morbidity and mortality from cardiovascular and respiratory conditions and casing lung cancer. A better characterization of soot containing aerosol sources in our major cities provides useful information for policy makers for assessment, implementation and monitoring of strategies to tackle air pollution issues affecting human health with additional benefits for climate change. Objectives. This study on local sources of primary Particulate Matter (PM) in the megacity of Paris is a follow-up of several programs (incl. EU-FP7-MEGAPOLI) that have shown that fine PM - in the Paris background atmosphere - is mostly secondary and imported. A network of 14 stations of Black Carbon has been implemented in the larger region of Paris to provide highly spatially resolved long term survey of local combustion aerosols. To our best knowledge, this is the first time that such densely BC network is operating over a large urban area, providing novel information on the spatial/temporal distribution of combustion aerosols within a post-industrialized megacity. Experimental. As part of the PRIMEQUAL "PREQUALIF" project, a dense Black Carbon network (of 14 stations) has been installed over the city of Paris beginning of 2012 in order to produce spatially resolved Equivalent Black Carbon (EBC) concentration maps with high time resolution through modeling and data assimilation. This network is composed of various real-time instruments (Multi-Angle Absorption Photometer, MAAP by THERMO; Multi-wavelength Aethalometers by MAGEE Scientific) implemented in contrasted sites (rural background, urban background, traffic) complementing the regulated measurements (PM, NOx) in the local air quality network AIRPARIF (http://www.airparif.asso.fr/). Contribution of imported versus local EBC is calculated using the "Lenschow" methodology (Lenschow et al., 2001), whereas the influence of domestic wood burning EBC (vs traffic) over the region of Paris is evaluated using the Aethalometer model developed by Sandradewi et al. (2008). Results and discussion. First results of this BC network are presented here including the temporal variations of EBC from wood burning (domestic heating) and fossil fuel (traffic) for the various sites (1-year observation for rural background and traffic sites; 4-year observations for urban background). The local versus imported contributions of EBC are also presented and discussed for these 2 sources. References. Lenschow, P., et al., Some ideas about the sources of PM10, Atmospheric Environment 35 Supplement No. 1 (2001) S23-S33 Sandradewi, J., et al., Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter, Environ. Sci. Technol., 42, 3316-3323, 2008

Assessing transfer property and reliability of urban bus network based on complex network theory

NASA Astrophysics Data System (ADS)

Zhang, Hui; Zhuge, Cheng-Xiang; Zhao, Xiang; Song, Wen-Bo

Transfer reliability has an important impact on the urban bus network. The proportion of zero and one transfer time is a key indicator to measure the connectivity of bus networks. However, it is hard to calculate the transfer time between nodes because of the complicated network structure. In this paper, the topological structures of urban bus network in Jinan are constructed by space L and space P. A method to calculate transfer times between stations has been proposed by reachable matrix under space P. The result shows that it is efficient to calculate the transfer time between nodes in large networks. In order to test the transfer reliability, a node failure process has been built according to degree, clustering coefficient and betweenness centrality under space L and space P. The results show that the deliberate attack by betweenness centrality under space P is more effective compared with other five attack modes. This research could provide a power tool to find hub stations in bus networks and give a help for traffic manager to guarantee the normal operation of urban bus systems.

Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment.

PubMed

Liu, Hai-Ying; Skjetne, Erik; Kobernus, Mike

2013-11-04

We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations.

Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment

PubMed Central

2013-01-01

We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations. PMID:24188173

The Vehicular Information Space Framework

NASA Astrophysics Data System (ADS)

Prinz, Vivian; Schlichter, Johann; Schweiger, Benno

Vehicular networks are distributed, self-organizing and highly mobile ad hoc networks. They allow for providing drivers with up-to-the-minute information about their environment. Therefore, they are expected to be a decisive future enabler for enhancing driving comfort and safety. This article introduces the Vehicular Information Space framework (VIS). Vehicles running the VIS form a kind of distributed database. It enables them to provide information like existing hazards, parking spaces or traffic densities in a location aware and fully distributed manner. In addition, vehicles can retrieve, modify and delete these information items. The underlying algorithm is based on features derived from existing structured Peer-to-Peer algorithms and extended to suit the specific characteristics of highly mobile ad hoc networks. We present, implement and simulate the VIS using a motorway and an urban traffic environment. Simulation studies on VIS message occurrence show that the VIS implies reasonable traffic overhead. Also, overall VIS message traffic is independent from the number of information items provided.

Improved traffic operations through real-time data collection and control.

DOT National Transportation Integrated Search

2016-05-01

Intersections are a major source of delay in urban networks, and reservation-based intersection control for : autonomous vehicles has great potential to improve intersection throughput. However, despite the high : flexibility in reservations, existin...

Quality of traffic flow on urban arterial streets and its relationship with safety.

PubMed

Dixit, Vinayak V; Pande, Anurag; Abdel-Aty, Mohamed; Das, Abhishek; Radwan, Essam

2011-09-01

The two-fluid model for vehicular traffic flow explains the traffic on arterials as a mix of stopped and running vehicles. It describes the relationship between the vehicles' running speed and the fraction of running vehicles. The two parameters of the model essentially represent 'free flow' travel time and level of interaction among vehicles, and may be used to evaluate urban roadway networks and urban corridors with partially limited access. These parameters are influenced by not only the roadway characteristics but also by behavioral aspects of driver population, e.g., aggressiveness. Two-fluid models are estimated for eight arterial corridors in Orlando, FL for this study. The parameters of the two-fluid model were used to evaluate corridor level operations and the correlations of these parameters' with rates of crashes having different types/severity. Significant correlations were found between two-fluid parameters and rear-end and angle crash rates. Rate of severe crashes was also found to be significantly correlated with the model parameter signifying inter-vehicle interactions. While there is need for further analysis, the findings suggest that the two-fluid model parameters may have potential as surrogate measures for traffic safety on urban arterial streets. Copyright © 2011 Elsevier Ltd. All rights reserved.

Examining the relationship between community design and crash incidence.

DOT National Transportation Integrated Search

2009-07-01

This study seeks to understand how urban formspecifically land use and street network configurations : may influence the incidence of traffic-related crashes injuries and deaths. It begins with an historic : overview of the safety concepts that...

Network Performance Evaluation Model for assessing the impacts of high-occupancy vehicle facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janson, B.N.; Zozaya-Gorostiza, C.; Southworth, F.

1986-09-01

A model to assess the impacts of major high-occupancy vehicle (HOV) facilities on regional levels of energy consumption and vehicle air pollution emissions in urban aeas is developed and applied. This model can be used to forecast and compare the impacts of alternative HOV facility design and operation plans on traffic patterns, travel costs, model choice, travel demand, energy consumption and vehicle emissions. The model is designed to show differences in the overall impacts of alternative HOV facility types, locations and operation plans rather than to serve as a tool for detailed engineering design and traffic planning studies. The Networkmore » Performance Evaluation Model (NETPEM) combines several urban transportation planning models within a multi-modal network equilibrium framework including modules with which to define the type, location and use policy of the HOV facility to be tested, and to assess the impacts of this facility.« less

Visual traffic jam analysis based on trajectory data.

PubMed

Wang, Zuchao; Lu, Min; Yuan, Xiaoru; Zhang, Junping; van de Wetering, Huub

2013-12-01

In this work, we present an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system.

Building a Multivariable Linear Regression Model of On-road Traffic for Creation of High Resolution Emission Inventories

NASA Astrophysics Data System (ADS)

Powell, James Eckhardt

Emissions inventories are an important tool, often built by governments, and used to manage emissions. To build an inventory of urban CO2 emissions and other fossil fuel combustion products in the urban atmosphere, an inventory of on-road traffic is required. In particular, a high resolution inventory is necessary to capture the local characteristics of transport emissions. These emissions vary widely due to the local nature of the fleet, fuel, and roads. Here we show a new model of ADT for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 7,767 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway traffic count data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. An EPA-supplied emissions factor was used to estimate transportation CO2 emissions, which is compared to several other estimates for the city's CO2 footprint.

Betweenness centrality and its applications from modeling traffic flows to network community detection

NASA Astrophysics Data System (ADS)

Ren, Yihui

As real-world complex networks are heterogeneous structures, not all their components such as nodes, edges and subgraphs carry the same role or importance in the functions performed by the networks: some elements are more critical than others. Understanding the roles of the components of a network is crucial for understanding the behavior of the network as a whole. One the most basic function of networks is transport; transport of vehicles/people, information, materials, forces, etc., and these quantities are transported along edges between source and destination nodes. For this reason, network path-based importance measures, also called centralities, play a crucial role in the understanding of the transport functions of the network and the network's structural and dynamical behavior in general. In this thesis we study the notion of betweenness centrality, which measures the fraction of lowest-cost (or shortest) paths running through a network component, in particular through a node or an edge. High betweenness centrality nodes/edges are those that will be frequently used by the entities transported through the network and thus they play a key role in the overall transport properties of the network. In the first part of the thesis we present a first-principles based method for traffic prediction using a cost-based generalization of the radiation model (emission/absorbtion model) for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. We then focus on studying the extent of changes in traffic flows in the wake of a localized damage or alteration to the network and we demonstrate that the changes can propagate globally, affecting traffic several hundreds of miles away. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events. In the second part of the thesis we focus on network deconstruction and community detection problems, both intensely studied topics in network science, using a weighted betweenness centrality approach. We present an algorithm that solves both problems efficiently and accurately and demonstrate that on both benchmark networks and data networks.

Network structure of subway passenger flows

NASA Astrophysics Data System (ADS)

Xu, Q.; Mao, B. H.; Bai, Y.

2016-03-01

The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.

Traffic pollution and countermeasures of urban traffic environment

NASA Astrophysics Data System (ADS)

He, Yuhong; Zheng, Chaocheng

2018-01-01

Background: Traffic environment has become a serious social problem in China currently, therefore, urban traffic environment governance is the requirement to solve this issue because as an important place in people's social life, urban traffic environment shows a strong city's energy. Objective: Based on analysis on social function of city traffic environment and its influence of traffic on urban environment in this paper, the goal to establish a healthy urban traffic environment must be included under the aim of sustainable development eternally and feasible measures were put forward afterwards. Method, result, conclusion and possible applications.

Area coverage provided by vehicle to vehicle communication in an urban network.

DOT National Transportation Integrated Search

2014-08-01

The information obtained from connected vehicle has the potential of providing local and area-wide traffic : management solutions by improving safety and mobility. The reliability and the frequency of this transmitted : information have to be address...

Real-time estimation of incident delay in dynamic and stochastic networks

DOT National Transportation Integrated Search

1997-01-01

The ability to predict the link travel times is a necessary requirement for most intelligent transportation systems (ITS) applications such as route guidance systems. In an urban traffic environment, these travel times are dynamic and stochastic and ...

Towards smart mobility in urban spaces: Bus tracking and information application

NASA Astrophysics Data System (ADS)

Yue, Wong Seng; Chye, Koh Keng; Hoy, Cheong Wan

2017-10-01

Smart city can be defined as an urban space with complete and advanced infrastructure, intelligent networks and platforms, with millions of sensors among which people themselves and their mobile devices. Urban mobility is one of the global smart city project which offers traffic management in real-time, management of passenger transport means, tracking applications and logistics, car sharing services, car park management and more smart mobility services. Due to the frustrated waiting time for the arrival of buses and the difficulty of accessing shuttle bus-related information in a one-stop centre, bus tracking and information application (BTA) is one the proposed solutions to solve the traffic problems in urban spaces. This paper is aimed to design and develop a bus tracking and information application in a selected city in Selangor state, Malaysia. Next, this application also provides an alternative to design public transport tracking and information application for the urban places in Malaysia. Furthermore, the application also provides a smart solution for the management of public infrastructures and urban facilities in Malaysia in future.

Resilience and efficiency in transportation networks

PubMed Central

Ganin, Alexander A.; Kitsak, Maksim; Marchese, Dayton; Keisler, Jeffrey M.; Seager, Thomas; Linkov, Igor

2017-01-01

Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions. PMID:29291243

Evaluation of an urban traffic Noise-Exposed population based on points of interest and noise maps: The case of Guangzhou.

PubMed

Wang, Haibo; Chen, Hanjie; Cai, Ming

2018-08-01

The primary objective of this study was to develop an evaluation method for assessing an urban traffic noise-exposed population and apply it in the main urban area of Guangzhou. The method based on points of interest (POIs) and noise map is realized in several steps. First, after regionalizing based on road networks and executing a cluster analysis for regions according to the properties of POIs, the environmental noise functional regions (NFRs) of the urban area are presented. Then, surrounding POIs are used to infer the type of buildings, and according to the attraction of different building types and the whole population of the region, the population distribution at the building level is calculated. Finally, with the help of a noise map, an evaluation method for assessing an urban traffic noise-exposed population is proposed. The method is applied in the main urban area of Guangzhou, and the results reveal the followings. 1) At daytime and nighttime, 23.63% and 30.53% of the population, respectively, experience noise levels that exceed the noise standards. The per capita noise exposure value at daytime and nighttime is 0.9 dB and 2.0 dB, respectively. 2) The percentages of the exposed population of Yuexiu District were 28.89% at daytime and 35.65% at nighttime, which are the largest, followed by the exposed population percentages of Liwan, Haizhu, and Tianhe Districts. 3) From the view of different classes of NFRs, the percentages of the exposed population of Class 1 and Class 4 are larger than the percentages of the exposed population from the other classes, especially at nighttime (48.24% of Class 1 and 40.79% of Class 4). 4) Although there are masses of people affected by traffic noise, a large percentage of them (85%) experience not more than 5 dB of traffic noise superscale. Copyright © 2018 Elsevier Ltd. All rights reserved.

Algorithms for constructing optimal paths and statistical analysis of passenger traffic

NASA Astrophysics Data System (ADS)

Trofimov, S. P.; Druzhinina, N. G.; Trofimova, O. G.

2018-01-01

Several existing information systems of urban passenger transport (UPT) are considered. Author’s UPT network model is presented. To a passenger a new service is offered that is the best path from one stop to another stop at a specified time. The algorithm and software implementation for finding the optimal path are presented. The algorithm uses the current UPT schedule. The article also describes the algorithm of statistical analysis of trip payments by the electronic E-cards. The algorithm allows obtaining the density of passenger traffic during the day. This density is independent of the network topology and UPT schedules. The resulting density of the traffic flow can solve a number of practical problems. In particular, the forecast for the overflow of passenger transport in the «rush» hours, the quantitative comparison of different topologies transport networks, constructing of the best UPT timetable. The efficiency of the proposed integrated approach is demonstrated by the example of the model town with arbitrary dimensions.

The impact of iterated games on traffic flow at noncontrolled intersections

NASA Astrophysics Data System (ADS)

Zhao, Chao; Jia, Ning

2015-05-01

Intersections without signal control widely exist in urban road networks. This paper studied the traffic flow in a noncontrolled intersection within an iterated game framework. We assume drivers have learning ability and can repetitively adjust their strategies (to give way or to rush through) in the intersection according to memories. A cellular automata model is applied to investigate the characteristics of the traffic flow. Numerical experiments indicate two main findings. First, the traffic flow experiences a "volcano-shaped" fundamental diagram with three different phases. Second, most drivers choose to give way in the intersection, but the aggressive drivers cannot be completely eliminated, which is coincident with field observations. Analysis are also given out to explain the observed phenomena. These findings allow deeper insight of the real-world bottleneck traffic flow.

Characterisation of an urban bus network for environmental purposes.

PubMed

André, Michel; Villanova, André

2004-12-01

Since pollutant emissions are closely related to the operating conditions of vehicles, their evaluation usually involves studying these operating conditions (through bus instrumentation and monitoring under actual operation), the design of representative driving or engine test cycles and the measurement of pollutant emissions. A preliminary characterisation of the routes on a bus network should make it possible to identify typical routes, the driving conditions and pollutant emissions of which are then studied. Two approaches are envisaged and applied to the Paris area, for which a wealth of information is available, which should be transferable to other bus networks. Both approaches are based on factorial analysis and automatic clustering, to allow optimum description and the identification of a pertinent typology of the bus routes in several classes. The first attempt at characterisation is based on statistics relating to bus operations: route characteristics (length, dedicated bus lanes, number of stops, location of stops: schools, tourist sites, hospitals, railways or underground stations), travel time, commercial speed, annual statistics (number of passengers, number of vehicles per hour, total kilometres), the irregularity of travel (variation of travel times, injuries, congestion.), as well as information on the problems encountered (congestion, distribution of the passenger load, junctions, bends). A second approach is based on the analysis of the "urban context" in which buses are driven. Population, employment, housing, road network, traffic and places that generate or disturb traffic (schools, railway stations, shopping areas, etc.) are calculated for the Ile de France region, by cells of 100 x 100 m, and collected in a geographical information system (GIS). Statistical analyses enable a typology of these urban cells to be established, the main parameters being density, type of housing, road types and traffic levels. The bus routes are then analysed according to their itineraries across these typical areas (distances travelled in each type of area) using a similar approach. A comparison of the typologies obtained from operational data and from urban data highlights the advantages and disadvantages of the two approaches. The first result from these typologies is the selection of routes which are representative of the different classes, in order to instrument buses and record driving patterns. This method should also make it possible to link driving conditions and urban characteristics, and then to allocate pollutant emission factors to given geographical situations, in particular, in the context of emission inventories or impact studies.

The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology

NASA Astrophysics Data System (ADS)

Yang, Wang-Dong; Wang, Tao

On these issues unified representation of urban transport information using urban transport ontology, it defines the statute and the algebraic operations of semantic fusion in ontology level in order to achieve the fusion of urban traffic information in the semantic completeness and consistency. Thus this paper takes advantage of the semantic completeness of the ontology to build urban traffic ontology model with which we resolve the problems as ontology mergence and equivalence verification in semantic fusion of traffic information integration. Information integration in urban transport can increase the function of semantic fusion, and reduce the amount of data integration of urban traffic information as well enhance the efficiency and integrity of traffic information query for the help, through the practical application of intelligent traffic information integration platform of Changde city, the paper has practically proved that the semantic fusion based on ontology increases the effect and efficiency of the urban traffic information integration, reduces the storage quantity, and improve query efficiency and information completeness.

A state of the art regarding urban air quality prediction models

NASA Astrophysics Data System (ADS)

Croitoru, Cristiana; Nastase, Ilinca

2018-02-01

Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

Effects of urban sprawl and vehicle miles traveled on traffic fatalities.

PubMed

Yeo, Jiho; Park, Sungjin; Jang, Kitae

2015-01-01

Previous research suggests that urban sprawl increases auto-dependency and that excessive auto use increases the risk of traffic fatalities. This indirect effect of urban sprawl on traffic fatalities is compared to non-vehicle miles traveled (VMT)-related direct effect of sprawl on fatalities. We conducted a path analysis to examine the causal linkages among urban sprawl, VMT, traffic fatalities, income, and fuel cost. The path diagram includes 2 major linkages: the direct relationship between urban sprawl and traffic fatalities and the indirect effect on fatalities through increased VMT in sprawling urban areas. To measure the relative strength of these causal linkages, path coefficients are estimated using data collected nationally from 147 urbanized areas in the United States. Through both direct and indirect paths, urban sprawl is associated with greater numbers of traffic fatalities, but the direct effect of sprawl on fatalities is more influential than the indirect effect. Enhancing traffic safety can be achieved by impeding urban sprawl and encouraging compact development. On the other hand, policy tools reducing VMT may be less effective than anticipated for traffic safety.

Complexity analysis on public transport networks of 97 large- and medium-sized cities in China

NASA Astrophysics Data System (ADS)

Tian, Zhanwei; Zhang, Zhuo; Wang, Hongfei; Ma, Li

2018-04-01

The traffic situation in Chinese urban areas is continuing to deteriorate. To make a better planning and designing of the public transport system, it is necessary to make profound research on the structure of urban public transport networks (PTNs). We investigate 97 large- and medium-sized cities’ PTNs in China, construct three types of network models — bus stop network, bus transit network and bus line network, then analyze the structural characteristics of them. It is revealed that bus stop network is small-world and scale-free, bus transit network and bus line network are both small-world. Betweenness centrality of each city’s PTN shows similar distribution pattern, although these networks’ size is various. When classifying cities according to the characteristics of PTNs or economic development level, the results are similar. It means that the development of cities’ economy and transport network has a strong correlation, PTN expands in a certain model with the development of economy.

A case study predicting environmental impacts of urban transport planning in China.

PubMed

Chen, Chong; Shao, Li-guo; Xu, Ling; Shang, Jin-cheng

2009-10-01

Predicting environmental impacts is essential when performing an environmental assessment on urban transport planning. System dynamics (SD) is usually used to solve complex nonlinear problems. In this study, we utilized system dynamics (SD) to evaluate the environmental impacts associated with urban transport planning in Jilin City, China with respect to the local economy, society, transport, the environment and resources. To accomplish this, we generated simulation models comprising interrelated subsystems designed to utilize changes in the economy, society, road construction, changes in the number of vehicles, the capacity of the road network capacity, nitrogen oxides emission, traffic noise, land used for road construction and fuel consumption associated with traffic to estimate dynamic trends in the environmental impacts associated with Jilin's transport planning. Two simulation scenarios were then analyzed comparatively. The results of this study indicated that implementation of Jilin transport planning would improve the current urban traffic conditions and boost the local economy and development while benefiting the environment in Jilin City. In addition, comparative analysis of the two scenarios provided additional information that can be used to aid in scientific decision-making regarding which aspects of the transport planning to implement in Jilin City. This study demonstrates that our application of the SD method, which is referred to as the Strategic Environmental Assessment (SEA), is feasible for use in urban transport planning.

Definition of perspective scheme of organization of traffic using methods of forecasting and modeling

NASA Astrophysics Data System (ADS)

Vlasov, V. M.; Novikov, A. N.; Novikov, I. A.; Shevtsova, A. G.

2018-03-01

In the environment of highly developed urban agglomerations, one of the main problems arises - inability of the road network to reach a high level of motorization. The introduction of intelligent transport systems allows solving this problem, but the main issue in their implementation remains open: to what extent this or that method of improving the transport network will be effective and whether it is able to solve the problem of vehicle growth especially for the long-term period. The main goal of this work was the development of an approach to forecasting the increase in the intensity of traffic flow for a long-term period using the population and the level of motorization. The developed approach made it possible to determine the projected population and, taking into account the level of motorization, to determine the growth factor of the traffic flow intensity, which allows calculating the intensity value for a long-term period with high accuracy. The analysis of the main methods for predicting the characteristics of the transport stream is performed. The basic values and parameters necessary for their use are established. The analysis of the urban settlement is carried out and the level of motorization characteristic for the given locality is determined. A new approach to predicting the intensity of the traffic flow has been developed, which makes it possible to predict the change in the transport situation in the long term in high accuracy. Calculations of the magnitude of the intensity increase on the basis of the developed forecasting method are made and the errors in the data obtained are determined. The main recommendations on the use of the developed forecasting approach for the long-term functioning of the road network are formulated.

Acoustic, Visual and Spatial Indicators for the Description of the Soundscape of Waterfront Areas with and without Road Traffic Flow.

PubMed

Puyana Romero, Virginia; Maffei, Luigi; Brambilla, Giovanni; Ciaburro, Giuseppe

2016-09-21

High flows of road traffic noise in urban agglomerations can negatively affect the livability of squares and parks located at the neighborhood, district and city levels, therefore pushing anyone who wants to enjoy calmer, quieter areas to move to non-urban parks. Due to the distances between these areas, it is not possible to go as regularly as would be necessary to satisfy any needs. Even if cities are densely populated, the presence of a sea or riverfront offers the possibility of large restorative places, or at least with potential features for being the natural core of an urban nucleus after a renewal intervention. This study evaluates the soundscape of the Naples waterfront, presenting an overview of the most significant visual, acoustic and spatial factors related to the pedestrian areas, as well as areas open to road traffic and others where the road traffic is limited. The factors were chosen with feature selection methods and artificial neural networks. The results show how certain factors, such as the perimeter between the water and promenade, the visibility of the sea or the density of green areas, can affect the perception of the soundscape quality in the areas with road traffic. In the pedestrian areas, acoustic factors, such as loudness or the A-weighted sound level exceeded for 10% of the measurement duration (LA10), influence the perceived quality of the soundscape.

Acoustic, Visual and Spatial Indicators for the Description of the Soundscape of Waterfront Areas with and without Road Traffic Flow

PubMed Central

Puyana Romero, Virginia; Maffei, Luigi; Brambilla, Giovanni; Ciaburro, Giuseppe

2016-01-01

High flows of road traffic noise in urban agglomerations can negatively affect the livability of squares and parks located at the neighborhood, district and city levels, therefore pushing anyone who wants to enjoy calmer, quieter areas to move to non-urban parks. Due to the distances between these areas, it is not possible to go as regularly as would be necessary to satisfy any needs. Even if cities are densely populated, the presence of a sea or riverfront offers the possibility of large restorative places, or at least with potential features for being the natural core of an urban nucleus after a renewal intervention. This study evaluates the soundscape of the Naples waterfront, presenting an overview of the most significant visual, acoustic and spatial factors related to the pedestrian areas, as well as areas open to road traffic and others where the road traffic is limited. The factors were chosen with feature selection methods and artificial neural networks. The results show how certain factors, such as the perimeter between the water and promenade, the visibility of the sea or the density of green areas, can affect the perception of the soundscape quality in the areas with road traffic. In the pedestrian areas, acoustic factors, such as loudness or the A-weighted sound level exceeded for 10% of the measurement duration (LA10), influence the perceived quality of the soundscape. PMID:27657105

An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

PubMed Central

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate. PMID:25793221

An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

PubMed

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

Mining spatiotemporal patterns of urban dwellers from taxi trajectory data

NASA Astrophysics Data System (ADS)

Mao, Feng; Ji, Minhe; Liu, Ting

2016-06-01

With the widespread adoption of locationaware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps: spatial clustering of taxi origin-destination (OD) based on urban traffic grids to discover potentially meaningful places, identifying threshold values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.

Personal Rapid Transit (PRT) : an Efficient and Long-Term Sustainable Traffic System. Analysis of a Demonstration Network in Stockholm

DOT National Transportation Integrated Search

1999-05-01

On behalf of the Office of Regional Planning and Urban Transportation at the Stockholm County Council and with financial funding from KFB, Transek Consultants was commissioned to analyze conditions, market and economic viability of a Personal Rapid t...

Does the livability of a residential street depend on the characteristics of the neighboring street network? : research brief.

DOT National Transportation Integrated Search

2016-07-01

The character of the nearby arterial road influences residential : livability across a number of livability measures. When : controlling for income, high levels of traffic and low levels of : urban design on the arterial both detract from the livabil...

Toolbox for Urban Mobility Simulation: High Resolution Population Dynamics for Global Cities

NASA Astrophysics Data System (ADS)

Bhaduri, B. L.; Lu, W.; Liu, C.; Thakur, G.; Karthik, R.

2015-12-01

In this rapidly urbanizing world, unprecedented rate of population growth is not only mirrored by increasing demand for energy, food, water, and other natural resources, but has detrimental impacts on environmental and human security. Transportation simulations are frequently used for mobility assessment in urban planning, traffic operation, and emergency management. Previous research, involving purely analytical techniques to simulations capturing behavior, has investigated questions and scenarios regarding the relationships among energy, emissions, air quality, and transportation. Primary limitations of past attempts have been availability of input data, useful "energy and behavior focused" models, validation data, and adequate computational capability that allows adequate understanding of the interdependencies of our transportation system. With increasing availability and quality of traditional and crowdsourced data, we have utilized the OpenStreetMap roads network, and has integrated high resolution population data with traffic simulation to create a Toolbox for Urban Mobility Simulations (TUMS) at global scale. TUMS consists of three major components: data processing, traffic simulation models, and Internet-based visualizations. It integrates OpenStreetMap, LandScanTM population, and other open data (Census Transportation Planning Products, National household Travel Survey, etc.) to generate both normal traffic operation and emergency evacuation scenarios. TUMS integrates TRANSIMS and MITSIM as traffic simulation engines, which are open-source and widely-accepted for scalable traffic simulations. Consistent data and simulation platform allows quick adaption to various geographic areas that has been demonstrated for multiple cities across the world. We are combining the strengths of geospatial data sciences, high performance simulations, transportation planning, and emissions, vehicle and energy technology development to design and develop a simulation framework to assist decision makers at all levels - local, state, regional, and federal. Using Cleveland, Tennessee as an example, in this presentation, we illustrate how emerging cities could easily assess future land use scenario driven impacts on energy and environment utilizing such a capability.

Urban planning and traffic safety at night

NASA Astrophysics Data System (ADS)

Ispas, N.; Trusca, D.

2016-08-01

Urban planning including traffic signs serve vital functions, providing road users with regulatory, warning and guidance information about the roadway and surrounding environment. There are a large number of signs and even more guidelines on how these signs should be designed, installed, and maintained in concordance with on road surface traffic signs. More requirements for signs are made for night urban traffic, including appearance (size, shape, colour), placement (height, lateral, and longitudinal), maintenance (visibility, position, damage) and signs light and retroreflective. In the night, traffic signs visibility can interact by on pedestrian visibility and diminish urban traffic safety. The main aim of this paper are the scientific determination of an urban specific zone visibility for evaluate at night real conditions in case of a traffic accident in the Braşov city area. The night visibility study was made using PC-Rect version 4.2. Other goal of the paper was to modify some urban planning solution in order to increase the urban safety in Brașov.

A Study on Urban Road Traffic Safety Based on Matter Element Analysis

PubMed Central

Hu, Qizhou; Zhou, Zhuping; Sun, Xu

2014-01-01

This paper examines a new evaluation of urban road traffic safety based on a matter element analysis, avoiding the difficulties found in other traffic safety evaluations. The issue of urban road traffic safety has been investigated through the matter element analysis theory. The chief aim of the present work is to investigate the features of urban road traffic safety. Emphasis was placed on the construction of a criterion function by which traffic safety achieved a hierarchical system of objectives to be evaluated. The matter element analysis theory was used to create the comprehensive appraisal model of urban road traffic safety. The technique was used to employ a newly developed and versatile matter element analysis algorithm. The matter element matrix solves the uncertainty and incompatibility of the evaluated factors used to assess urban road traffic safety. The application results showed the superiority of the evaluation model and a didactic example was included to illustrate the computational procedure. PMID:25587267

An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm

PubMed Central

Lu, Guangquan; Xiong, Ying; Wang, Yunpeng

2016-01-01

The schedule of urban road network recovery caused by rainstorms, snow, and other bad weather conditions, traffic incidents, and other daily events is essential. However, limited studies have been conducted to investigate this problem. We fill this research gap by proposing an optimal schedule for urban road network repair with limited repair resources based on the greedy algorithm. Critical links will be given priority in repair according to the basic concept of the greedy algorithm. In this study, the link whose restoration produces the ratio of the system-wide travel time of the current network to the worst network is the minimum. We define such a link as the critical link for the current network. We will re-evaluate the importance of damaged links after each repair process is completed. That is, the critical link ranking will be changed along with the repair process because of the interaction among links. We repair the most critical link for the specific network state based on the greedy algorithm to obtain the optimal schedule. The algorithm can still quickly obtain an optimal schedule even if the scale of the road network is large because the greedy algorithm can reduce computational complexity. We prove that the problem can obtain the optimal solution using the greedy algorithm in theory. The algorithm is also demonstrated in the Sioux Falls network. The problem discussed in this paper is highly significant in dealing with urban road network restoration. PMID:27768732

Outlier Detection in Urban Air Quality Sensor Networks.

PubMed

van Zoest, V M; Stein, A; Hoek, G

2018-01-01

Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly applied outlier detection methods are unsuitable for air pollutant measurements that have large spatial and temporal variations as occur in urban areas. We present a novel outlier detection method based upon a spatio-temporal classification, focusing on hourly NO 2 concentrations. We divide a full year's observations into 16 spatio-temporal classes, reflecting urban background vs. urban traffic stations, weekdays vs. weekends, and four periods per day. For each spatio-temporal class, we detect outliers using the mean and standard deviation of the normal distribution underlying the truncated normal distribution of the NO 2 observations. Applying this method to a low-cost air quality sensor network in the city of Eindhoven, the Netherlands, we found 0.1-0.5% of outliers. Outliers could reflect measurement errors or unusual high air pollution events. Additional evaluation using expert knowledge is needed to decide on treatment of the identified outliers. We conclude that our method is able to detect outliers while maintaining the spatio-temporal variability of air pollutant concentrations in urban areas.

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City.

PubMed

Zhou, Lianjie; Chen, Nengcheng; Yuan, Sai; Chen, Zeqiang

2016-10-29

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems.

A statistical downscaling approach for roadside NO2 concentrations: Application to a WRF-Chem study for Berlin

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Lauer, Axel; von Schneidemesser, Erika; Butler, Tim

2017-04-01

Many European cities continue to struggle with meeting the European air quality limits for NO2. In Berlin, Germany, most of the exceedances in NO2 recorded at monitoring sites near busy roads can be largely attributed to emissions from traffic. In order to assess the impact of changes in traffic emissions on air quality at policy relevant scales, we combine the regional atmosphere-chemistry transport model WRF-Chem at a resolution of 1kmx1km with a statistical downscaling approach. Here, we build on the recently published study evaluating the performance of a WRF-Chem setup in representing observed urban background NO2 concentrations from Kuik et al. (2016) and extend this setup by developing and testing an approach to statistically downscale simulated urban background NO2 concentrations to street level. The approach uses a multilinear regression model to relate roadside NO2 concentrations observed with the municipal monitoring network with observed NO2 concentrations at urban background sites and observed traffic counts. For this, the urban background NO2 concentrations are decomposed into a long term, a synoptic and a diurnal component using the Kolmogorov-Zurbenko filtering method. We estimate the coefficients of the regression model for five different roadside stations in Berlin representing different street types. In a next step we combine the coefficients with simulated urban background concentrations and observed traffic counts, in order to estimate roadside NO2 concentrations based on the results obtained with WRF-Chem at the five selected stations. In a third step, we extrapolate the NO2 concentrations to all major roads in Berlin. The latter is based on available data for Berlin of daily mean traffic counts, diurnal and weekly cycles of traffic as well as simulated urban background NO2 concentrations. We evaluate the NO2 concentrations estimated with this method at street level for Berlin with additional observational data from stationary measurements and mobile measurements conducted during a campaign in summer 2014. The results show that this approach allows us to estimate NO2 concentrations at roadside reasonably well. The approach can be applied when observations show a strong correlation between roadside NO2 concentrations and traffic emissions from a single type of road. The method, however, shows weaknesses for intersections where observed NO2 concentrations are influenced by traffic on several different roads. We then apply this downscaling approach to estimate the impact of different traffic emission scenarios both on urban background and street level NO2 concentrations. References Kuik, F., Lauer, A., Churkina, G., Denier van der Gon, H. A. C., Fenner, D., Mar, K. A., and Butler, T. M.: Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data, Geosci. Model Dev., 9, 4339-4363, doi:10.5194/gmd-9-4339-2016, 2016.

Assessing the air quality impact of nitrogen oxides and benzene from road traffic and domestic heating and the associated cancer risk in an urban area of Verona (Italy)

NASA Astrophysics Data System (ADS)

Schiavon, Marco; Redivo, Martina; Antonacci, Gianluca; Rada, Elena Cristina; Ragazzi, Marco; Zardi, Dino; Giovannini, Lorenzo

2015-11-01

Simulations of emission and dispersion of nitrogen oxides (NOx) are performed in an urban area of Verona (Italy), characterized by street canyons and typical sources of urban pollutants. Two dominant source categories are considered: road traffic and, as an element of novelty, domestic heaters. Also, to assess the impact of urban air pollution on human health and, in particular, the cancer risk, simulations of emission and dispersion of benzene are carried out. Emissions from road traffic are estimated by the COPERT 4 algorithm, whilst NOx emission factors from domestic heaters are retrieved by means of criteria provided in the technical literature. Then maps of the annual mean concentrations of NOx and benzene are calculated using the AUSTAL2000 dispersion model, considering both scenarios representing the current situation, and scenarios simulating the introduction of environmental strategies for air pollution mitigation. The simulations highlight potentially critical situations of human exposure that may not be detected by the conventional network of air quality monitoring stations. The proposed methodology provides a support for air quality policies, such as planning targeted measurement campaigns, re-locating monitoring stations and adopting measures in favour of better air quality in urban planning. In particular, the estimation of the induced cancer risk is an important starting point to conduct zoning analyses and to detect the areas where population is more directly exposed to potential risks for health.

Walkability for Different Urban Granularities

NASA Astrophysics Data System (ADS)

Hollenstein, D.; Bleisch, S.

2016-06-01

The positive effects of low-intensity physical activity are widely acknowledged and in this context walking is often promoted as an active form of transport. Under the concept of walkability the role of the built environment in encouraging walking is investigated. For that purpose, walkability is quantified area-wise by measuring a varying set of built environment attributes. In purely GIS-based approaches to studying walkability, indices are generally built using existing and easily accessible data. These include street network design, population density, land use mix, and access to destinations. Access to destinations is usually estimated using either a fixed radius, or distances in the street network. In this paper, two approaches to approximate a footpath network are presented. The two footpath networks were built making different assumptions regarding the walkability of different street types with respect to more or less restrictive safety preferences. Information on sidewalk presence, pedestrian crossings, and traffic restrictions were used to build both networks. The first network comprises car traffic free areas only. The second network includes streets with low speed limits that have no sidewalks. Both networks are compared to the more commonly used street network in an access-to-distance analysis. The results suggest that for the generally highly walkable study area, access to destination mostly depends on destination density within the defined walkable distance. However, on single street segments access to destinations is diminished when only car traffic free spaces are assumed to be walkable.

Spatial Analysis of Urban Form and Pedestrian Exposure to Traffic Noise

PubMed Central

Sheng, Ni; Tang, U. Wa

2011-01-01

In the Macao Peninsula, the high population density (49,763 inhabitants/km2) and the lack of control over the number of vehicles (460 vehicles/km) have led to an increase in urban pollution. To provide useful information to local government and urban planners, this paper investigates the spatial distribution of traffic noise in the Macao Peninsula. The interactions among urban form, traffic flow and traffic noise are addressed. Considering the spatial nature of urban geometry and traffic, a high-resolution GIS-based traffic noise model system is applied. Results indicate that the Macao Peninsula has fallen into a situation of serious traffic noise pollution. About 60% of traffic noise levels along the major pedestrian sidewalks in the evening peak hour exceed the National Standard of 70 dB(A) in China. In particular, about 21% of traffic noise levels along the pedestrian sidewalks are above the National Standard by 5 dB(A). Noticeably, the high pedestrian exposure to traffic noise in the historical urban area reduces the comfort of tourists walking in the historic centre and is ruining the reputation of the area as a World Cultural Heritage site. PMID:21776213

Spatial analysis of urban form and pedestrian exposure to traffic noise.

PubMed

Sheng, Ni; Tang, U Wa

2011-06-01

In the Macao Peninsula, the high population density (49,763 inhabitants/km2) and the lack of control over the number of vehicles (460 vehicles/km) have led to an increase in urban pollution. To provide useful information to local government and urban planners, this paper investigates the spatial distribution of traffic noise in the Macao Peninsula. The interactions among urban form, traffic flow and traffic noise are addressed. Considering the spatial nature of urban geometry and traffic, a high-resolution GIS-based traffic noise model system is applied. Results indicate that the Macao Peninsula has fallen into a situation of serious traffic noise pollution. About 60% of traffic noise levels along the major pedestrian sidewalks in the evening peak hour exceed the National Standard of 70 dB(A) in China. In particular, about 21% of traffic noise levels along the pedestrian sidewalks are above the National Standard by 5 dB(A). Noticeably, the high pedestrian exposure to traffic noise in the historical urban area reduces the comfort of tourists walking in the historic centre and is ruining the reputation of the area as a World Cultural Heritage site.

Strategies for prevention of road traffic injuries (RTIs) in Pakistan: situational analysis.

PubMed

Khan, Adeel Ahmed; Fatmi, Zafar

2014-05-01

Road traffic injuries (RTIs) are one of the leading causes of death among productive age group. Using systems approach framework (SAF), current preventive strategies for RTI control were reviewed in Pakistan. A review of the literature was done using four international search engines. Only ten studies on preventive strategies for RTI stemming from Pakistan were found. The first Road Traffic Injuries Research Network (RTIRN) surveillance system for road traffic injuries was established in urban city (Karachi) in Pakistan has shown promise for injury control and should be scaled up to other cities. Enforcement of traffic laws on seat-belt and helmet wearing is poor. National Highway and Motorway Police Ordinance (2000) was one of the few legislative measure so far taken in Pakistan. Using SAF, efforts are required to implement interventions targeting human, vehicle design and also making environment safer for road users.

An Experimental Study of the Noise Due to Traffic in a Congested Urban Area

NASA Astrophysics Data System (ADS)

Sangeetha, M.; Sankar, P.

2016-03-01

Noise pollution in an urban environment is an issue of serious concern in the major cities of India. There are various factors that contribute to the increase of noise levels in urban areas. The intensity of traffic is one of the factors which contributes to a drastic increase in environmental noise. The management of noise pollution has to be considered in the decision making process. In this paper, an attempt is made to study the existing noise level due to the traffic in Velachery which is declared as a sensitive area by the Ministry of Environment and Forestry (MoEF). The noise level data is collected using the MS6710 digital sound meter. The Custic simulation software version 3.2 is used for finding the propagation of noise. The spatial patterns of measurement were also calculated, in the sub-urban area of Velachery, Chennai, Tamilnadu, India. A means of transmitting this data to vehicles moving in the area, through a wireless medium is simulated using NCTUns 6.0 (network simulator), to enable drivers to understand the environmental conditions. A hardware was also designed which can be used to transmit and receive the noise data using the Zigbee module. A noise transmitting station is placed at a junction, so that it can transmit this noise data to the receivers which are fitted inside the vehicles.

Social Media Meets Big Urban Data: A Case Study of Urban Waterlogging Analysis.

PubMed

Zhang, Ningyu; Chen, Huajun; Chen, Jiaoyan; Chen, Xi

2016-01-01

With the design and development of smart cities, opportunities as well as challenges arise at the moment. For this purpose, lots of data need to be obtained. Nevertheless, circumstances vary in different cities due to the variant infrastructures and populations, which leads to the data sparsity. In this paper, we propose a transfer learning method for urban waterlogging disaster analysis, which provides the basis for traffic management agencies to generate proactive traffic operation strategies in order to alleviate congestion. Existing work on urban waterlogging mostly relies on past and current conditions, as well as sensors and cameras, while there may not be a sufficient number of sensors to cover the relevant areas of a city. To this end, it would be helpful if we could transfer waterlogging. We examine whether it is possible to use the copious amounts of information from social media and satellite data to improve urban waterlogging analysis. Moreover, we analyze the correlation between severity, road networks, terrain, and precipitation. Moreover, we use a multiview discriminant transfer learning method to transfer knowledge to small cities. Experimental results involving cities in China and India show that our proposed framework is effective.

Social Media Meets Big Urban Data: A Case Study of Urban Waterlogging Analysis

PubMed Central

Chen, Huajun; Chen, Jiaoyan

2016-01-01

With the design and development of smart cities, opportunities as well as challenges arise at the moment. For this purpose, lots of data need to be obtained. Nevertheless, circumstances vary in different cities due to the variant infrastructures and populations, which leads to the data sparsity. In this paper, we propose a transfer learning method for urban waterlogging disaster analysis, which provides the basis for traffic management agencies to generate proactive traffic operation strategies in order to alleviate congestion. Existing work on urban waterlogging mostly relies on past and current conditions, as well as sensors and cameras, while there may not be a sufficient number of sensors to cover the relevant areas of a city. To this end, it would be helpful if we could transfer waterlogging. We examine whether it is possible to use the copious amounts of information from social media and satellite data to improve urban waterlogging analysis. Moreover, we analyze the correlation between severity, road networks, terrain, and precipitation. Moreover, we use a multiview discriminant transfer learning method to transfer knowledge to small cities. Experimental results involving cities in China and India show that our proposed framework is effective. PMID:27774098

Leveraging Scarce Resources: A Case Study where Community Service Did the Work

ERIC Educational Resources Information Center

Tarawneh, Tarek M.; Tarawneh, Mohammed S.; Majali, Sawsan A.

2004-01-01

The University of Jordan is the first national university established in Jordan. Although first established in a suburban and secluded area of the capital Amman, the continuous urban development in its vicinity has led to excessive delays and traffic congestion on its surrounding street network. As a result, the University's administration…

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network

PubMed Central

Pamučar, Dragan; Vasin, Ljubislav; Atanasković, Predrag; Miličić, Milica

2016-01-01

The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone. PMID:27195005

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

PubMed

Pamučar, Dragan; Vasin, Ljubislav; Atanasković, Predrag; Miličić, Milica

2016-01-01

The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone.

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

PubMed

Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

2015-01-01

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection

PubMed Central

Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

2015-01-01

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

Optimization design of urban expressway ramp control

NASA Astrophysics Data System (ADS)

Xu, Hongke; Li, Peiqi; Zheng, Jinnan; Sun, Xiuzhen; Lin, Shan

2017-05-01

In this paper, various types of expressway systems are analyzed, and a variety of signal combinations are proposed to mitigate traffic congestion. And various signal combinations are used to verify the effectiveness of the multi-signal combinatorial control strategy. The simulation software VISSIM was used to simulate the system. Based on the network model of 25 kinds of road length combinations and the simulation results, an optimization scheme suitable for the practical road model is summarized. The simulation results show that the controller can reduce the travel time by 25% under the large traffic flow and improve the road capacity by about 20%.

Effects of canyon geometry on the distribution of traffic-related air pollution in a large urban area: Implications of a multi-canyon air pollution dispersion model

NASA Astrophysics Data System (ADS)

Fu, Xiangwen; Liu, Junfeng; Ban-Weiss, George A.; Zhang, Jiachen; Huang, Xin; Ouyang, Bin; Popoola, Olalekan; Tao, Shu

2017-09-01

Street canyons are ubiquitous in urban areas. Traffic-related air pollutants in street canyons can adversely affect human health. In this study, an urban-scale traffic pollution dispersion model is developed considering street distribution, canyon geometry, background meteorology, traffic assignment, traffic emissions and air pollutant dispersion. In the model, vehicle exhausts generated from traffic flows first disperse inside street canyons along the micro-scale wind field generated by computational fluid dynamics (CFD) model. Then, pollutants leave the street canyon and further disperse over the urban area. On the basis of this model, the effects of canyon geometry on the distribution of NOx and CO from traffic emissions were studied over the center of Beijing. We found that an increase in building height leads to heavier pollution inside canyons and lower pollution outside canyons at pedestrian level, resulting in higher domain-averaged concentrations over the area. In addition, canyons with highly even or highly uneven building heights on each side of the street tend to lower the urban-scale air pollution concentrations at pedestrian level. Further, increasing street widths tends to lead to lower pollutant concentrations by reducing emissions and enhancing ventilation simultaneously. Our results indicate that canyon geometry strongly influences human exposure to traffic pollutants in the populated urban area. Carefully planning street layout and canyon geometry while considering traffic demand as well as local weather patterns may significantly reduce inhalation of unhealthy air by urban residents.

A Numerical Simulation of Traffic-Related Air Pollution Exposures in Urban Street Canyons

NASA Astrophysics Data System (ADS)

Liu, J.; Fu, X.; Tao, S.

2016-12-01

Urban street canyons are usually associated with intensive vehicle emissions. However, the high buildings successively along both sides of a street block the dispersion of traffic-generated air pollutants, which enhances human exposure and adversely affects human health. In this study, an urban scale traffic pollution dispersion model is developed with the consideration of street distribution, canyon geometry, background meteorology, traffic assignment, traffic emissions and air pollutant dispersion. Vehicle exhausts generated from traffic flows will first disperse inside a street canyon along the micro-scale wind field (generated by computational fluid dynamics (CFD) model) and then leave the street canyon and further disperse over the urban area. On the basis of this model, the effects of canyon geometry on the distribution of NOx and CO from traffic emissions were studied over the center of Beijing, China. We found that an increase of building height along the streets leads to higher pollution levels inside streets and lower pollution levels outside, resulting in higher domain-averaged concentrations over the area. In addition, street canyons with equal (or highly uneven) building heights on two sides of a street tend to lower the urban-scale air pollution concentrations at pedestrian level. Our results indicate that canyon geometry strongly influences human exposure to traffic pollutants in the populated urban area. Carefully planning street layout and canyon geometry in consideration of traffic demand as well as local weather pattern may significantly reduce the chances of unhealthy air being inhaled by urban residents.

Vulnerability Analysis and Evaluation of Urban Road System in Tianjin

NASA Astrophysics Data System (ADS)

Liu, Y. Q.; Wu, X.

In recent years, with the development of economy, the road construction of our country has entered into a period of rapid growth. The road transportation network has been expanding and the risk of disasters is increasing. In this paper we study the vulnerability of urban road system in Tianjin. After analyzed many risk factors of the urban road system security, including road construction, road traffic and the natural environment, we proposed an evaluation index of vulnerability of urban road system and established the corresponding evaluation index system. Based on the results of analysis and comprehensive evaluation, appropriate improvement measures and suggestions which may reduce the vulnerability of the road system and improve the safety and reliability of the road system are proposed.

Green Infrastructure Concept for JABODETABEKJUR Metropolitan Area

NASA Astrophysics Data System (ADS)

Tanuwidjaja, Gunawan; Gates Chang, Bill

2017-07-01

Sixty “Mega Cities” would emerge by 2015 catering of 600 million populations, and were threatened by the climate change, because of cyclones, flooding, etc. Jakarta became a metro region covering Jakarta, Bogor, Tangerang, Bekasi, Depok and Cianjur. Jakarta metropolitan faced the very high population growth, urban sprawling, traffic jams, flooding, green open space reduction, environmental degradation, urban slums and illegal street hawkers. Flooding and traffic congestions were the two most important issues to solve. SWOT analysis and urban design solutions were produced to create a sustainable solution. Related to transportation issues, Singapore Mass Rapid Transport (MRT) concept was evaluated. Meanwhile the Netherlands’ polder concept as well as Singapore’s Integrated Water Management were also analyzed. The development of above ground MRT as well as Busway could be developed to connect Jakarta Metropolitan Region. The networks were developed on the main toll road networks. The MRT and Busway would eventually replace the need of automobile use in the future. The Transit - Oriented - Development (TOD) with high density can be suggested to be concentrated nearby the MRT and Busway interchange stations. The Netherlands’ polder and were adopted for urban’ low-lying lands in Jakarta Metropolitan Region, A polder system was defined as the Integrated Man-made Drainage System consisting Dikes, Drains, Retention Ponds, Outfall Structures or Pumping Stations. The polder system was proposed to be extended to Tangerang and Bekasi area.

Real-time network traffic classification technique for wireless local area networks based on compressed sensing

NASA Astrophysics Data System (ADS)

Balouchestani, Mohammadreza

2017-05-01

Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

Assessment of the service performance of drainage system and transformation of pipeline network based on urban combined sewer system model.

PubMed

Peng, Hai-Qin; Liu, Yan; Wang, Hong-Wu; Ma, Lu-Ming

2015-10-01

In recent years, due to global climate change and rapid urbanization, extreme weather events occur to the city at an increasing frequency. Waterlogging is common because of heavy rains. In this case, the urban drainage system can no longer meet the original design requirements, resulting in traffic jams and even paralysis and post a threat to urban safety. Therefore, it provides a necessary foundation for urban drainage planning and design to accurately assess the capacity of the drainage system and correctly simulate the transport effect of drainage network and the carrying capacity of drainage facilities. This study adopts InfoWorks Integrated Catchment Management (ICM) to present the two combined sewer drainage systems in Yangpu District, Shanghai (China). The model can assist the design of the drainage system. Model calibration is performed based on the historical rainfall events. The calibrated model is used for the assessment of the outlet drainage and pipe loads for the storm scenario currently existing or possibly occurring in the future. The study found that the simulation and analysis results of the drainage system model were reliable. They could fully reflect the service performance of the drainage system in the study area and provide decision-making support for regional flood control and transformation of pipeline network.

Predictability of Road Traffic and Congestion in Urban Areas

PubMed Central

Wang, Jingyuan; Mao, Yu; Li, Jing; Xiong, Zhang; Wang, Wen-Xu

2015-01-01

Mitigating traffic congestion on urban roads, with paramount importance in urban development and reduction of energy consumption and air pollution, depends on our ability to foresee road usage and traffic conditions pertaining to the collective behavior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device installed in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measuring its entropy, we find a relatively high daily predictability of traffic conditions despite the absence of any priori knowledge of drivers' origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive dependence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of recovering the traffic condition of an inaccessible segment from its adjacent segments with respect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers' behaviors and the variability of their origins and destinations enables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion. PMID:25849534

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auld, Joshua; Hope, Michael; Ley, Hubert

This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typicallymore » done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.« less

Factor Analysis of Traffic Safety in Urban Roads Based on FTA-LEC

NASA Astrophysics Data System (ADS)

Shuicheng, TIAN; Xingbo, YANG; Xiaoqing, SHEN; Detao, ZHANG

2018-05-01

In order to reduce the number and the loss of urban road traffic accidents in our country, improve the safety of road traffic, a statistical analysis of the research report on major road traffic accidents in 2016 was conducted. The risk factors affecting urban road traffic in China were analyzed by using FTA to find the basic hidden events. Secondly, the risk value of the identified hidden danger events were calculated and classified into four levels I, II, III and IV through the LEC evaluation method. Finally, the graded results of risk factors are verified through a case of specific accidents in Beijing. The results show that: the case verified the scientificalness and effectiveness of hazard classification and provided guidance for urban road traffic management.

Understanding Road Usage Patterns in Urban Areas

NASA Astrophysics Data System (ADS)

Wang, Pu; Hunter, Timothy; Bayen, Alexandre M.; Schechtner, Katja; González, Marta C.

2012-12-01

In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a network of road usage by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.

Research on Urban Road Traffic Congestion Charging Based on Sustainable Development

NASA Astrophysics Data System (ADS)

Ye, Sun

Traffic congestion is a major problem which bothers our urban traffic sustainable development at present. Congestion charging is an effective measure to alleviate urban traffic congestion. The paper first probes into several key issues such as the goal, the pricing, the scope, the method and the redistribution of congestion charging from theoretical angle. Then it introduces congestion charging practice in Singapore and London and draws conclusion and suggestion that traffic congestion charging should take scientific plan, support of public, public transportation development as the premise.

An Efficient Method of Sharing Mass Spatio-Temporal Trajectory Data Based on Cloudera Impala for Traffic Distribution Mapping in an Urban City

PubMed Central

Zhou, Lianjie; Chen, Nengcheng; Yuan, Sai; Chen, Zeqiang

2016-01-01

The efficient sharing of spatio-temporal trajectory data is important to understand traffic congestion in mass data. However, the data volumes of bus networks in urban cities are growing rapidly, reaching daily volumes of one hundred million datapoints. Accessing and retrieving mass spatio-temporal trajectory data in any field is hard and inefficient due to limited computational capabilities and incomplete data organization mechanisms. Therefore, we propose an optimized and efficient spatio-temporal trajectory data retrieval method based on the Cloudera Impala query engine, called ESTRI, to enhance the efficiency of mass data sharing. As an excellent query tool for mass data, Impala can be applied for mass spatio-temporal trajectory data sharing. In ESTRI we extend the spatio-temporal trajectory data retrieval function of Impala and design a suitable data partitioning method. In our experiments, the Taiyuan BeiDou (BD) bus network is selected, containing 2300 buses with BD positioning sensors, producing 20 million records every day, resulting in two difficulties as described in the Introduction section. In addition, ESTRI and MongoDB are applied in experiments. The experiments show that ESTRI achieves the most efficient data retrieval compared to retrieval using MongoDB for data volumes of fifty million, one hundred million, one hundred and fifty million, and two hundred million. The performance of ESTRI is approximately seven times higher than that of MongoDB. The experiments show that ESTRI is an effective method for retrieving mass spatio-temporal trajectory data. Finally, bus distribution mapping in Taiyuan city is achieved, describing the buses density in different regions at different times throughout the day, which can be applied in future studies of transport, such as traffic scheduling, traffic planning and traffic behavior management in intelligent public transportation systems. PMID:27801869

Rural-urban disparity in knowledge and compliance with traffic signs among young commercial motorcyclists in selected local government areas in Oyo State, Nigeria.

PubMed

Olumide, Adesola O; Owoaje, Eme T

2017-06-01

This study compared knowledge and compliance with traffic signs among young commercial motorcyclists in rural and urban communities in Oyo state, Nigeria. Information on knowledge and compliance with 10 common traffic signs was obtained from 149 rural and 113 urban commercial motorcyclists aged 18-35 years. Aggregate knowledge scores were computed and categorized as good (≥5) and poor (<5) knowledge. Overall, 98.7% rural versus 61.1% urban motorcyclists had poor knowledge of traffic signs (p < 0.05). After controlling for age, level of education and years of commercial riding, motorcyclists in the rural areas were more likely to have poor knowledge of the traffic signs (OR = 58.15; 95% CI = 11.96-282.79). A higher proportion of rural than urban motorcyclists never obeyed any of the traffic signs. Young rural commercial motorcyclists' knowledge and compliance with the road signs was poorer than their urban counterparts. Interventions to improve the rural motorcyclists' knowledge and ultimately compliance with road signs are urgently required.

Applicability of models to estimate traffic noise for urban roads.

PubMed

Melo, Ricardo A; Pimentel, Roberto L; Lacerda, Diego M; Silva, Wekisley M

2015-01-01

Traffic noise is a highly relevant environmental impact in cities. Models to estimate traffic noise, in turn, can be useful tools to guide mitigation measures. In this paper, the applicability of models to estimate noise levels produced by a continuous flow of vehicles on urban roads is investigated. The aim is to identify which models are more appropriate to estimate traffic noise in urban areas since several models available were conceived to estimate noise from highway traffic. First, measurements of traffic noise, vehicle count and speed were carried out in five arterial urban roads of a brazilian city. Together with geometric measurements of width of lanes and distance from noise meter to lanes, these data were input in several models to estimate traffic noise. The predicted noise levels were then compared to the respective measured counterparts for each road investigated. In addition, a chart showing mean differences in noise between estimations and measurements is presented, to evaluate the overall performance of the models. Measured Leq values varied from 69 to 79 dB(A) for traffic flows varying from 1618 to 5220 vehicles/h. Mean noise level differences between estimations and measurements for all urban roads investigated ranged from -3.5 to 5.5 dB(A). According to the results, deficiencies of some models are discussed while other models are identified as applicable to noise estimations on urban roads in a condition of continuous flow. Key issues to apply such models to urban roads are highlighted.

The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

PubMed

Dėdelė, Audrius; Miškinytė, Auksė

2015-09-01

In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

Study of the air quality in the surroundings of an urban park: A micrometeorological approach

NASA Astrophysics Data System (ADS)

Sastre, Mariano; Yagüe, Carlos; Arrillaga, Jon A.; Román-Cascón, Carlos; Maqueda, Gregorio; Artíñano, Begoña; Díaz-Ramiro, Elías; Gómez-Moreno, Francisco J.; Barreiro, Marcos; Borge, Rafael; Narros, Adolfo; Pérez, Javier; Quaassdorff, Christina

2017-04-01

In this work we study the differences showed by two types of pollutants, particulate matter (PM) and NOx, by comparing ambient concentration measurements within an urban park versus the corresponding values nearby (but outside) it. The results are linked to both proximity to emission sources, such as road traffic, and the microscale atmospheric conditions. The work is motivated by the fact that poor air quality is a crucial issue of current cities. For some of them it is not uncommon to face this problem with occasional traffic restrictions when high concentrations of pollutants are reached. These events occur more frequently with specific large-scale atmospheric conditions, for example when a strong anticyclone is present. As the meteorological conditions may significantly influence the pollutants concentrations, the research project TECNAIRE-CM (Innovative technologies for the assessment and improvement of urban air quality) aims to provide new approaches to obtain proper descriptions of the urban pollution and its dynamics at different spatial and temporal scales, not only the synoptic scale. So far, a few field campaigns have been developed within TECNAIRE-CM at two locations in the city of Madrid, which are considered hot spots according to the air quality network records. Here we use the data from a field campaign carried out during summer 2016, which consider standard pollution and meteorological measurements, as well as sonic anemometer data. The latter help to include atmospheric turbulence as a significant agent for air quality characterization. The instrumentation was deployed at a location with considerable traffic density, but nearby a border of the main urban park of the city, so that its influence might be investigated. Supplementary data considered for this work correspond to permanent instrumentation within the park. With this extra information we can compare both measurements inside and outside the park. Therefore, we study the effect on wind, turbulence or air quality when we measure at a site either directly exposed to traffic emissions or partly protected and with a reduced influence of typical atmospheric urban phenomena. This work has been funded by Madrid Regional Research Plan through TECNAIRE (P2013/MAE-2972).

Motor transport related harmful PM2.5 and PM10: from onroad measurements to the modelling of air pollution by neural network approach on street and urban level

NASA Astrophysics Data System (ADS)

Lozhkina, O.; Lozhkin, V.; Nevmerzhitsky, N.; Tarkhov, D.; Vasilyev, A.

2016-11-01

The level of PM10 and PM2.5 concentrations in the air on seven roads in St. Petersburg, Russia, were investigated using gravimetry and nephelometry measurement techniques in 2013-2015. The effects of meteorological conditions (temperature, relative humidity, wind direction, and speed) and the intensity of traffic flows on the results of the measurements were also evaluated. On the base of the measurements, there was developed a neural network modelling approach that allowed to quantify exhaust / non-exhaust PM10 and PM 2.5 emissions and carry out numerical investigations of air pollution by transport related PM2.5 and PM10 on street and urban level in St. Petersburg.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

Mortality from road traffic accidents in a rapidly urbanizing Chinese city: A 20-year analysis in Shenzhen, 1994-2013.

PubMed

Xie, Shao-Hua; Wu, Yong-Sheng; Liu, Xiao-Jian; Fu, Ying-Bin; Li, Shan-Shan; Ma, Han-Wu; Zou, Fei; Cheng, Jin-Quan

2016-01-01

This study aimed to describe the trends of motorization and mortality rates from road traffic accidents and examine their associations in a rapidly urbanizing city in China, Shenzhen. Using data from the Shenzhen Deaths Registry between 1994 and 2013, we calculated the annual mortality rates of road traffic accidents, in addition to the age- and sex-specific mortality rates and their annual percentage changes (APCs) for the period of 2000-2013. We also examined the associations between mortality rate of road traffic accidents and traffic growth with Spearman's rank correlation analysis and a log-linear model derived from Smeed's law. A total of 20,196 deaths due to road traffic accidents, including 14,391 (71.3%) male deaths and 5,805 (28.7%) female deaths, were recorded in Shenzhen from 1994 to 2013. The annual mortality rates in terms of deaths per population and deaths per vehicle changed in similar patterns, demonstrating an increase since 1994 and peaking in 1997, followed by a steady decrease thereafter. The decrease in mortality was faster in individuals aged 20 year or older compared to those younger than 20 years. The mortality rates in term of deaths per population were positively correlated with the total number of vehicles per kilometer of road but negatively correlated with the motorization rate in term of vehicles per population. The estimated model for deaths due to road traffic accidents in relation to the total population and the number of registered vehicles was ln (deaths/10,000 vehicles) = -1.902 × ln (vehicles/population) - 1.961. The coefficient was statistically significant (P < .001) and the coefficient of determination was 0.966, indicating a good model fit. We described a generally decreasing trend in the mortality rates of road traffic accidents in a rapidly urbanizing Chinese city based observations in the 20-year period from 1994 to 2013. The decreased mortality rate may be explained by the expansion of road network construction, improved road safety regulations and management, as well as more accessible ambulance services in recent years. Nevertheless, road traffic accidents remain a universal problem of great public health concern in the whole population.

Comparing emission rates derived from a model with a plume-based approach and quantifying the contribution of vehicle classes to on-road emissions and air quality.

PubMed

Xu, Junshi; Wang, Jonathan; Hilker, Nathan; Fallah-Shorshani, Masoud; Saleh, Marc; Tu, Ran; Wang, An; Minet, Laura; Stogios, Christos; Evans, Greg; Hatzopoulou, Marianne

2018-06-05

This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to carbon monoxide (CO), nitrogen oxides (NO x ), and elemental carbon (EC) along an urban corridor. To this end, a field campaign was conducted over one week in June 2016 on an arterial road in Toronto, Canada. Traffic data were collected using a traffic camera and a radar, while air quality was characterized using two monitoring stations: one located at ground-level and another at the rooftop of a four-storey building. A traffic simulation model was calibrated and validated and sec-by-sec speed profiles for all vehicle trajectories were extracted to model emissions. In addition, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. Our results indicate that modelled EFs for CO and NO x are twice as high as plume-based EFs. Besides, modelled results indicate that transit bus emissions accounted for 60% and 70% of the total emissions of NO x and EC. Transit bus emission rates in g/passenger.km for NO x and EC were up to 8 and 22 times the emission rates of passenger cars. In contrast, the Toronto streetcars, which are electrically fuelled, were found to improve near-road air quality despite their negative impact on traffic speeds. Finally, we observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background given that the study network is located in a busy downtown area. Implications This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to various pollutants. Besides, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. We observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background as the study network is located in a busy downtown area.

Containing air pollution and traffic congestion: Transport policy and the environment in Singapore

NASA Astrophysics Data System (ADS)

Chin, Anthony T. H.

Land transportation remains one of the main contributors of noise and air pollution in urban areas. This is in addition to traffic congestion and accidents which result in the loss of productive activity. While there is a close relationship between traffic volumes and levels of noise and air pollution, transport authorities often assume that solving traffic congestion would reduce noise and air pollutant levels. Tight control over automobile ownership and use in Singapore has contributed in improving traffic flows, travel speeds and air quality. The adoption of internationally accepted standards on automobile emissions and gasoline have been effective in reducing air pollution from motor vehicles. Demand management measures have largely focused on controlling the source of traffic congestion, i.e. private automobile ownership and its use especially within the Central Business District during the day. This paper reviews and analyzes the effectiveness of two measures which are instrumental in controlling congestion and automobile ownership, i.e. road pricing and the vehicle quota scheme (VQS). While these measures have been successful in achieving desired objectives, it has also led to the spreading of traffic externalities to other roads in the network, loss in consumer welfare and rent seeking by automobile traders.

Assessing rear-end crash potential in urban locations based on vehicle-by-vehicle interactions, geometric characteristics and operational conditions.

PubMed

Dimitriou, Loukas; Stylianou, Katerina; Abdel-Aty, Mohamed A

2018-03-01

Rear-end crashes are one of the most frequently occurring crash types, especially in urban networks. An understanding of the contributing factors and their significant association with rear-end crashes is of practical importance and will help in the development of effective countermeasures. The objective of this study is to assess rear-end crash potential at a microscopic level in an urban environment, by investigating vehicle-by-vehicle interactions. To do so, several traffic parameters at the individual vehicle level have been taken into consideration, for capturing car-following characteristics and vehicle interactions, and to investigate their effect on potential rear-end crashes. In this study rear-end crash potential was estimated based on stopping distance between two consecutive vehicles, and four rear-end crash potential cases were developed. The results indicated that 66.4% of the observations were estimated as rear-end crash potentials. It was also shown that rear-end crash potential was presented when traffic flow and speed standard deviation were higher. Also, locational characteristics such as lane of travel and location in the network were found to affect drivers' car following decisions and additionally, it was shown that speeds were lower and headways higher when Heavy Goods Vehicles lead. Finally, a model-based behavioral analysis based on Multinomial Logit regression was conducted to systematically identify the statistically significant variables in explaining rear-end risk potential. The modeling results highlighted the significance of the explanatory variables associated with rear-end crash potential, however it was shown that their effect varied among different model configurations. The outcome of the results can be of significant value for several purposes, such as real-time monitoring of risk potential, allocating enforcement units in urban networks and designing targeted proactive safety policies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Traffic management teams : a description and action plan for Virginia.

DOT National Transportation Integrated Search

1988-01-01

A traffic management team improves the overall traffic operations in an urban area, especially along urban corridors, through the communication, coordination, and cooperation of the transportation-related operational agencies in the area. Since vario...

Long-term observations of tropospheric particle number size distributions and equivalent black carbon mass concentrations in the German Ultrafine Aerosol Network (GUAN)

NASA Astrophysics Data System (ADS)

Birmili, W.; Weinhold, K.; Merkel, M.; Rasch, F.; Sonntag, A.; Wiedensohler, A.; Bastian, S.; Schladitz, A.; Löschau, G.; Cyrys, J.; Pitz, M.; Gu, J.; Kusch, T.; Flentje, H.; Quass, U.; Kaminski, H.; Kuhlbusch, T. A. J.; Meinhardt, F.; Schwerin, A.; Bath, O.; Ries, L.; Wirtz, K.; Fiebig, M.

2015-11-01

The German Ultrafine Aerosol Network (GUAN) is a cooperative atmospheric observation network, which aims at improving the scientific understanding of aerosol-related effects in the troposphere. The network addresses research questions dedicated to both, climate and health related effects. GUAN's core activity has been the continuous collection of tropospheric particle number size distributions and black carbon mass concentrations at seventeen observation sites in Germany. These sites cover various environmental settings including urban traffic, urban background, rural background, and Alpine mountains. In association with partner projects, GUAN has implemented a high degree of harmonisation of instrumentation, operating procedures, and data evaluation procedures. The quality of the measurement data is assured by laboratory intercomparisons as well as on-site comparisons with reference instruments. This paper describes the measurement sites, instrumentation, quality assurance and data evaluation procedures in the network as well as the EBAS repository, where the data sets can be obtained (doi:10.5072/guan).

Long-term observations of tropospheric particle number size distributions and equivalent black carbon mass concentrations in the German Ultrafine Aerosol Network (GUAN)

NASA Astrophysics Data System (ADS)

Birmili, Wolfram; Weinhold, Kay; Rasch, Fabian; Sonntag, André; Sun, Jia; Merkel, Maik; Wiedensohler, Alfred; Bastian, Susanne; Schladitz, Alexander; Löschau, Gunter; Cyrys, Josef; Pitz, Mike; Gu, Jianwei; Kusch, Thomas; Flentje, Harald; Quass, Ulrich; Kaminski, Heinz; Kuhlbusch, Thomas A. J.; Meinhardt, Frank; Schwerin, Andreas; Bath, Olaf; Ries, Ludwig; Gerwig, Holger; Wirtz, Klaus; Fiebig, Markus

2016-08-01

The German Ultrafine Aerosol Network (GUAN) is a cooperative atmospheric observation network, which aims at improving the scientific understanding of aerosol-related effects in the troposphere. The network addresses research questions dedicated to both climate- and health-related effects. GUAN's core activity has been the continuous collection of tropospheric particle number size distributions and black carbon mass concentrations at 17 observation sites in Germany. These sites cover various environmental settings including urban traffic, urban background, rural background, and Alpine mountains. In association with partner projects, GUAN has implemented a high degree of harmonisation of instrumentation, operating procedures, and data evaluation procedures. The quality of the measurement data is assured by laboratory intercomparisons as well as on-site comparisons with reference instruments. This paper describes the measurement sites, instrumentation, quality assurance, and data evaluation procedures in the network as well as the EBAS repository, where the data sets can be obtained (doi:10.5072/guan).

Is Traffic Still an Important Emitter of Monoaromatic Organic Compounds in European Urban Areas?

PubMed

Borbon, Agnès; Boynard, Anne; Salameh, Thérèse; Baudic, Alexia; Gros, Valérie; Gauduin, Julie; Perrussel, Olivier; Pallares, Cyril

2018-01-16

Trends of long-term observations and emission inventories suggest that traffic emissions will no longer dominate the concentrations of monoaromatic compounds (i.e., TEX - toluene, xylenes, and ethylbenzene) in European urban areas. But the split limit between traffic and other emission sector contributions such as solvent use remains tenuous. Here long-term observations of an extensive set of hydrocarbons, including TEX, at traffic and urban background sites in London, Paris and Strasbourg were combined to estimate the relative importance of traffic emissions on TEX in every city. When analyzing the urban enhancement emission ratios of TEX-to-benzene on a seasonal basis, two potential source signatures other than traffic could be differentiated in all cities (1) summertime evaporation from fuel and/or solvent and (2) wintertime domestic heating. However, traffic emissions still unambiguously dominate the concentration levels of TEX in every city despite the reduction of their emissions at exhaust pipe over the last two decades. Traffic explains between 60% and 96% (at ±20%) of TEX levels while it is less clear for xylenes at some locations. Our results provide a basis to evaluate regional emission inventories. The method is applicable at any urban area where speciated hydrocarbon monitoring is available.

Traffic Surveillance Data Processing in Urban Freeway Corridors Using Kalman Filter Techniques

DOT National Transportation Integrated Search

1978-11-01

Real-time surveillance of traffic conditions on urban freeway corridors using spatially discrete presence detectors is addressed. Using a finite-dimensional (macroscopic) fluid-analog model for freeway vehicular traffic flow, an extended Kalman filte...

Effective Vehicle-Based Kangaroo Detection for Collision Warning Systems Using Region-Based Convolutional Networks.

PubMed

Saleh, Khaled; Hossny, Mohammed; Nahavandi, Saeid

2018-06-12

Traffic collisions between kangaroos and motorists are on the rise on Australian roads. According to a recent report, it was estimated that there were more than 20,000 kangaroo vehicle collisions that occurred only during the year 2015 in Australia. In this work, we are proposing a vehicle-based framework for kangaroo detection in urban and highway traffic environment that could be used for collision warning systems. Our proposed framework is based on region-based convolutional neural networks (RCNN). Given the scarcity of labeled data of kangaroos in traffic environments, we utilized our state-of-the-art data generation pipeline to generate 17,000 synthetic depth images of traffic scenes with kangaroo instances annotated in them. We trained our proposed RCNN-based framework on a subset of the generated synthetic depth images dataset. The proposed framework achieved a higher average precision (AP) score of 92% over all the testing synthetic depth image datasets. We compared our proposed framework against other baseline approaches and we outperformed it with more than 37% in AP score over all the testing datasets. Additionally, we evaluated the generalization performance of the proposed framework on real live data and we achieved a resilient detection accuracy without any further fine-tuning of our proposed RCNN-based framework.

TrajGraph: A Graph-Based Visual Analytics Approach to Studying Urban Network Centralities Using Taxi Trajectory Data.

PubMed

Huang, Xiaoke; Zhao, Ye; Yang, Jing; Zhang, Chong; Ma, Chao; Ye, Xinyue

2016-01-01

We propose TrajGraph, a new visual analytics method, for studying urban mobility patterns by integrating graph modeling and visual analysis with taxi trajectory data. A special graph is created to store and manifest real traffic information recorded by taxi trajectories over city streets. It conveys urban transportation dynamics which can be discovered by applying graph analysis algorithms. To support interactive, multiscale visual analytics, a graph partitioning algorithm is applied to create region-level graphs which have smaller size than the original street-level graph. Graph centralities, including Pagerank and betweenness, are computed to characterize the time-varying importance of different urban regions. The centralities are visualized by three coordinated views including a node-link graph view, a map view and a temporal information view. Users can interactively examine the importance of streets to discover and assess city traffic patterns. We have implemented a fully working prototype of this approach and evaluated it using massive taxi trajectories of Shenzhen, China. TrajGraph's capability in revealing the importance of city streets was evaluated by comparing the calculated centralities with the subjective evaluations from a group of drivers in Shenzhen. Feedback from a domain expert was collected. The effectiveness of the visual interface was evaluated through a formal user study. We also present several examples and a case study to demonstrate the usefulness of TrajGraph in urban transportation analysis.

A regression-based method for mapping traffic-related air pollution: application and testing in four contrasting urban environments.

PubMed

Briggs, D J; de Hoogh, C; Gulliver, J; Wills, J; Elliott, P; Kingham, S; Smallbone, K

2000-05-15

Accurate, high-resolution maps of traffic-related air pollution are needed both as a basis for assessing exposures as part of epidemiological studies, and to inform urban air-quality policy and traffic management. This paper assesses the use of a GIS-based, regression mapping technique to model spatial patterns of traffic-related air pollution. The model--developed using data from 80 passive sampler sites in Huddersfield, as part of the SAVIAH (Small Area Variations in Air Quality and Health) project--uses data on traffic flows and land cover in the 300-m buffer zone around each site, and altitude of the site, as predictors of NO2 concentrations. It was tested here by application in four urban areas in the UK: Huddersfield (for the year following that used for initial model development), Sheffield, Northampton, and part of London. In each case, a GIS was built in ArcInfo, integrating relevant data on road traffic, urban land use and topography. Monitoring of NO2 was undertaken using replicate passive samplers (in London, data were obtained from surveys carried out as part of the London network). In Huddersfield, Sheffield and Northampton, the model was first calibrated by comparing modelled results with monitored NO2 concentrations at 10 randomly selected sites; the calibrated model was then validated against data from a further 10-28 sites. In London, where data for only 11 sites were available, validation was not undertaken. Results showed that the model performed well in all cases. After local calibration, the model gave estimates of mean annual NO2 concentrations within a factor of 1.5 of the actual mean (approx. 70-90%) of the time and within a factor of 2 between 70 and 100% of the time. r2 values between modelled and observed concentrations are in the range of 0.58-0.76. These results are comparable to those achieved by more sophisticated dispersion models. The model also has several advantages over dispersion modelling. It is able, for example, to provide high-resolution maps across a whole urban area without the need to interpolate between receptor points. It also offers substantially reduced costs and processing times compared to formal dispersion modelling. It is concluded that the model might thus be used as a means of mapping long-term air pollution concentrations either in support of local authority air-quality management strategies, or in epidemiological studies.

[Policies for the promotion of sustainable mobility and the reduction of traffic-related air pollution in the cities participating in the EpiAir2 project].

PubMed

Di Lonardo, Sara; Nuvolone, Daniela; Forastiere, Francesco; Cadum, Ennio; Barchielli, Alessandro

2013-01-01

to describe transport policies adopted in recent years (2006-2010) by some Italian municipalities and their effectiveness. survey data refer to fifteen cities participating in the EpiAir2 project: Torino, Milano, Venezia, Bologna, Firenze, Pisa, Roma, Taranto, Palermo, Cagliari, Trieste, Genova, Ancona, Napoli, and Bari. this survey revealed strengths and weaknesses of the way in which these Italian cities address the promotion of sustainable mobility. As a general rule, the vehicle fleets have been renewed with a reduction of old-emission-standard vehicles. Italian cities reported a considerable delay in the development of underground and tram systems, and suburban rail networks, compared to other European urban areas. Regarding other aspects of urban mobility (supply/demand for public transport, low traffic and pedestrian zones, bike paths, car and bike sharing), this survey highlighted a great heterogeneity among Italian cities. differences between Italian cities are partly explained by structural and cultural features and also by local governance, specifically the political capability to design and adopt effective policies concerning urban transportation systems and their environmental impact. Various and fragmented initiatives are signs that Italy has not formulated a comprehensive and integrated strategy about sustainable mobility in urban areas yet.

Psychoacoustical evaluation of natural and urban sounds in soundscapes.

PubMed

Yang, Ming; Kang, Jian

2013-07-01

Among various sounds in the environment, natural sounds, such as water sounds and birdsongs, have proven to be highly preferred by humans, but the reasons for these preferences have not been thoroughly researched. This paper explores differences between various natural and urban environmental sounds from the viewpoint of objective measures, especially psychoacoustical parameters. The sound samples used in this study include the recordings of single sound source categories of water, wind, birdsongs, and urban sounds including street music, mechanical sounds, and traffic noise. The samples are analyzed with a number of existing psychoacoustical parameter algorithmic models. Based on hierarchical cluster and principal components analyses of the calculated results, a series of differences has been shown among different sound types in terms of key psychoacoustical parameters. While different sound categories cannot be identified using any single acoustical and psychoacoustical parameter, identification can be made with a group of parameters, as analyzed with artificial neural networks and discriminant functions in this paper. For artificial neural networks, correlations between network predictions and targets using the average and standard deviation data of psychoacoustical parameters as inputs are above 0.95 for the three natural sound categories and above 0.90 for the urban sound category. For sound identification/classification, key parameters are fluctuation strength, loudness, and sharpness.

Urban Growth Modeling Using AN Artificial Neural Network a Case Study of Sanandaj City, Iran

NASA Astrophysics Data System (ADS)

Mohammady, S.; Delavar, M. R.; Pahlavani, P.

2014-10-01

Land use activity is a major issue and challenge for town and country planners. Modelling and managing urban growth is a complex problem. Cities are now recognized as complex, non-linear and dynamic process systems. The design of a system that can handle these complexities is a challenging prospect. Local governments that implement urban growth models need to estimate the amount of urban land required in the future given anticipated growth of housing, business, recreation and other urban uses within the boundary. There are so many negative implications related with the type of inappropriate urban development such as increased traffic and demand for mobility, reduced landscape attractively, land use fragmentation, loss of biodiversity and alterations of the hydrological cycle. The aim of this study is to use the Artificial Neural Network (ANN) to make a powerful tool for simulating urban growth patterns. Our study area is Sanandaj city located in the west of Iran. Landsat imageries acquired at 2000 and 2006 are used. Dataset were used include distance to principle roads, distance to residential areas, elevation, slope, distance to green spaces and distance to region centers. In this study an appropriate methodology for urban growth modelling using satellite remotely sensed data is presented and evaluated. Percent Correct Match (PCM) and Figure of Merit were used to evaluate ANN results.

Use of a handheld low-cost sensor to explore the effect of urban design features on local-scale spatial and temporal air quality variability.

PubMed

Miskell, Georgia; Salmond, Jennifer A; Williams, David E

2018-04-01

Portable low-cost instruments have been validated and used to measure ambient nitrogen dioxide (NO 2 ) at multiple sites over a small urban area with 20min time resolution. We use these results combined with land use regression (LUR) and rank correlation methods to explore the effects of traffic, urban design features, and local meteorology and atmosphere chemistry on small-scale spatio-temporal variations. We measured NO 2 at 45 sites around the downtown area of Vancouver, BC, in spring 2016, and constructed four different models: i) a model based on averaging concentrations observed at each site over the whole measurement period, and separate temporal models for ii) morning, iii) midday, and iv) afternoon. Redesign of the temporal models using the average model predictors as constants gave three 'hybrid' models that used both spatial and temporal variables. These accounted for approximately 50% of the total variation with mean absolute error±5ppb. Ranking sites by concentration and by change in concentration across the day showed a shift of high NO 2 concentrations across the central city from morning to afternoon. Locations could be identified in which NO 2 concentration was determined by the geography of the site, and others as ones in which the concentration changed markedly from morning to afternoon indicating the importance of temporal controls. Rank correlation results complemented LUR in identifying significant urban design variables that impacted NO 2 concentration. High variability across a relatively small space was partially described by predictor variables related to traffic (bus stop density, speed limits, traffic counts, distance to traffic lights), atmospheric chemistry (ozone, dew point), and environment (land use, trees). A high-density network recording continuously would be needed fully to capture local variations. Copyright © 2017 Elsevier B.V. All rights reserved.

Surveying traffic congestion based on the concept of community structure of complex networks

NASA Astrophysics Data System (ADS)

Ma, Lili; Zhang, Zhanli; Li, Meng

2016-07-01

In this paper, taking the traffic of Beijing city as an instance, we study city traffic states, especially traffic congestion, based on the concept of network community structure. Concretely, using the floating car data (FCD) information of vehicles gained from the intelligent transport system (ITS) of the city, we construct a new traffic network model which is with floating cars as network nodes and time-varying. It shows that this traffic network has Gaussian degree distributions at different time points. Furthermore, compared with free traffic situations, our simulations show that the traffic network generally has more obvious community structures with larger values of network fitness for congested traffic situations, and through the GPSspg web page, we show that all of our results are consistent with the reality. Then, it indicates that network community structure should be an available way for investigating city traffic congestion problems.

Assessment of honking impact on traffic noise in urban traffic environment of Nagpur, India.

PubMed

Vijay, Ritesh; Sharma, Asheesh; Chakrabarti, Tapan; Gupta, Rajesh

2015-01-01

In context of increasing traffic noise in urban India, the objective of the research study is to assess noise due to heterogeneous traffic conditions and the impact of honking on it. Traffic volume, noise levels, honking, road geometry and vehicular speed were measured on national highway, major and minor roads in Nagpur, India. Initial study showed lack of correlation between traffic volume and equivalent noise due to some factors, later identified as honking, road geometry and vehicular speed. Further, frequency analysis of traffic noise showed that honking contributed an additional 2 to 5 dB (A) noise, which is quite significant. Vehicular speed was also found to increase traffic noise. Statistical method of analysis of variance (ANOVA) confirms that frequent honking (p < 0.01) and vehicular speed (p < 0.05) have substantial impact on traffic noise apart from traffic volume and type of road. The study suggests that honking must also be a component in traffic noise assessment and to identify and monitor "No Honking" zones in urban agglomerations.

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

NASA Astrophysics Data System (ADS)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

An economic way of reducing health, environmental, and other pressures of urban traffic: a decision analysis on trip aggregation

PubMed Central

Tuomisto, Jouni T; Tainio, Marko

2005-01-01

Background Traffic congestion is rapidly becoming the most important obstacle to urban development. In addition, traffic creates major health, environmental, and economical problems. Nonetheless, automobiles are crucial for the functions of the modern society. Most proposals for sustainable traffic solutions face major political opposition, economical consequences, or technical problems. Methods We performed a decision analysis in a poorly studied area, trip aggregation, and studied decisions from the perspective of two different stakeholders, the passenger and society. We modelled the impact and potential of composite traffic, a hypothetical large-scale demand-responsive public transport system for the Helsinki metropolitan area, where a centralised system would collect the information on all trip demands online, would merge the trips with the same origin and destination into public vehicles with eight or four seats, and then would transmit the trip instructions to the passengers' mobile phones. Results We show here that in an urban area with one million inhabitants, trip aggregation could reduce the health, environmental, and other detrimental impacts of car traffic typically by 50–70%, and if implemented could attract about half of the car passengers, and within a broad operational range would require no public subsidies. Conclusion Composite traffic provides new degrees of freedom in urban decision-making in identifying novel solutions to the problems of urban traffic. PMID:16309549

Urban street structure and traffic safety.

PubMed

Mohan, Dinesh; Bangdiwala, Shrikant I; Villaveces, Andres

2017-09-01

This paper reports the influence of road type and junction density on road traffic fatality rates in U.S. cities. The Fatality Analysis Reporting System (FARS) files were used to obtain fatality rates for all cities for the years 2005-2010. A stratified random sample of 16 U.S. cities was taken, and cities with high and low road traffic fatality rates were compared on their road layout details (TIGER maps were used). Statistical analysis was done to determine the effect of junction density and road type on road traffic fatality rates. The analysis of road network and road traffic crash fatality rates in these randomly selected U.S. cities shows that, (a) higher number of junctions per road length was significantly associated with a lower motor- vehicle crash and pedestrian mortality rates, and, (b) increased number of kilometers of roads of any kind was associated with higher fatality rates, but an additional kilometer of main arterial road was associated with a significantly higher increase in total fatalities. When compared to non-arterial roads, the higher the ratio of highways and main arterial roads, there was an association with higher fatality rates. These results have important implications for road safety professionals. They suggest that once the road and street structure is put in place, that will influence whether a city has low or high traffic fatality rates. A city with higher proportion of wider roads and large city blocks will tend to have higher traffic fatality rates, and therefore in turn require much more efforts in police enforcement and other road safety measures. Urban planners need to know that smaller block size with relatively less wide roads will result in lower traffic fatality rates and this needs to be incorporated at the planning stage. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

Congestion control strategy on complex network with privilege traffic

NASA Astrophysics Data System (ADS)

Li, Shi-Bao; He, Ya; Liu, Jian-Hang; Zhang, Zhi-Gang; Huang, Jun-Wei

The congestion control of traffic is one of the most important studies in complex networks. In the previous congestion algorithms, all the network traffic is assumed to have the same priority, and the privilege of traffic is ignored. In this paper, a privilege and common traffic congestion control routing strategy (PCR) based on the different priority of traffic is proposed, which can be devised to cope with the different traffic congestion situations. We introduce the concept of privilege traffic in traffic dynamics for the first time and construct a new traffic model which taking into account requirements with different priorities. Besides, a new factor Ui is introduced by the theoretical derivation to characterize the interaction between different traffic routing selection, furthermore, Ui is related to the network throughput. Since the joint optimization among different kinds of traffic is accomplished by PCR, the maximum value of Ui can be significantly reduced and the network performance can be improved observably. The simulation results indicate that the network throughput with PCR has a better performance than the other strategies. Moreover, the network capacity is improved by 25% at least. Additionally, the network throughput is also influenced by privilege traffic number and traffic priority.

Understanding congested travel in urban areas

PubMed Central

Çolak, Serdar; Lima, Antonio; González, Marta C.

2016-01-01

Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings. PMID:26978719

Understanding congested travel in urban areas

NASA Astrophysics Data System (ADS)

Çolak, Serdar; Lima, Antonio; González, Marta C.

2016-03-01

Rapid urbanization and increasing demand for transportation burdens urban road infrastructures. The interplay of number of vehicles and available road capacity on their routes determines the level of congestion. Although approaches to modify demand and capacity exist, the possible limits of congestion alleviation by only modifying route choices have not been systematically studied. Here we couple the road networks of five diverse cities with the travel demand profiles in the morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban traffic. We present that a dimensionless ratio of the road supply to the travel demand explains the percentage of time lost in congestion. Finally, we examine congestion relief under a centralized routing scheme with varying levels of awareness of social good and quantify the benefits to show that moderate levels are enough to achieve significant collective travel time savings.

Finding Multiple Lanes in Urban Road Networks with Vision and Lidar

DTIC Science & Technology

2009-03-24

drawbacks. First, the cost of updating and main- taining millions of kilometers of roadway is prohibitive. Second, the danger of autonomous vehicles perceiving... autonomous vehicles . We propose that a data infrastructure is useful for topological information and sparse geometry, but reject relying upon it for dense...Throughout the race, approximately 50 human- driven and autonomous vehicles were simultaneously active, thus providing realistic traffic scenarios. Our most

A large-scale measurement, analysis and modelling of electromagnetic radiation levels in the vicinity of GSM/UMTS base stations in an urban area.

PubMed

Karadağ, Teoman; Yüceer, Mehmet; Abbasov, Teymuraz

2016-01-01

The present study analyses the electric field radiating from the GSM/UMTS base stations located in central Malatya, a densely populated urban area in Turkey. The authors have conducted both instant and continuous measurements of high-frequency electromagnetic fields throughout their research by using non-ionising radiation-monitoring networks. Over 15,000 instant and 13,000,000 continuous measurements were taken throughout the process. The authors have found that the normal electric field radiation can increase ∼25% during daytime, depending on mobile communication traffic. The authors' research work has also demonstrated the fact that the electric field intensity values can be modelled for each hour, day or week with the results obtained from continuous measurements. The authors have developed an estimation model based on these values, including mobile communication traffic (Erlang) values obtained from mobile phone base stations and the temperature and humidity values in the environment. The authors believe that their proposed artificial neural network model and multivariable least-squares regression analysis will help predict the electric field intensity in an environment in advance. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Bayes classifiers for imbalanced traffic accidents datasets.

PubMed

Mujalli, Randa Oqab; López, Griselda; Garach, Laura

2016-03-01

Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009-2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessment of annoyance due to urban road traffic noise combined with tramway noise.

PubMed

Klein, A; Marquis-Favre, C; Champelovier, P

2017-01-01

Due to the expansion of urban areas, an increasing number of residents are exposed to combined community noise sources. Studies show that the exposure to transportation noise significantly affects health and well-being. Noise annoyance is one of these adverse health effects. Up to now, annoyance due to transportation noise is mostly assessed considering single noise exposure situations neglecting the effects of potential interactions between noise sources. In this study, perceptual phenomena involved in noise annoyance due to combined urban road traffic and tramway noises are assessed in laboratory conditions with imaginary and simulated contexts. The urban road traffic was composed of light vehicles, heavy vehicles, buses, and powered-two-wheelers in different driving conditions. The tramway traffic corresponded to tramways in in-curve operating configurations. It could be shown that the road traffic and tramway traffic partial annoyance responses were influenced by each other. Throughout the experiments the strongest component effect prevailed but secondary phenomena could also be observed. Considering the perceptual phenomena highlighted in the analysis, it is shown that total noise annoyance due to the combined noises can be most adequately predicted by the strongest component model. This result was obtained by calculating partial annoyance responses due to urban road and tramway traffic.

A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.

PubMed

Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing

2015-01-01

Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.

Safety modeling of urban arterials in Shanghai, China.

PubMed

Wang, Xuesong; Fan, Tianxiang; Chen, Ming; Deng, Bing; Wu, Bing; Tremont, Paul

2015-10-01

Traffic safety on urban arterials is influenced by several key variables including geometric design features, land use, traffic volume, and travel speeds. This paper is an exploratory study of the relationship of these variables to safety. It uses a comparatively new method of measuring speeds by extracting GPS data from taxis operating on Shanghai's urban network. This GPS derived speed data, hereafter called Floating Car Data (FCD) was used to calculate average speeds during peak and off-peak hours, and was acquired from samples of 15,000+ taxis traveling on 176 segments over 18 major arterials in central Shanghai. Geometric design features of these arterials and surrounding land use characteristics were obtained by field investigation, and crash data was obtained from police reports. Bayesian inference using four different models, Poisson-lognormal (PLN), PLN with Maximum Likelihood priors (PLN-ML), hierarchical PLN (HPLN), and HPLN with Maximum Likelihood priors (HPLN-ML), was used to estimate crash frequencies. Results showed the HPLN-ML models had the best goodness-of-fit and efficiency, and models with ML priors yielded estimates with the lowest standard errors. Crash frequencies increased with increases in traffic volume. Higher average speeds were associated with higher crash frequencies during peak periods, but not during off-peak periods. Several geometric design features including average segment length of arterial, number of lanes, presence of non-motorized lanes, number of access points, and commercial land use, were positively related to crash frequencies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling disease outbreaks in realistic urban social networks

NASA Astrophysics Data System (ADS)

Eubank, Stephen; Guclu, Hasan; Anil Kumar, V. S.; Marathe, Madhav V.; Srinivasan, Aravind; Toroczkai, Zoltán; Wang, Nan

2004-05-01

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

Incorporating twitter-based human activity information in spatial analysis of crashes in urban areas.

PubMed

Bao, Jie; Liu, Pan; Yu, Hao; Xu, Chengcheng

2017-09-01

The primary objective of this study was to investigate how to incorporate human activity information in spatial analysis of crashes in urban areas using Twitter check-in data. This study used the data collected from the City of Los Angeles in the United States to illustrate the procedure. The following five types of data were collected: crash data, human activity data, traditional traffic exposure variables, road network attributes and social-demographic data. A web crawler by Python was developed to collect the venue type information from the Twitter check-in data automatically. The human activities were classified into seven categories by the obtained venue types. The collected data were aggregated into 896 Traffic Analysis Zones (TAZ). Geographically weighted regression (GWR) models were developed to establish a relationship between the crash counts reported in a TAZ and various contributing factors. Comparative analyses were conducted to compare the performance of GWR models which considered traditional traffic exposure variables only, Twitter-based human activity variables only, and both traditional traffic exposure and Twitter-based human activity variables. The model specification results suggested that human activity variables significantly affected the crash counts in a TAZ. The results of comparative analyses suggested that the models which considered both traditional traffic exposure and human activity variables had the best goodness-of-fit in terms of the highest R 2 and lowest AICc values. The finding seems to confirm the benefits of incorporating human activity information in spatial analysis of crashes using Twitter check-in data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Soft Mobility as a Smart Condition in a Mountain City

NASA Astrophysics Data System (ADS)

Virtudes, Ana; Azevedo, Henrique; Abbara, Arwa; Sá, João

2017-10-01

Nowadays soft mobility is a crucial issue towards a most sustainable urban environment. Not only because it promotes a less polluted atmosphere among the always dense and busy urban fabric, but also because it avoids several traffic problems. The use of bicycles, or mechanic mechanisms to support the pedestrian mobility is an emerging requirement of cities’ quality. In this sense, this article aims to discuss the soft mobility as a requirement of smart cities having as a case study one mountain urban area. It refers to the urban area of Covilhã on the highest mountain of Portugal with nearly two thousand meters high. During the last decades, this city’s transformation process has driven to an urban sprawl to the suburbs, increasing the efforts in terms of transportation required by the commuters. In fact, the number of inhabitants living in the city centre is decreasing in favour of the peripheral neighbourhoods. At the same time a set of several mechanic mechanisms such as public lifts, has been built in order to promote a soft pedestrian mobility. However, in many cases, because of the lack of connection and continuity of pedestrian paths in between these mechanisms, they are not allowing a pedestrian mobility network at the city scale. Thus, this paper aims to present a set of good practices in terms of pedestrian mobility network at the city scale, in order to promote a smarter urban environment. The principal results are that soft mobility is a key issue in order to turn cities smarter, among several other factors such as smart economy, smart people, smart governance or smart living. The major conclusions show that the concerns with mobility are key tools to achieve the smart city sustainability, providing and efficient and flexible traveling across the urban fabric, boosting the use of non-polluting ways of mobility. At the same time, there is the conclusion that the underlying areas of development for a smart city, despite its cultural or territorial environments, include several aspects such as reducing the transportation problems as congestion, traffic jams or painful accidents.

Interspecific comparison of traffic noise effects on dove coo transmission in urban environments.

PubMed

Shieh, Bao-Sen; Liang, Shih-Hsiung; Chiu, Yuh-Wen; Lin, Szu-Ying

2016-08-31

Most previous studies concerning avian adaptation to anthropogenic noise have focused on songbirds, but few have focused on non-songbirds commonly found in urban environments such as doves. We conducted field playback-recording experiments on the perch-coos of five dove species, including four native Taiwan species (the spotted dove, Spilopelia chinensis, the oriental turtle-dove, Streptopelia orientalis, the red collared-dove, Streptopelia tranquebarica, and the emerald dove, Chalcophaps indica) and one species not native to Taiwan (the zebra dove, Geopelia striata) to evaluate the detection and recognition of dove coos in habitats with differing levels of traffic noise. Our results suggest that traffic noise has selected dominant urban species such as the spotted dove to temporally and spatially adjust cooing to reduce the masking effects of traffic noise and rare urban species such as the emerald dove to avoid areas of high traffic noise. Additionally, although the zebra dove had the highest coo frequency among the study species, its coos showed the highest detection value but not the highest recognition value. We conclude that traffic noise is an important factor in shaping the distribution of rare and dominant dove species in urban environments through its significant effects on coo transmission.

Interspecific comparison of traffic noise effects on dove coo transmission in urban environments

NASA Astrophysics Data System (ADS)

Shieh, Bao-Sen; Liang, Shih-Hsiung; Chiu, Yuh-Wen; Lin, Szu-Ying

2016-08-01

Most previous studies concerning avian adaptation to anthropogenic noise have focused on songbirds, but few have focused on non-songbirds commonly found in urban environments such as doves. We conducted field playback-recording experiments on the perch-coos of five dove species, including four native Taiwan species (the spotted dove, Spilopelia chinensis, the oriental turtle-dove, Streptopelia orientalis, the red collared-dove, Streptopelia tranquebarica, and the emerald dove, Chalcophaps indica) and one species not native to Taiwan (the zebra dove, Geopelia striata) to evaluate the detection and recognition of dove coos in habitats with differing levels of traffic noise. Our results suggest that traffic noise has selected dominant urban species such as the spotted dove to temporally and spatially adjust cooing to reduce the masking effects of traffic noise and rare urban species such as the emerald dove to avoid areas of high traffic noise. Additionally, although the zebra dove had the highest coo frequency among the study species, its coos showed the highest detection value but not the highest recognition value. We conclude that traffic noise is an important factor in shaping the distribution of rare and dominant dove species in urban environments through its significant effects on coo transmission.

Research investigations in and demonstrations of remote sensing applications to urban environmental problems

NASA Technical Reports Server (NTRS)

Hidalgo, J. U.

1975-01-01

The applicability of remote sensing to transportation and traffic analysis, urban quality, and land use problems is discussed. Other topics discussed include preliminary user analysis, potential uses, traffic study by remote sensing, and urban condition analysis using ERTS.

Populations potentially exposed to traffic-related air pollution in seven world cities.

PubMed

Su, Jason G; Apte, Joshua S; Lipsitt, Jonah; Garcia-Gonzales, Diane A; Beckerman, Bernardo S; de Nazelle, Audrey; Texcalac-Sangrador, José Luis; Jerrett, Michael

2015-05-01

Traffic-related air pollution (TRAP) likely exerts a large burden of disease globally, and in many places, traffic is increasing dramatically. The impact, however, of urban form on the portion of population potentially exposed to TRAP remains poorly understood. In this study, we estimate portions of population potentially exposed to TRAP across seven global cities of various urban forms. Data on population distributions and road networks were collected from the best available sources in each city and from remote sensing analysis. Using spatial mapping techniques, we first overlaid road buffers onto population data to estimate the portions of population potentially exposed for four plausible impact zones. Based on a most likely scenario with impacts from highways up to 300meters and major roadways up to 50meters, we identified that the portions of population potentially exposed for the seven cities ranged from 23 to 96%. High-income North American cities had the lowest potential exposure portions, while those in Europe had the highest. Second, we adjusted exposure zone concentration levels based on a literature suggested multiplier for each city using corresponding background concentrations. Though Beijing and Mexico City did not have the highest portion of population exposure, those in their exposure zones had the highest levels of exposure. For all seven cities, the portion of population potentially exposed was positively correlated with roadway density and, to a lesser extent, with population density. These analyses suggest that urban form may influence the portion of population exposed to TRAP and vehicle emissions and other factors may influence the exposure levels. Greater understanding of urban form and other factors influencing potential exposure to TRAP may help inform interventions that protect public health. Copyright © 2014 Elsevier Ltd. All rights reserved.

Environmental impact of electric motorcycles: Evidence from traffic noise assessment by a building-based data mining technique.

PubMed

Sheng, N; Zhou, X; Zhou, Y

2016-06-01

This study provided new evidence on the potential adoption of electric motorcycle (EM) as a cleaner alternative to gasoline-powered motorcycle. The effects of EM on human exposure to traffic noise were assessed in different urban areas with different traffic scenarios. The assessment was carried out by a developed building-based model system that took into account the contribution of motorcycle traffic. The results indicated that the EM could be an appealing solution to reduce the risk of human exposure to excessive high traffic noise in a motorcycle city. Particularly, in a historical urban area in which the total traffic volume was lower and motorcycle traffic was dominant, the proportion of noise levels meeting the standard of 70 dB(A) increased significantly from 12.2% to 41.9% when 100% of gasoline motorcycles in the real traffic scenario were replaced by EMs. On the other hand, in a modern urban area in which the total traffic volume was higher and traffic noise levels at majority of sites were higher than 75 dB(A), the proportion of noise levels above 75 dB(A) decreased significantly from 82.6% to 59.9%. Nevertheless, the effect of EM on improving the traffic noise compliance rate in the modern urban area was not significant and other policies or measures need to be sought. Copyright © 2016 Elsevier B.V. All rights reserved.

Fine-granularity inference and estimations to network traffic for SDN.

PubMed

Jiang, Dingde; Huo, Liuwei; Li, Ya

2018-01-01

An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.

Fine-granularity inference and estimations to network traffic for SDN

PubMed Central

Huo, Liuwei; Li, Ya

2018-01-01

An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective. PMID:29718913

Study of annoyance due to urban automobile traffic. Annex 4: A catalog of the characteristics of noise at different measuring points

NASA Technical Reports Server (NTRS)

Aubree, D.; Auzou, S.; Rapin, J. M.

1984-01-01

The characteristics of urban traffic were studied. Data synthesis of and data specifically for the city of Paris concerning noise due to automobile traffic were examined. Information on noise characteristics at different measuring locations is presented.

Traffic placement policies for a multi-band network

NASA Technical Reports Server (NTRS)

Maly, Kurt J.; Foudriat, E. C.; Game, David; Mukkamala, R.; Overstreet, C. Michael

1990-01-01

Recently protocols were introduced that enable the integration of synchronous traffic (voice or video) and asynchronous traffic (data) and extend the size of local area networks without loss in speed or capacity. One of these is DRAMA, a multiband protocol based on broadband technology. It provides dynamic allocation of bandwidth among clusters of nodes in the total network. A number of traffic placement policies for such networks are proposed and evaluated. Metrics used for performance evaluation include average network access delay, degree of fairness of access among the nodes, and network throughput. The feasibility of the DRAMA protocol is established through simulation studies. DRAMA provides effective integration of synchronous and asychronous traffic due to its ability to separate traffic types. Under the suggested traffic placement policies, the DRAMA protocol is shown to handle diverse loads, mixes of traffic types, and numbers of nodes, as well as modifications to the network structure and momentary traffic overloads.

Cellular automata model for urban road traffic flow considering pedestrian crossing street

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Yang, Shuo; Chen, Xiao-Xu

2016-11-01

In order to analyze the effect of pedestrians' crossing street on vehicle flows, we investigated traffic characteristics of vehicles and pedestrians. Based on that, rules of lane changing, acceleration, deceleration, randomization and update are modified. Then we established two urban two-lane cellular automata models of traffic flow, one of which is about sections with non-signalized crosswalk and the other is on uncontrolled sections with pedestrians crossing street at random. MATLAB is used for numerical simulation of the different traffic conditions; meanwhile space-time diagram and relational graphs of traffic flow parameters are generated and then comparatively analyzed. Simulation results indicate that when vehicle density is lower than around 25 vehs/(km lane), pedestrians have modest impact on traffic flow, whereas when vehicle density is higher than about 60 vehs/(km lane), traffic speed and volume will decrease significantly especially on sections with non-signal-controlled crosswalk. The results illustrate that the proposed models reconstruct the traffic flow's characteristic with the situation where there are pedestrians crossing and can provide some practical reference for urban traffic management.

Topsoil investigation on two different urban areas in West Hungary

NASA Astrophysics Data System (ADS)

Horváth, Adrienn; Bidló, András

2015-04-01

Heavy metal contents of urban soils in two different urban areas have been investigated in Sopron town (169.01 km2) and in Szombathely town 97.50 km2) in Hungary. In a standard network 208 samples have been collected Sopron from 0 to 10 and from 10 to 20 cm depth. 164 samples have been taken on 88 points in the area of Szombathely. We analysed all of the soil samples with ICP equipment applying Lakanen-Erviö method (Ammonium Acetate - EDTA (pH 4.65)) and we focused on Co, Cu, Ni, Pb and Zn during the evaluation. The soils of suburb are determined largely by the bedrock, but in the downtown the soil pH was alkaline in soils of Sopron. Therefore, the toxic elements are still accumulated in the topsoil. The lead content was very high (suggested pollution limit >25 mg Pb/kg) in both layers on the whole area of the town. Urban soils with high copper content (among 611 mg and 1221 mg Cu/kg) have been collected from garden and viticulture areas. According to our measurements we found the highest average values in the soils of parks. The pH of urban topsoils of Szombathely was mostly neutral and it was lower in soil of agricultural areas on the suburb, where the artificial fertiliser is still used. The Pb content was high (more than 25 mg Pb/kg) in case of 13 samples next to traffic roads of the town. The Co, Cu and Ni results were below the suggested Hungarian background limits. The Zn values were above the suggested Hungarian pollution (20 mg Zn/kg) and interventional limits (>40 mg Zn/kg) in most cases. According to the results we found the highest average values of heavy metals in the soil of traffic areas or next to the Gyöngyös creek, which could be originated from traffic contamination, binding in the soil of urban green spaces, thus possibly affects human health. The research is supported by the "Agroclimate-2" (VKSZ_12-1-2013-0034) joint EU-national research project. Keywords: anthropogenic effects, heavy metal content, lead pollution, polluted urban soils

Prevalence and regional correlates of road traffic injury among Chinese urban residents: A 21-city population-based study.

PubMed

Rockett, Ian R H; Jiang, Shuhan; Yang, Qian; Yang, Tingzhong; Yang, Xiaozhao Y; Peng, Sihui; Yu, Lingwei

2017-08-18

This study estimated the prevalence of road traffic injury among Chinese urban residents and examined individual and regional-level correlates. A cross-sectional multistage process was used to sample residents from 21 selected cities in China. Survey respondents reported their history of road traffic injury in the past 12 months through a community survey. Multilevel, multivariable logistic regression analysis was used to identify injury correlates. Based on a retrospective 12-month reporting window, road traffic injury prevalence among urban residents was 13.2%. Prevalence of road traffic injury, by type, was 8.7, 8.7, 8.5, and 7.7% in the automobile, bicycle, motorcycle, and pedestrian categories, respectively. Multilevel analysis showed that prevalence of road traffic injury was positively associated with minority status, income, and mental health disorder score at the individual level. Regionally, road traffic injury was associated with geographic location of residence and prevalence of mental health disorders. Both individual and regional-level variables were associated with road traffic injury among Chinese urban residents, a finding whose implications transcend wholesale imported generic solutions. This descriptive research demonstrates an urgent need for longitudinal studies across China on risk and protective factors, in order to inform injury etiology, surveillance, prevention, treatment, and evaluation.

Traffic Driven Analysis of Cellular and WiFi Networks

ERIC Educational Resources Information Center

Paul, Utpal Kumar

2012-01-01

Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…

Estimates of CO2 traffic emissions from mobile concentration measurements

NASA Astrophysics Data System (ADS)

Maness, H. L.; Thurlow, M. E.; McDonald, B. C.; Harley, R. A.

2015-03-01

We present data from a new mobile system intended to aid in the design of upcoming urban CO2-monitoring networks. Our collected data include GPS probe data, video-derived traffic density, and accurate CO2 concentration measurements. The method described here is economical, scalable, and self-contained, allowing for potential future deployment in locations without existing traffic infrastructure or vehicle fleet information. Using a test data set collected on California Highway 24 over a 2 week period, we observe that on-road CO2 concentrations are elevated by a factor of 2 in congestion compared to free-flow conditions. This result is found to be consistent with a model including vehicle-induced turbulence and standard engine physics. In contrast to surface concentrations, surface emissions are found to be relatively insensitive to congestion. We next use our model for CO2 concentration together with our data to independently derive vehicle emission rate parameters. Parameters scaling the leading four emission rate terms are found to be within 25% of those expected for a typical passenger car fleet, enabling us to derive instantaneous emission rates directly from our data that compare generally favorably to predictive models presented in the literature. The present results highlight the importance of high spatial and temporal resolution traffic data for interpreting on- and near-road concentration measurements. Future work will focus on transport and the integration of mobile platforms into existing stationary network designs.

Spatial and temporal variations in traffic-related particulate matter at New York City high schools

NASA Astrophysics Data System (ADS)

Patel, Molini M.; Chillrud, Steven N.; Correa, Juan C.; Feinberg, Marian; Hazi, Yair; Deepti, K. C.; Prakash, Swati; Ross, James M.; Levy, Diane; Kinney, Patrick L.

Relatively little is known about exposures to traffic-related particulate matter at schools located in dense urban areas. The purpose of this study was to examine the influences of diesel traffic proximity and intensity on ambient concentrations of fine particulate matter (PM 2.5) and black carbon (BC), an indicator of diesel exhaust particles, at New York City (NYC) high schools. Outdoor PM 2.5 and BC were monitored continuously for 4-6 weeks at each of 3 NYC schools and 1 suburban school located 40 km upwind of the city. Traffic count data were obtained using an automated traffic counter or video camera. BC concentrations were 2-3 fold higher at urban schools compared with the suburban school, and among the 3 urban schools, BC concentrations were higher at schools located adjacent to highways. PM 2.5 concentrations were significantly higher at urban schools than at the suburban school, but concentrations did not vary significantly among urban schools. Both hourly average counts of trucks and buses and meteorological factors such as wind direction, wind speed, and humidity were significantly associated with hourly average ambient BC and PM 2.5 concentrations in multivariate regression models. An increase of 443 trucks/buses per hour was associated with a 0.62 μg/m 3 increase in hourly average BC at an NYC school located adjacent to a major interstate highway. Car traffic counts were not associated with BC. The results suggest that local diesel vehicle traffic may be important sources of airborne fine particles in dense urban areas and consequently may contribute to local variations in PM 2.5 concentrations. In urban areas with higher levels of diesel traffic, local, neighborhood-scale monitoring of pollutants such as BC, which compared to PM 2.5, is a more specific indicator of diesel exhaust particles, may more accurately represent population exposures.

Ultrasonic Sensors in Urban Traffic Driving-Aid Systems

PubMed Central

Alonso, Luciano; Milanés, Vicente; Torre-Ferrero, Carlos; Godoy, Jorge; Oria, Juan P.; de Pedro, Teresa

2011-01-01

Currently, vehicles are often equipped with active safety systems to reduce the risk of accidents, most of which occur in urban environments. The most prominent include Antilock Braking Systems (ABS), Traction Control and Stability Control. All these systems use different kinds of sensors to constantly monitor the conditions of the vehicle, and act in an emergency. In this paper the use of ultrasonic sensors in active safety systems for urban traffic is proposed, and the advantages and disadvantages when compared to other sensors are discussed. Adaptive Cruise Control (ACC) for urban traffic based on ultrasounds is presented as an application example. The proposed system has been implemented in a fully-automated prototype vehicle and has been tested under real traffic conditions. The results confirm the good performance of ultrasonic sensors in these systems. PMID:22346596

Ultrasonic sensors in urban traffic driving-aid systems.

PubMed

Alonso, Luciano; Milanés, Vicente; Torre-Ferrero, Carlos; Godoy, Jorge; Oria, Juan P; de Pedro, Teresa

2011-01-01

Currently, vehicles are often equipped with active safety systems to reduce the risk of accidents, most of which occur in urban environments. The most prominent include Antilock Braking Systems (ABS), Traction Control and Stability Control. All these systems use different kinds of sensors to constantly monitor the conditions of the vehicle, and act in an emergency. In this paper the use of ultrasonic sensors in active safety systems for urban traffic is proposed, and the advantages and disadvantages when compared to other sensors are discussed. Adaptive Cruise Control (ACC) for urban traffic based on ultrasounds is presented as an application example. The proposed system has been implemented in a fully-automated prototype vehicle and has been tested under real traffic conditions. The results confirm the good performance of ultrasonic sensors in these systems.

Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately

Effects of traffic generation patterns on the robustness of complex networks

NASA Astrophysics Data System (ADS)

Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui

2018-02-01

Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.

The treatment of uncertainties in reactive pollution dispersion models at urban scales.

PubMed

Tomlin, A S; Ziehn, T; Goodman, P; Tate, J E; Dixon, N S

2016-07-18

The ability to predict NO2 concentrations ([NO2]) within urban street networks is important for the evaluation of strategies to reduce exposure to NO2. However, models aiming to make such predictions involve the coupling of several complex processes: traffic emissions under different levels of congestion; dispersion via turbulent mixing; chemical processes of relevance at the street-scale. Parameterisations of these processes are challenging to quantify with precision. Predictions are therefore subject to uncertainties which should be taken into account when using models within decision making. This paper presents an analysis of mean [NO2] predictions from such a complex modelling system applied to a street canyon within the city of York, UK including the treatment of model uncertainties and their causes. The model system consists of a micro-scale traffic simulation and emissions model, and a Reynolds averaged turbulent flow model coupled to a reactive Lagrangian particle dispersion model. The analysis focuses on the sensitivity of predicted in-street increments of [NO2] at different locations in the street to uncertainties in the model inputs. These include physical characteristics such as background wind direction, temperature and background ozone concentrations; traffic parameters such as overall demand and primary NO2 fraction; as well as model parameterisations such as roughness lengths, turbulent time- and length-scales and chemical reaction rate coefficients. Predicted [NO2] is shown to be relatively robust with respect to model parameterisations, although there are significant sensitivities to the activation energy for the reaction NO + O3 as well as the canyon wall roughness length. Under off-peak traffic conditions, demand is the key traffic parameter. Under peak conditions where the network saturates, road-side [NO2] is relatively insensitive to changes in demand and more sensitive to the primary NO2 fraction. The most important physical parameter was found to be the background wind direction. The study highlights the key parameters required for reliable [NO2] estimations suggesting that accurate reference measurements for wind direction should be a critical part of air quality assessments for in-street locations. It also highlights the importance of street scale chemical processes in forming road-side [NO2], particularly for regions of high NOx emissions such as close to traffic queues.

Variability in exposure to ambient ultrafine particles in urban schools: Comparative assessment between Australia and Spain.

PubMed

Mazaheri, Mandana; Reche, Cristina; Rivas, Ioar; Crilley, Leigh R; Álvarez-Pedrerol, Mar; Viana, Mar; Tobias, Aurelio; Alastuey, Andrés; Sunyer, Jordi; Querol, Xavier; Morawska, Lidia

2016-03-01

Ambient ultrafine particle number concentrations (PNC) have inhomogeneous spatio-temporal distributions and depend on a number of different urban factors, including background conditions and distant sources. This paper quantitatively compares exposure to ambient ultrafine particles at urban schools in two cities in developed countries, with high insolation climatic conditions, namely Brisbane (Australia) and Barcelona (Spain). The analysis used comprehensive indoor and outdoor air quality measurements at 25 schools in Brisbane and 39 schools in Barcelona. PNC modes were analysed with respect to ambient temperature, land use and urban characteristics, combined with the measured elemental carbon concentrations, NOx (Brisbane) and NO2 (Barcelona). The trends and modes of the quantified weekday average daily cycles of ambient PNC exhibited significant differences between the two cities. PNC increases were observed during traffic rush hours in both cases. However, the mid-day peak was dominant in Brisbane schools and had the highest contribution to total PNC for both indoors and outdoors. In Barcelona, the contribution from traffic was highest for ambient PNC, while the mid-day peak had a slightly higher contribution for indoor concentrations. Analysis of the relationships between PNC and land use characteristics in Barcelona schools showed a moderate correlation with the percentage of road network area and an anti-correlation with the percentage of green area. No statistically significant correlations were found for Brisbane. Overall, despite many similarities between the two cities, school-based exposure patterns were different. The main source of ambient PNC at schools was shown to be traffic in Barcelona and mid-day new particle formation in Brisbane. The mid-day PNC peak in Brisbane could have been driven by the combined effect of background and meteorological conditions, as well as other local/distant sources. The results have implications for urban development, especially in terms of air quality mitigation and management at schools. Copyright © 2015 Elsevier Ltd. All rights reserved.

SCALING AN URBAN EMERGENCY EVACUATION FRAMEWORK: CHALLENGES AND PRACTICES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karthik, Rajasekar; Lu, Wei

2014-01-01

Critical infrastructure disruption, caused by severe weather events, natural disasters, terrorist attacks, etc., has significant impacts on urban transportation systems. We built a computational framework to simulate urban transportation systems under critical infrastructure disruption in order to aid real-time emergency evacuation. This framework will use large scale datasets to provide a scalable tool for emergency planning and management. Our framework, World-Wide Emergency Evacuation (WWEE), integrates population distribution and urban infrastructure networks to model travel demand in emergency situations at global level. Also, a computational model of agent-based traffic simulation is used to provide an optimal evacuation plan for traffic operationmore » purpose [1]. In addition, our framework provides a web-based high resolution visualization tool for emergency evacuation modelers and practitioners. We have successfully tested our framework with scenarios in both United States (Alexandria, VA) and Europe (Berlin, Germany) [2]. However, there are still some major drawbacks for scaling this framework to handle big data workloads in real time. On our back-end, lack of proper infrastructure limits us in ability to process large amounts of data, run the simulation efficiently and quickly, and provide fast retrieval and serving of data. On the front-end, the visualization performance of microscopic evacuation results is still not efficient enough due to high volume data communication between server and client. We are addressing these drawbacks by using cloud computing and next-generation web technologies, namely Node.js, NoSQL, WebGL, Open Layers 3 and HTML5 technologies. We will describe briefly about each one and how we are using and leveraging these technologies to provide an efficient tool for emergency management organizations. Our early experimentation demonstrates that using above technologies is a promising approach to build a scalable and high performance urban emergency evacuation framework that can improve traffic mobility and safety under critical infrastructure disruption in today s socially connected world.« less

Impact on air quality of measures to reduce CO2 emissions from road traffic in Basel, Rotterdam, Xi'an and Suzhou

NASA Astrophysics Data System (ADS)

Keuken, M. P.; Jonkers, S.; Verhagen, H. L. M.; Perez, L.; Trüeb, S.; Okkerse, W.-J.; Liu, J.; Pan, X. C.; Zheng, L.; Wang, H.; Xu, R.; Sabel, C. E.

2014-12-01

Two traffic scenarios to reduce CO2 emissions from road traffic in two European cities (Basel and Rotterdam) and two Chinese cities (Xi'an and Suzhou) were evaluated in terms of their impact on air quality. The two scenarios, one modelling a reduction of private vehicle kilometres driven by 10% on urban streets and the other modelling the introduction of 50% electric-powered private vehicle kilometres on urban streets, were both compared to a scenario following “business-as-usual”: 2020-BAU. The annual average concentrations of NO2, PM2.5, PM10 and elemental carbon (EC) were modelled separately in busy street canyons, near urban motorways and in the remainder of the urban area. It was concluded that traffic-related CO2 emissions in 2020-BAU could be expected to remain at the levels of 2010 in Basel and Rotterdam, while in Xi'an and Suzhou to increase 30-50% due to growth in the traffic volume. Traffic-related CO2 emissions may be reduced by up to 5% and 25%, respectively using the first and second scenarios. Air pollution in the Chinese cities is a factor 3 to 5 higher than in the European cities in 2010 and 2020-BAU. The impact of both CO2 reduction scenarios on air quality in 2020-BAU is limited. In Europe, due to implementation of stringent emission standards in all sectors, air quality is expected to improve at both the urban background and near busy road traffic. In China, the regional background is expected to improve for EC, stabilize for PM2.5 and PM10, and decrease for NO2. The urban background follows this regional trend, while near busy road traffic, air pollution will remain elevated due to the considerable growth in traffic volume. A major constraint for modelling air quality in China is access to the input data required and lack of measurements at ground level for validation.

Modeling carbon emissions from urban traffic system using mobile monitoring.

PubMed

Sun, Daniel Jian; Zhang, Ying; Xue, Rui; Zhang, Yi

2017-12-01

Comprehensive analyses of urban traffic carbon emissions are critical in achieving low-carbon transportation. This paper started from the architecture design of a carbon emission mobile monitoring system using multiple sets of equipment and collected the corresponding data about traffic flow, meteorological conditions, vehicular carbon emissions and driving characteristics on typical roads in Shanghai and Wuxi, Jiangsu province. Based on these data, the emission model MOVES was calibrated and used with various sensitivity and correlation evaluation indices to analyze the traffic carbon emissions at microscopic, mesoscopic and macroscopic levels, respectively. The major factors that influence urban traffic carbon emissions were investigated, so that emission factors of CO, CO 2 and HC were calculated by taking representative passenger cars as a case study. As a result, the urban traffic carbon emissions were assessed quantitatively, and the total amounts of CO, CO 2 and HC emission from passenger cars in Shanghai were estimated as 76.95kt, 8271.91kt, and 2.13kt, respectively. Arterial roads were found as the primary line source, accounting for 50.49% carbon emissions. In additional to the overall major factors identified, the mobile monitoring system and carbon emission quantification method proposed in this study are of rather guiding significance for the further urban low-carbon transportation development. Copyright © 2017 Elsevier B.V. All rights reserved.

Urban snow indicates pollution originating from road traffic.

PubMed

Kuoppamäki, Kirsi; Setälä, Heikki; Rantalainen, Anna-Lea; Kotze, D Johan

2014-12-01

Traffic is a major source of pollutants in cities. In this well-replicated study we analysed a broad array of contaminants in snowpacks along roads of different traffic intensities. The majority of pollutants showed a similar pattern with respect to traffic intensity: pH and conductivity as well as concentrations of PAHs, total suspended solids, phosphorus and most heavy metals were higher next to high intensity roads compared to low intensity roads. These pollutant levels also decreased considerably up to 5 m distance from the roads. Furthermore, apart from nitrogen, these variables increased in concentration from control sites in urban forest patches to road bank sites next to roads of low, intermediate and high traffic intensities. The deposition pattern of various traffic-derived pollutants--whether gaseous or particle-bound--was the same. Such information can be useful for the purposes of managing pollutants in urban areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting Information Flows in Network Traffic.

ERIC Educational Resources Information Center

Hinich, Melvin J.; Molyneux, Robert E.

2003-01-01

Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

Relationship between microscopic dynamics in traffic flow and complexity in networks.

PubMed

Li, Xin-Gang; Gao, Zi-You; Li, Ke-Ping; Zhao, Xiao-Mei

2007-07-01

Complex networks are constructed in the evolution process of traffic flow, and the states of traffic flow are represented by nodes in the network. The traffic dynamics can then be studied by investigating the statistical properties of those networks. According to Kerner's three-phase theory, there are two different phases in congested traffic, synchronized flow and wide moving jam. In the framework of this theory, we study different properties of synchronized flow and moving jam in relation to complex network. Scale-free network is constructed in stop-and-go traffic, i.e., a sequence of moving jams [Chin. Phys. Lett. 10, 2711 (2005)]. In this work, the networks generated in synchronized flow are investigated in detail. Simulation results show that the degree distribution of the networks constructed in synchronized flow has two power law regions, so the distinction in topological structure can really reflect the different dynamics in traffic flow. Furthermore, the real traffic data are investigated by this method, and the results are consistent with the simulations.

Urban trees and traffic safety: considering the U.S. roadside policy and crash data

Treesearch

Kathleen L. Wolf

2006-01-01

In the mid to late 20th century, U.S. transportation agencies focused on traffic planning and design practices intended to achieve high levels of traffic capacity and safety for roads at lowest cost. Intangible values of the roadside such as community character and environmental systems were often overlooked, including the urban forest....

Research on Influence and Prediction Model of Urban Traffic Link Tunnel curvature on Fire Temperature Based on Pyrosim--SPSS Multiple Regression Analysis

NASA Astrophysics Data System (ADS)

Li, Xiao Ju; Yao, Kun; Dai, Jun Yu; Song, Yun Long

2018-05-01

The underground space, also known as the “fourth dimension” of the city, reflects the efficient use of urban development intensive. Urban traffic link tunnel is a typical underground limited-length space. Due to the geographical location, the special structure of space and the curvature of the tunnel, high-temperature smoke can easily form the phenomenon of “smoke turning” and the fire risk is extremely high. This paper takes an urban traffic link tunnel as an example to focus on the relationship between curvature and the temperature near the fire source, and use the pyrosim built different curvature fire model to analyze the influence of curvature on the temperature of the fire, then using SPSS Multivariate regression analysis simulate curvature of the tunnel and fire temperature data. Finally, a prediction model of urban traffic link tunnel curvature on fire temperature was proposed. The regression model analysis and test show that the curvature is negatively correlated with the tunnel temperature. This model is feasible and can provide a theoretical reference for the urban traffic link tunnel fire protection design and the preparation of the evacuation plan. And also, it provides some reference for other related curved tunnel curvature design and smoke control measures.

[Analysis of the death cases in the urban rail traffic accident in Shanghai].

PubMed

Hu, Yi-Ping; Cao, Yu; Ma, Kai-Jun

2009-06-01

To analyze the features of death cases in the urban rail traffic accidents in order to prevent the similar accidents in the future and to provide reference for forensic expertise. Eighteen death cases in urban rail traffic accidents between 2005 to 2008 in Shanghai were collected. The forensic characteristics were summarized in aspects of the nature of cases, the injury mechanism and characteristics, etc. There were total 18 cases with 14 suicide and 4 accidental incidents, aged from 21 to 55 years. Of those dead, 14 died of craniocerebral injury and 4 died of traumatic shock. The injury mechanism included hit, fall and rolling. The injury in urban rail traffic accidents have their own characteristics, mainly due to suicide, and partly due to accidental incident, and most of these cases are probably preventable.

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

PubMed Central

Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

2017-01-01

Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction. PMID:28672867

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

PubMed

Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

2017-06-26

Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

Analysis of the build-up of semi and non volatile organic compounds on urban roads.

PubMed

Mahbub, Parvez; Ayoko, Godwin A; Goonetilleke, Ashantha; Egodawatta, Prasanna

2011-04-01

Vehicular traffic in urban areas may adversely affect urban water quality through the build-up of traffic generated semi and non volatile organic compounds (SVOCs and NVOCs) on road surfaces. The characterisation of the build-up processes is the key to developing mitigation measures for the removal of such pollutants from urban stormwater. An in-depth analysis of the build-up of SVOCs and NVOCs was undertaken in the Gold Coast region in Australia. Principal Component Analysis (PCA) and Multicriteria Decision tools such as PROMETHEE and GAIA were employed to understand the SVOC and NVOC build-up under combined traffic scenarios of low, moderate, and high traffic in different land uses. It was found that congestion in the commercial areas and use of lubricants and motor oils in the industrial areas were the main sources of SVOCs and NVOCs on urban roads, respectively. The contribution from residential areas to the build-up of such pollutants was hardly noticeable. It was also revealed through this investigation that the target SVOCs and NVOCs were mainly attached to particulate fractions of 75-300 μm whilst the redistribution of coarse fractions due to vehicle activity mainly occurred in the >300 μm size range. Lastly, under combined traffic scenario, moderate traffic with average daily traffic ranging from 2300 to 5900 and average congestion of 0.47 were found to dominate SVOC and NVOC build-up on roads. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Harmonized Perspective on Transportation Management in Smart Cities: The Novel IoT-Driven Environment for Road Traffic Modeling.

PubMed

Masek, Pavel; Masek, Jan; Frantik, Petr; Fujdiak, Radek; Ometov, Aleksandr; Hosek, Jiri; Andreev, Sergey; Mlynek, Petr; Misurec, Jiri

2016-11-08

The unprecedented growth of today's cities together with increased population mobility are fueling the avalanche in the numbers of vehicles on the roads. This development led to the new challenges for the traffic management, including the mitigation of road congestion, accidents, and air pollution. Over the last decade, researchers have been focusing their efforts on leveraging the recent advances in sensing, communications, and dynamic adaptive technologies to prepare the deployed road traffic management systems (TMS) for resolving these important challenges in future smart cities. However, the existing solutions may still be insufficient to construct a reliable and secure TMS that is capable of handling the anticipated influx of the population and vehicles in urban areas. Along these lines, this work systematically outlines a perspective on a novel modular environment for traffic modeling, which allows to recreate the examined road networks in their full resemblance. Our developed solution is targeted to incorporate the progress in the Internet of Things (IoT) technologies, where low-power, embedded devices integrate as part of a next-generation TMS. To mimic the real traffic conditions, we recreated and evaluated a practical traffic scenario built after a complex road intersection within a large European city.

A Harmonized Perspective on Transportation Management in Smart Cities: The Novel IoT-Driven Environment for Road Traffic Modeling

PubMed Central

Masek, Pavel; Masek, Jan; Frantik, Petr; Fujdiak, Radek; Ometov, Aleksandr; Hosek, Jiri; Andreev, Sergey; Mlynek, Petr; Misurec, Jiri

2016-01-01

The unprecedented growth of today’s cities together with increased population mobility are fueling the avalanche in the numbers of vehicles on the roads. This development led to the new challenges for the traffic management, including the mitigation of road congestion, accidents, and air pollution. Over the last decade, researchers have been focusing their efforts on leveraging the recent advances in sensing, communications, and dynamic adaptive technologies to prepare the deployed road traffic management systems (TMS) for resolving these important challenges in future smart cities. However, the existing solutions may still be insufficient to construct a reliable and secure TMS that is capable of handling the anticipated influx of the population and vehicles in urban areas. Along these lines, this work systematically outlines a perspective on a novel modular environment for traffic modeling, which allows to recreate the examined road networks in their full resemblance. Our developed solution is targeted to incorporate the progress in the Internet of Things (IoT) technologies, where low-power, embedded devices integrate as part of a next-generation TMS. To mimic the real traffic conditions, we recreated and evaluated a practical traffic scenario built after a complex road intersection within a large European city. PMID:27834796

An Anomalous Noise Events Detector for Dynamic Road Traffic Noise Mapping in Real-Life Urban and Suburban Environments.

PubMed

Socoró, Joan Claudi; Alías, Francesc; Alsina-Pagès, Rosa Ma

2017-10-12

One of the main aspects affecting the quality of life of people living in urban and suburban areas is their continued exposure to high Road Traffic Noise (RTN) levels. Until now, noise measurements in cities have been performed by professionals, recording data in certain locations to build a noise map afterwards. However, the deployment of Wireless Acoustic Sensor Networks (WASN) has enabled automatic noise mapping in smart cities. In order to obtain a reliable picture of the RTN levels affecting citizens, Anomalous Noise Events (ANE) unrelated to road traffic should be removed from the noise map computation. To this aim, this paper introduces an Anomalous Noise Event Detector (ANED) designed to differentiate between RTN and ANE in real time within a predefined interval running on the distributed low-cost acoustic sensors of a WASN. The proposed ANED follows a two-class audio event detection and classification approach, instead of multi-class or one-class classification schemes, taking advantage of the collection of representative acoustic data in real-life environments. The experiments conducted within the DYNAMAP project, implemented on ARM-based acoustic sensors, show the feasibility of the proposal both in terms of computational cost and classification performance using standard Mel cepstral coefficients and Gaussian Mixture Models (GMM). The two-class GMM core classifier relatively improves the baseline universal GMM one-class classifier F1 measure by 18.7% and 31.8% for suburban and urban environments, respectively, within the 1-s integration interval. Nevertheless, according to the results, the classification performance of the current ANED implementation still has room for improvement.

Assessment of Exposure of Elementary Schools to Traffic Pollution by GIS Methods.

PubMed

Štych, Přemysl; Šrámková, Denisa; Braniš, Martin

2016-06-01

The susceptibility of children to polluted air has been pointed out several times in the past. Generally, children suffer from higher exposure to air pollutants than adults because of their higher physical activity, higher metabolic rate and the resultant increase in minute ventilation. The aim of this study was to examine the exposure characteristics of public elementary schools in Prague (the capital of the Czech Republic). The exposure was examined by two different methods: by the proximity of selected schools to major urban roads and their location within the modeled urban PM10 concentration fields. We determined average daily traffic counts for all roads within 300 m of 251 elementary schools using the national road network database and geographic information system and calculated by means of GIS tools the proximity of the schools to the roads. In the second method we overlapped the GIS layer of predicted annual urban PM10 concentration field with that of geocoded school addresses. The results showed that 208 Prague schools (almost 80%) are situated in a close proximity (<300 m) of roads exhibiting high traffic loads. Both methods showed good agreement in the proportion of highly exposed schools at risk; however, we found significant differences in the locations of schools at risk determined by the two methods. We argue that results of similar proximity studies should be treated with caution before they are used in risk based decision-making process, since different methods may provide different outcomes. Copyright© by the National Institute of Public Health, Prague 2015.

The Monitoring and Spatial-Temporal Evolution Characteristic Analysis for Land Subsidence in Beijing

NASA Astrophysics Data System (ADS)

Zhou, Q.; Zhao, W.; Yu, J.

2018-05-01

At present the land subsidence has been the main geological disaster in the plain area of China, and became one of the most serious disaster that restrict the social and economic sustainable development, it also is an important content in the project of national geographic conditions monitoring. With the development of economy and society, Beijing as the capital of China has experienced significant population growth in the last few decades which led to over-exploitation of the ground water to meet the water demand of more than 20 million inhabitants, especially in the urban region with high population density. However, the rainfall and surface runoff can't satisfy the need of aquifer recharge that product the land subsidence. As China's political center and a metropolis, there are a lot of large constructions, underground traffic projects and complicated municipal pipeline network, and Beijing is also an important traffic hub for national railway and highway network, all of them would be threatened by the land subsidence disaster. In this article the author used twenty ENVISAT Synthetic Aperture Radar (SAR) images acquired in 2008 June-2010 August and ten TerraSAR images acquired in 2011 June-2012 September were processed with Small Baseline Subset SAR Interferometry (SBAS-InSAR) techniques, to investigate spatial and temporal patterns of land subsidence in the urban area of Beijing.

Measuring accident risk exposure for pedestrians in different micro-environments.

PubMed

Lassarre, Sylvain; Papadimitriou, Eleonora; Yannis, George; Golias, John

2007-11-01

Pedestrians are mainly exposed to the risk of road accident when crossing a road in urban areas. Traditionally in the road safety field, the risk of accident for pedestrian is estimated as a rate of accident involvement per unit of time spent on the road network. The objective of this research is to develop an approach of accident risk based on the concept of risk exposure used in environmental epidemiology, such as in the case of exposure to pollutants. This type of indicator would be useful for comparing the effects of urban transportation policy scenarios on pedestrian safety. The first step is to create an indicator of pedestrians' exposure, which is based on motorised vehicles' "concentration" by lane and also takes account of traffic speed and time spent to cross. This is applied to two specific micro-environments: junctions and mid-block locations. A model of pedestrians' crossing behaviour along a trip is then developed, based on a hierarchical choice between junctions and mid-block locations and taking account of origin and destination, traffic characteristics and pedestrian facilities. Finally, a complete framework is produced for modelling pedestrians' exposure in the light of their crossing behaviour. The feasibility of this approach is demonstrated on an artificial network and a first set of results is obtained from the validation of the models in observational studies.

Residents' evaluation of urban environments: attraction of urban life and anxiety associated with traffic accidents and urban crimes.

PubMed

Tachikawa, Tomoko; Hashimoto, Shusa

2007-12-01

The results of questionnaire and interview surveys conducted in Mitaka and Musashino cities are presented for investigating of residents' evaluation of their urban environment, particularly regarding its attractiveness. A special attention was paid to residents' evaluation with regard to anxiety associated with traffic accidents and urban crimes. The urban infrastructure and residents' responses were examined using a Geographic Information System (GIS). Attractiveness associated with the urban environment was classified into two categories: "attractiveness in daily life" and "attractiveness in non-daily life." The residents valued opportunities for relaxing and living in comfort. In non-daily life, the residents specifically valued improved living conditions and harmony between the natural environment and commercial facilities. They attributed crime anxiety to trees, narrow streets, obstructed views, dark areas and a gloomy atmosphere. Residents regarded violent crimes as being prevalent, but considered trespassing and property crimes infrequent. The residents' anxiety about traffic accidents was caused by reckless driving habits, narrow streets, lack of separation between roadway and pedestrians' ways, heavy traffic, and obstructed views. Residents cited main roads and intersections as locations of anxiety, which concurred with frequent accidents.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

PubMed

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-04-10

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

PubMed Central

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-01-01

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270

The impact of traffic emissions on air quality in the Berlin-Brandenburg region - a case study on cycling scenarios

NASA Astrophysics Data System (ADS)

Kuik, F.; Lauer, A.; von Schneidemesser, E.; Butler, T. M.

2016-12-01

Many European cities continue to struggle with exceedances of NO2 limit values at measurement sites near roads, of which a large contribution is attributed to emissions from traffic. In this study, we explore how urban air quality can be improved with different traffic measures using the example of the Berlin-Brandenburg region. In order to simulate urban background air quality we use the Weather Research and Forecasting model with chemistry (WRF-Chem) at a horizontal resolution of 1km. We use emission input data at a horizontal resolution of 1km obtained by downscaling TNO-MACC III emissions based on local proxy data including population and traffic densities. In addition we use a statistical approach combining the simulated urban background concentrations with information on traffic densities to estimate NO2 at street level. This helps assessing whether the emission scenarios studied here can lead to significant reductions in NO2 concentrations at street level. The emission scenarios in this study represent a range of scenarios in which car traffic is replaced with bicycle traffic. Part of this study was an initial discussion phase with stakeholders, including policy makers and NGOs. The discussions have shown that the different stakeholders are interested in a scientific assessment of the impact of replacing car traffic with bicycle traffic in the Berlin-Brandenburg urban area. Local policy makers responsible for city planning and implementing traffic measures can make best use of scientific modeling results if input data and scenarios are as realistic as possible. For these reasons, the scenarios cover very idealized optimistic ("all passenger cars are replaced by bicycles") and pessimistic ("all cyclists are replaced by cars") scenarios to explore the sensitivity of simulated urban background air quality to these changes, as well as additional scenarios based on city-specific data to analyze more realistic situations. Of particular interest is how these impact street level NO2 concentrations.

An adaptable neural-network model for recursive nonlinear traffic prediction and modeling of MPEG video sources.

PubMed

Doulamis, A D; Doulamis, N D; Kollias, S D

2003-01-01

Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.

Air quality assessment of Estarreja, an urban industrialized area, in a coastal region of Portugal.

PubMed

Figueiredo, M L; Monteiro, A; Lopes, M; Ferreira, J; Borrego, C

2013-07-01

Despite the increasing concern given to air quality in urban and industrial areas in recent years, particular emphasis on regulation, control, and reduction of air pollutant emissions is still necessary to fully characterize the chain emissions-air quality-exposure-dose-health effects, for specific sources. The Estarreja region was selected as a case study because it has one of the largest chemical industrial complexes in Portugal that has been recently expanded, together with a growing urban area with an interesting location in the Portuguese coastland and crossed by important road traffic and rail national networks. This work presents the first air quality assessment for the region concerning pollutant emissions and meteorological and air quality monitoring data analysis, over the period 2000-2009. This assessment also includes a detailed investigation and characterization of past air pollution episodes for the most problematic pollutants: ozone and PM10. The contribution of different emission sources and meteorological conditions to these episodes is investigated. The stagnant meteorological conditions associated with local emissions, namely industrial activity and road traffic, are the major contributors to the air quality degradation over the study region. A set of measures to improve air quality--regarding ozone and PM10 levels--is proposed as an air quality management strategy for the study region.

Evidence of Long Range Dependence and Self-similarity in Urban Traffic Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thakur, Gautam S; Helmy, Ahmed; Hui, Pan

2015-01-01

Transportation simulation technologies should accurately model traffic demand, distribution, and assignment parame- ters for urban environment simulation. These three param- eters significantly impact transportation engineering bench- mark process, are also critical in realizing realistic traffic modeling situations. In this paper, we model and charac- terize traffic density distribution of thousands of locations around the world. The traffic densities are generated from millions of images collected over several years and processed using computer vision techniques. The resulting traffic den- sity distribution time series are then analyzed. It is found using the goodness-of-fit test that the traffic density dis- tributions follows heavy-tailmore » models such as Log-gamma, Log-logistic, and Weibull in over 90% of analyzed locations. Moreover, a heavy-tail gives rise to long-range dependence and self-similarity, which we studied by estimating the Hurst exponent (H). Our analysis based on seven different Hurst estimators strongly indicate that the traffic distribution pat- terns are stochastically self-similar (0.5 H 1.0). We believe this is an important finding that will influence the design and development of the next generation traffic simu- lation techniques and also aid in accurately modeling traffic engineering of urban systems. In addition, it shall provide a much needed input for the development of smart cities.« less

Evaluation of daily time spent in transportation and traffic-influenced microenvironments by urban Canadians.

PubMed

Matz, Carlyn J; Stieb, David M; Egyed, Marika; Brion, Orly; Johnson, Markey

2018-01-01

Exposure to traffic and traffic-related air pollution is associated with a wide array of health effects. Time spent in a vehicle, in active transportation, along roadsides, and in close proximity to traffic can substantially contribute to daily exposure to air pollutants. For this study, we evaluated daily time spent in transportation and traffic-influenced microenvironments by urban Canadians using the Canadian Human Activity Pattern Survey (CHAPS) 2 results. Approximately 4-7% of daily time was spent in on- or near-road locations, mainly associated with being in a vehicle and smaller contributions from active transportation. Indoor microenvironments can be impacted by traffic emissions, especially when located near major roadways. Over 60% of the target population reported living within one block of a roadway with moderate to heavy traffic, which was variable with income level and city, and confirmed based on elevated NO 2 exposure estimated using land use regression. Furthermore, over 55% of the target population ≤ 18 years reported attending a school or daycare in close proximity to moderate to heavy traffic, and little variation was observed based on income or city. The results underline the importance of traffic emissions as a major source of exposure in Canadian urban centers, given the time spent in traffic-influenced microenvironments.

Minimal-delay traffic grooming for WDM star networks

NASA Astrophysics Data System (ADS)

Choi, Hongsik; Garg, Nikhil; Choi, Hyeong-Ah

2003-10-01

All-optical networks face the challenge of reducing slower opto-electronic conversions by managing assignment of traffic streams to wavelengths in an intelligent manner, while at the same time utilizing bandwidth resources to the maximum. This challenge becomes harder in networks closer to the end users that have insufficient data to saturate single wavelengths as well as traffic streams outnumbering the usable wavelengths, resulting in traffic grooming which requires costly traffic analysis at access nodes. We study the problem of traffic grooming that reduces the need to analyze traffic, for a class of network architecture most used by Metropolitan Area Networks; the star network. The problem being NP-complete, we provide an efficient twice-optimal-bound greedy heuristic for the same, that can be used to intelligently groom traffic at the LANs to reduce latency at the access nodes. Simulation results show that our greedy heuristic achieves a near-optimal solution.

Development of a Healthy Urban Route Planner for cyclists and pedestrians in Amsterdam

NASA Astrophysics Data System (ADS)

van der Molen, Michiel; Ligtenberg, Arend; Vreugdenhil, Corne; Steeneveld, Gert-Jan

2017-04-01

Cities are hotspots of air pollution and heat stress, the exposure to which results in nuisance, health risks, cost of medication, reduced labour productivity and sick leave for citizens. Yet the air pollution and heat stress are spatially and temporally unevenly distributed over the city, depending on pollutant emissions, street design and atmospheric turbulent mixing and radiation. This spatiotemporal variation allows pedestrians and bikers to choose alternative routes to minimize their exposure, if the distribution is known. In this project, we develop a route planner for bicyclists and pedestrians for Amsterdam (NL), that proposes routes and departure times based on model simulations of weather and air quality. We use the WRF-Chem atmosphere and air quality model at unprecedented grid spacing of 100-m (Ronda et al, 2015, Super et al, 2016), with an underlying urban canopy model and NOx and PM10 emissions. The emissions by traffic are calculated based on observed traffic intensities and emission factors. An urban land use map will characterize urban density and street configuration to estimate urban heat storage (Attema et al, 2015). WRF-Chem runs will be issued daily for a lead time of 48 hours, resulting in forecast maps of temperature and pollutant concentrations that will be uniquely expressed in a metric that combines both threats. The hourly fields of this metric are provided to the route planner based on the open source routing library pgRouting to identify the more healthy routes on the route network of Amsterdam. The objectives of the healthy urban route planner are to raise awareness of heat and air quality issues in Amsterdam, to provide an innovative adaptation tool for citizens and tourists, to locate the most important bottlenecks in (the exposure to) air pollution and heat stress, and ultimately to test the readiness of the travellers to use the information and adapt the route. We expect to particularly target a group of lung- and cardiovascular patients, and elderly people. In the future the planner will be expanded with pollen information and possibly with real-time traffic information.

What Have we Learned about Intelligent Transportation Systems?

DOT National Transportation Integrated Search

1980-01-01

The Traffic Planning manual is a reference of basic traffic enginnering techniques and their potential for improving traffic flow and traffic safety of urban arterial streets and highways. The manual identifies the traffic engineering measure appropr...

Appalachian versus non-Appalachian US traffic fatalities, 2008-2010

PubMed Central

Zhu, Motao; Zhao, Songzhu; Gurka, Kelly K.; Kandati, Sahiti; Coben, Jeffrey H.

2013-01-01

Purpose Though myriad health disparities exist in Appalachia, limited research has examined traffic fatalities in the region. This study compared traffic-fatality rates in Appalachia and the non-Appalachian US. Methods Fatality Analysis Reporting System and Census data from 2008-2010 were used to calculate traffic-fatality rates. Poisson models were used to estimate unadjusted (RR) and adjusted rate ratios (aRR), controlling for age, sex, and county-specific population density levels. Results: The Appalachian traffic-fatality rate was 45% (95% CI: 1.42, 1.47) higher than the non-Appalachian rate. Though only 29% of fatalities occur in rural counties in non-Appalachia versus 48% in Appalachia, rates in rural counties were similar (RR=0.97; 95% CI: 0.95, 1.00). However, the rate for urban, Appalachian counties was 42% (95% CI: 1.38, 1.45) higher than among urban, non-Appalachian counties. Appalachian rates were higher for passenger-vehicle drivers, motorcyclists, and all-terrain-vehicle riders, regardless of rurality, as well as for passenger-vehicle passengers overall and for urban counties. Conversely, Appalachia experienced lower rates among pedestrians and bicyclists, regardless of rurality. Conclusions Disparities in traffic fatality rates exist in Appalachia. Though elevated rates are partially explained by the proportion of residents living in rural settings, overall rates in urban Appalachia were consistently higher than in urban non-Appalachia. PMID:23619016

a Numerical Investigation of the Jamming Transition in Traffic Flow on Diluted Planar Networks

NASA Astrophysics Data System (ADS)

Achler, Gabriele; Barra, Adriano

In order to develop a toy model for car's traffic in cities, in this paper we analyze, by means of numerical simulations, the transition among fluid regimes and a congested jammed phase of the flow of kinetically constrained hard spheres in planar random networks similar to urban roads. In order to explore as timescales as possible, at a microscopic level we implement an event driven dynamics as the infinite time limit of a class of already existing model (Follow the Leader) on an Erdos-Renyi two-dimensional graph, the crossroads being accounted by standard Kirchoff density conservations. We define a dynamical order parameter as the ratio among the moving spheres versus the total number and by varying two control parameters (density of the spheres and coordination number of the network) we study the phase transition. At a mesoscopic level it respects an, again suitable, adapted version of the Lighthill-Whitham model, which belongs to the fluid-dynamical approach to the problem. At a macroscopic level, the model seems to display a continuous transition from a fluid phase to a jammed phase when varying the density of the spheres (the amount of cars in a city-like scenario) and a discontinuous jump when varying the connectivity of the underlying network.

Michigan urban trunkline segments safety performance functions (SPFs) : final report.

DOT National Transportation Integrated Search

2016-07-01

This study involves the development of safety performance functions (SPFs) for urban and suburban trunkline segments in the : state of Michigan. Extensive databases were developed through the integration of traffic crash information, traffic volumes,...

Speed harmonization and peak-period shoulder use to manage urban freeway congestion.

DOT National Transportation Integrated Search

2009-10-01

Traffic congestion is an increasing problem in the nations urban areas, leading to personal inconvenience, : increased pollution, hampered economic productivity, and reduced quality of life. While traffic congestion tends : to continuously increas...

Sonification of network traffic flow for monitoring and situational awareness

PubMed Central

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543

Sonification of network traffic flow for monitoring and situational awareness.

PubMed

Debashi, Mohamed; Vickers, Paul

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.

Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

PubMed

Ding, Rui; Ujang, Norsidah; Hamid, Hussain Bin; Wu, Jianjun

2015-01-01

Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

Improving pedestrian facilities in congested urban areas: a case study of Chennai city

NASA Astrophysics Data System (ADS)

Subramanyam, B.; Prasanna Kumar, R.

2017-07-01

Traffic congestion and lack of public pedestrian space are some problems faced by most urban metropolises. Conventionally walking has been a mode of transportation in Indian cities. The percentage of pedestrians may vary from 16 to 57 depending upon the city. Encounters between vehicular traffic and pedestrian traffic are at its rise currently. Rapid industrialization and urbanization in India has resulted in neglecting of pedestrian facilities. Consequently pedestrian are at greater risk for their safety more especially in the commercial zones of large cities. A change in perspective spotlight will create a sense of awareness that the pedestrian traffic is also vital as the vehicular traffic. Soothing the traffic would moderately cut the driving expediency but the pedestrians will get a much safer and peaceful route to their terminuses. Safety and comfort are the two pans of a balance while considering the pedestrian traffic. Considering these aspects, this study deals a study in improving pedestrian facilities by analysing the existing skeleton of the selected locations. The adequacy of facility is checked based on IRC latest guidelines and counteractive measures are postulated.

The impact of traffic-flow patterns on air quality in urban street canyons.

PubMed

Thaker, Prashant; Gokhale, Sharad

2016-01-01

We investigated the effect of different urban traffic-flow patterns on pollutant dispersion in different winds in a real asymmetric street canyon. Free-flow traffic causes more turbulence in the canyon facilitating more dispersion and a reduction in pedestrian level concentration. The comparison of with and without a vehicle-induced-turbulence revealed that when winds were perpendicular, the free-flow traffic reduced the concentration by 73% on the windward side with a minor increase of 17% on the leeward side, whereas for parallel winds, it reduced the concentration by 51% and 29%. The congested-flow traffic increased the concentrations on the leeward side by 47% when winds were perpendicular posing a higher risk to health, whereas reduced it by 17-42% for parallel winds. The urban air quality and public health can, therefore, be improved by improving the traffic-flow patterns in street canyons as vehicle-induced turbulence has been shown to contribute significantly to dispersion. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimation of carbon dioxide emissions per urban center link unit using data collected by the Advanced Traffic Information System in Daejeon, Korea

NASA Astrophysics Data System (ADS)

Ryu, B. Y.; Jung, H. J.; Bae, S. H.; Choi, C. U.

2013-12-01

CO2 emissions on roads in urban centers substantially affect global warming. It is important to quantify CO2 emissions in terms of the link unit in order to reduce these emissions on the roads. Therefore, in this study, we utilized real-time traffic data and attempted to develop a methodology for estimating CO2 emissions per link unit. Because of the recent development of the vehicle-to-infrastructure (V2I) communication technology, data from probe vehicles (PVs) can be collected and speed per link unit can be calculated. Among the existing emission calculation methodologies, mesoscale modeling, which is a representative modeling measurement technique, requires speed and traffic data per link unit. As it is not feasible to install fixed detectors at every link for traffic data collection, in this study, we developed a model for traffic volume estimation by utilizing the number of PVs that can be additionally collected when the PV data are collected. Multiple linear regression and an artificial neural network (ANN) were used for estimating the traffic volume. The independent variables and input data for each model are the number of PVs, travel time index (TTI), the number of lanes, and time slots. The result from the traffic volume estimate model shows that the mean absolute percentage error (MAPE) of the ANN is 18.67%, thus proving that it is more effective. The ANN-based traffic volume estimation served as the basis for the calculation of emissions per link unit. The daily average emissions for Daejeon, where this study was based, were 2210.19 ton/day. By vehicle type, passenger cars accounted for 71.28% of the total emissions. By road, Gyeryongro emitted 125.48 ton/day, accounting for 5.68% of the total emission, the highest percentage of all roads. In terms of emissions per kilometer, Hanbatdaero had the highest emission volume, with 7.26 ton/day/km on average. This study proves that real-time traffic data allow an emissions estimate in terms of the link unit. Furthermore, an analysis of CO2 emissions can support traffic management to make decisions related to the reduction of carbon emissions.

Impact of vehicular networks on emergency medical services in urban areas.

PubMed

Lee, Chun-Liang; Huang, Chung-Yuan; Hsiao, Tzu-Chien; Wu, Chun-Yen; Chen, Yaw-Chung; Wang, I-Cheng

2014-10-31

The speed with which emergency personnel can provide emergency treatment is crucial to reducing death and disability among acute and critically ill patients. Unfortunately, the rapid development of cities and increased numbers of vehicles are preventing emergency vehicles from easily reaching locations where they are needed. A significant number of researchers are experimenting with vehicular networks to address this issue, but in most studies the focus has been on communication technologies and protocols, with few efforts to assess how network applications actually support emergency medical care. Our motivation was to search the literature for suggested methods for assisting emergency vehicles, and to use simulations to evaluate them. Our results and evidence-based studies were cross-referenced to assess each method in terms of cumulative survival ratio (CSR) gains for acute and critically ill patients. Simulation results indicate that traffic light preemption resulted in significant CSR increases of between 32.4% and 90.2%. Route guidance was found to increase CSRs from 14.1% to 57.8%, while path clearing increased CSRs by 15.5% or less. It is our hope that this data will support the efforts of emergency medical technicians, traffic managers, and policy makers.

Impact of Vehicular Networks on Emergency Medical Services in Urban Areas

PubMed Central

Lee, Chun-Liang; Huang, Chung-Yuan; Hsiao, Tzu-Chien; Wu, Chun-Yen; Chen, Yaw-Chung; Wang, I.-Cheng

2014-01-01

The speed with which emergency personnel can provide emergency treatment is crucial to reducing death and disability among acute and critically ill patients. Unfortunately, the rapid development of cities and increased numbers of vehicles are preventing emergency vehicles from easily reaching locations where they are needed. A significant number of researchers are experimenting with vehicular networks to address this issue, but in most studies the focus has been on communication technologies and protocols, with few efforts to assess how network applications actually support emergency medical care. Our motivation was to search the literature for suggested methods for assisting emergency vehicles, and to use simulations to evaluate them. Our results and evidence-based studies were cross-referenced to assess each method in terms of cumulative survival ratio (CSR) gains for acute and critically ill patients. Simulation results indicate that traffic light preemption resulted in significant CSR increases of between 32.4% and 90.2%. Route guidance was found to increase CSRs from 14.1% to 57.8%, while path clearing increased CSRs by 15.5% or less. It is our hope that this data will support the efforts of emergency medical technicians, traffic managers, and policy makers. PMID:25365059

Objects Grouping for Segmentation of Roads Network in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

Maboudi, M.; Amini, J.; Hahn, M.

2016-06-01

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors - as the main source of large scale mapping applications - was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of "Object-based Image Analysis (OBIA)" as an alternative to pixel-based image analysis methods. Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

Air Pollution Monitoring and Mining Based on Sensor Grid in London

PubMed Central

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-01-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895

Air Pollution Monitoring and Mining Based on Sensor Grid in London.

PubMed

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-06-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.

Road traffic impact on urban water quality: a step towards integrated traffic, air and stormwater modelling.

PubMed

Fallah Shorshani, Masoud; Bonhomme, Céline; Petrucci, Guido; André, Michel; Seigneur, Christian

2014-04-01

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.

Prediction algorithms for urban traffic control

DOT National Transportation Integrated Search

1979-02-01

The objectives of this study are to 1) review and assess the state-of-the-art of prediction algorithms for urban traffic control in terms of their accuracy and application, and 2) determine the prediction accuracy obtainable by examining the performa...

Pedestrian Friendly Traffic Signal Control.

DOT National Transportation Integrated Search

2016-01-01

This project continues research aimed at real-time detection and use of pedestrian : traffic flow information to enhance adaptive traffic signal control in urban areas : where pedestrian traffic is substantial and must be given appropriate attention ...

Residential Exposure to Urban Traffic Is Associated with Increased Carotid Intima-Media Thickness in Children

PubMed Central

Armijos, Rodrigo X.; Weigel, M. Margaret; Myers, Orrin B.; Li, Wen-Whai; Racines, Marcia; Berwick, Marianne

2015-01-01

Chronic exposure to urban traffic pollution is documented to promote atherosclerosis in adults but little is known about its potential effects in children. Our study examined the association of long-term exposure to traffic with carotid intima-media thickness (cIMT) in 287 healthy children. Residential proximity and distance-weighted traffic density (DWTD) were used as proximity markers for traffic-related air pollution exposure. The multivariable analyses revealed that children residing <100 meters from the nearest heavily trafficked road had cIMT mean and maximum measurements that were increased by 15% and 11% compared to those living ≥ 200 meters away (P = 0.0001). Similar increases in cIMT were identified for children in the highest versus lowest DWTD tertile. Children who resided 100–199 meters from traffic or in the middle DWTD tertile also exhibited increased cIMT but these differences were not statistically significant. No statistically significant differences were identified between residential distance to traffic or DWTD and systemic inflammation indicators (CRP, IL-6). The study results suggest that exposure to urban traffic promotes arterial remodeling in children. This finding is important since even small increases in cIMT over time can potentially lead to earlier progression to atherosclerosis. It is also important because traffic-related pollution is potentially modifiable. PMID:25685160

Residential exposure to urban traffic is associated with increased carotid intima-media thickness in children.

PubMed

Armijos, Rodrigo X; Weigel, M Margaret; Myers, Orrin B; Li, Wen-Whai; Racines, Marcia; Berwick, Marianne

2015-01-01

Chronic exposure to urban traffic pollution is documented to promote atherosclerosis in adults but little is known about its potential effects in children. Our study examined the association of long-term exposure to traffic with carotid intima-media thickness (cIMT) in 287 healthy children. Residential proximity and distance-weighted traffic density (DWTD) were used as proximity markers for traffic-related air pollution exposure. The multivariable analyses revealed that children residing <100 meters from the nearest heavily trafficked road had cIMT mean and maximum measurements that were increased by 15% and 11% compared to those living ≥ 200 meters away (P = 0.0001). Similar increases in cIMT were identified for children in the highest versus lowest DWTD tertile. Children who resided 100-199 meters from traffic or in the middle DWTD tertile also exhibited increased cIMT but these differences were not statistically significant. No statistically significant differences were identified between residential distance to traffic or DWTD and systemic inflammation indicators (CRP, IL-6). The study results suggest that exposure to urban traffic promotes arterial remodeling in children. This finding is important since even small increases in cIMT over time can potentially lead to earlier progression to atherosclerosis. It is also important because traffic-related pollution is potentially modifiable.

Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic, Validation and Extensions.

PubMed

Zambrano-Martinez, Jorge Luis; Calafate, Carlos T; Soler, David; Cano, Juan-Carlos

2017-12-15

Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels.

Fast packet switching algorithms for dynamic resource control over ATM networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsang, R.P.; Keattihananant, P.; Chang, T.

1996-12-01

Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less

Cluster categorization of urban roads to optimize their noise monitoring.

PubMed

Zambon, G; Benocci, R; Brambilla, G

2016-01-01

Road traffic in urban areas is recognized to be associated with urban mobility and public health, and it is often the main source of noise pollution. Lately, noise maps have been considered a powerful tool to estimate the population exposure to environmental noise, but they need to be validated by measured noise data. The project Dynamic Acoustic Mapping (DYNAMAP), co-funded in the framework of the LIFE 2013 program, is aimed to develop a statistically based method to optimize the choice and the number of monitoring sites and to automate the noise mapping update using the data retrieved from a low-cost monitoring network. Indeed, the first objective should improve the spatial sampling based on the legislative road classification, as this classification is mainly based on the geometrical characteristics of the road, rather than its noise emission. The present paper describes the statistical approach of the methodology under development and the results of its preliminary application to a limited sample of roads in the city of Milan. The resulting categorization of roads, based on clustering the 24-h hourly L Aeqh, looks promising to optimize the spatial sampling of noise monitoring toward a description of the noise pollution due to complex urban road networks more efficient than that based on the legislative road classification.

Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: A case study of an urban storm in Beijing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lai, Wen-li; Wang, Hong-rui; Wang, Cheng

Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters have occurred almost annually in the urban area of Beijing, the capital of China. Based on a self-organizing map (SOM) artificial neural network (ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product (GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANN is suitable for automatically and quantitatively assessing risks associated withmore » waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors, producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. As a result, the points that were assigned risk grades of IV or V were located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng.« less

Waterlogging risk assessment based on self-organizing map (SOM) artificial neural networks: A case study of an urban storm in Beijing

DOE PAGES

Lai, Wen-li; Wang, Hong-rui; Wang, Cheng; ...

2017-05-05

Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters have occurred almost annually in the urban area of Beijing, the capital of China. Based on a self-organizing map (SOM) artificial neural network (ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product (GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANN is suitable for automatically and quantitatively assessing risks associated withmore » waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors, producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. As a result, the points that were assigned risk grades of IV or V were located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng.« less

Minnesota urban partnership agreement national evaluation : traffic system data test plan.

DOT National Transportation Integrated Search

2009-11-17

This report presents the traffic system data test plan for the Minnesota Urban Partnership Agreement (UPA) under the United States Department of Transportation (U.S. DOT) UPA Program. The Minnesota UPA projects focus on reducing congestion by employi...

Traffic Management for Satellite-ATM Networks

NASA Technical Reports Server (NTRS)

Goyal, Rohit; Jain, Raj; Fahmy, Sonia; Vandalore, Bobby; Goyal, Mukul

1998-01-01

Various issues associated with "Traffic Management for Satellite-ATM Networks" are presented in viewgraph form. Specific topics include: 1) Traffic management issues for TCP/IP based data services over satellite-ATM networks; 2) Design issues for TCP/IP over ATM; 3) Optimization of the performance of TCP/IP over ATM for long delay networks; and 4) Evaluation of ATM service categories for TCP/IP traffic.

Nonuniform traffic spots (NUTS) in multistage interconnection networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lang, T.; Kurisaki, L.

1990-09-01

The performance of multistage interconnection networks for multiprocessors is degraded when the traffic pattern produces nonuniform congestion in the blocking switches, that is, when there exist nonuniform traffic spots. For some specific patterns the authors evaluate this degradation in performance and propose modifications to the network organization and operation to reduce the degradation. Successful modifications are the use of diverting switches and the extension of the network with additional links. The use of these modifications makes the network more effective for a larger variety of traffic patterns. The authors also consider the case in which the network carries the superpositionmore » of two types of traffic. One type is the high throughput data and instruction traffic, while the other consists of control and I/O packets which are of low throughput but have severe real-time constraints. The authors conclude that diverting switches and networks with additional links are also suitable for assuring low latency for the real-time traffic, especially when using the displacing mode.« less

Design guidelines for raised and traversable medians in urban areas.

DOT National Transportation Integrated Search

1983-01-01

Major urban and suburban streets must provide a high level of service for through traffic as well as access to abutting properties. To an extent, the provisions of traffic service and the accommodation of access needs are conflicting functions that a...

San Francisco urban partnership agreement, national evaluation : traffic system data test plan.

DOT National Transportation Integrated Search

2011-06-01

This report presents the test plan for collecting and analyzing traffic system data for the San Francisco Urban Partnership Agreement (UPA) under the United States Department of Transportation (U.S. DOT) UPA Program. The San Francisco UPA projects fo...

Improving safety in high-speed work zones : a Super 70 study : [summary].

DOT National Transportation Integrated Search

2011-08-01

Highway work zones, particularly those on urban high-speed roads, require special attention and adequate traffic management to reduce the adverse impact of altered geometry and traffic that differ from typical conditions. Super 70 was an urban recons...

Effects of the amount of feedback information on urban traffic with advanced traveler information system

NASA Astrophysics Data System (ADS)

Chen, Jie; Li, Ming; Jiang, Rui; Hu, Mao-Bin

2017-09-01

In a real traffic system, information feedback has already been proven to be a good way to alleviate traffic jams. However, due to the massive traffic information of real system, the procedure is often difficult in practice. In this paper, we study the effects of the amount of feedback information based on a cellular automaton model of urban traffic. What we found most interesting is that when providing the traffic information of a part of a road to travelers, the performance of the system will be better than that providing the road's full traffic information. From this basis, we can provide more effective routing strategy with less information. We demonstrate that only providing the traffic information of about first half road from upstream to downstream can maximize the traffic capacity of the system. We also give an explanation for these phenomena by studying the distribution pattern of vehicles and the detailed turning environment at the intersections. The effects of the traffic light period are also provided.

Urban sprawl as a risk factor in motor vehicle occupant and pedestrian fatalities.

PubMed

Ewing, Reid; Schieber, Richard A; Zegeer, Charles V

2003-09-01

We sought to determine the association between urban sprawl and traffic fatalities. We created a sprawl index by applying principal components analysis to data for 448 US counties in the largest 101 metropolitan areas. Regression analysis was used to determine associations between the index and traffic fatalities. For every 1% increase in the index (i.e., more compact, less sprawl), all-mode traffic fatality rates fell by 1.49% (P <.001) and pedestrian fatality rates fell by 1.47% to 3.56%, after adjustment for pedestrian exposure (P <.001). Urban sprawl was directly related to traffic fatalities and pedestrian fatalities. Subsequent studies should investigate relationships at a finer geographic scale and should strive to improve on the measure of exposure used to adjust pedestrian fatality rates.

A quantitative estimation of the exhaust, abrasion and resuspension components of particulate traffic emissions using electron microscopy

NASA Astrophysics Data System (ADS)

Weinbruch, Stephan; Worringen, Annette; Ebert, Martin; Scheuvens, Dirk; Kandler, Konrad; Pfeffer, Ulrich; Bruckmann, Peter

2014-12-01

The contribution of the three traffic-related components exhaust, abrasion, and resuspension to kerbside and urban background PM10 and PM1 levels was quantified based on the analysis of individual particles by scanning electron microscopy. A total of 160 samples was collected on 38 days between February and September 2009 at a kerbside and an urban background station in the urban/industrial Ruhr area (Germany). Based on size, morphology, chemical composition and stability under electron bombardment, the 111,003 particles studied in detail were classified into the following 14 particle classes: traffic/exhaust, traffic/abrasion, traffic/resuspension, carbonaceous/organic, industry/metallurgy, industry/power plants, secondary particles, (aged) sea salt, silicates, Ca sulfates, carbonates, Fe oxides/hydroxides, biological particles, and other particles. The traffic/exhaust component consists predominantly of externally mixed soot particles and soot internally mixed with secondary particles. The traffic/abrasion component contains all particles with characteristic tracer elements (Fe, Cu, Ba, Sb, Zn) for brake and tire abrasion. The traffic/resuspension component is defined by the mixing state and comprises all internally mixed particles with a high proportion of silicates or Fe oxides/hydroxides which contain soot or abrasion particles as minor constituent. In addition, silicates and Fe oxides/hydroxides internally mixed with chlorine and sulphur containing particles were also assigned to the traffic/resuspension component. The total contribution of traffic to PM10 was found to be 27% at the urban background station and 48% at the kerbside station, the corresponding values for PM1 are 15% and 39%. These values lie within the range reported in previous literature. The relative share of the different traffic components for PM10 at the kerbside station was 27% exhaust, 15% abrasion, and 58% resuspension (38%, 8%, 54% for PM1). For the urban background, the following relative shares were obtained for PM10: 22% exhaust, 22% abrasion and 56% resuspension (40%, 27%, 33% for PM1). Compared to previous publications we have observed a significantly lower portion of exhaust particles and a significantly higher portion of resuspension particles. The high abundance of resuspension particles underlines their significance for the observed adverse health effects of traffic emissions and for mitigation measures.

Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network.

PubMed

Al-Mayouf, Yusor Rafid Bahar; Ismail, Mahamod; Abdullah, Nor Fadzilah; Wahab, Ainuddin Wahid Abdul; Mahdi, Omar Adil; Khan, Suleman; Choo, Kim-Kwang Raymond

2016-01-01

Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destination node via multi-hop routing techniques. An appropriate, efficient, and stable routing algorithm must be developed for various VANET applications to address the issues of dynamic topology and intermittent connectivity. Therefore, this paper proposes a novel routing algorithm called efficient and stable routing algorithm based on user mobility and node density (ESRA-MD). The proposed algorithm can adapt to significant changes that may occur in the urban vehicular environment. This algorithm works by selecting an optimal route on the basis of hop count and link duration for delivering data from source to destination, thereby satisfying various quality of service considerations. The validity of the proposed algorithm is investigated by its comparison with ARP-QD protocol, which works on the mechanism of optimal route finding in VANETs in urban environments. Simulation results reveal that the proposed ESRA-MD algorithm shows remarkable improvement in terms of delivery ratio, delivery delay, and communication overhead.

Pedestrian friendly traffic signal control : final research report.

DOT National Transportation Integrated Search

2016-01-01

This project continues research aimed at real-time detection and use of pedestrian : traffic flow information to enhance adaptive traffic signal control in urban areas : where pedestrian traffic is substantial and must be given appropriate attention ...

An Anomalous Noise Events Detector for Dynamic Road Traffic Noise Mapping in Real-Life Urban and Suburban Environments

PubMed Central

2017-01-01

One of the main aspects affecting the quality of life of people living in urban and suburban areas is their continued exposure to high Road Traffic Noise (RTN) levels. Until now, noise measurements in cities have been performed by professionals, recording data in certain locations to build a noise map afterwards. However, the deployment of Wireless Acoustic Sensor Networks (WASN) has enabled automatic noise mapping in smart cities. In order to obtain a reliable picture of the RTN levels affecting citizens, Anomalous Noise Events (ANE) unrelated to road traffic should be removed from the noise map computation. To this aim, this paper introduces an Anomalous Noise Event Detector (ANED) designed to differentiate between RTN and ANE in real time within a predefined interval running on the distributed low-cost acoustic sensors of a WASN. The proposed ANED follows a two-class audio event detection and classification approach, instead of multi-class or one-class classification schemes, taking advantage of the collection of representative acoustic data in real-life environments. The experiments conducted within the DYNAMAP project, implemented on ARM-based acoustic sensors, show the feasibility of the proposal both in terms of computational cost and classification performance using standard Mel cepstral coefficients and Gaussian Mixture Models (GMM). The two-class GMM core classifier relatively improves the baseline universal GMM one-class classifier F1 measure by 18.7% and 31.8% for suburban and urban environments, respectively, within the 1-s integration interval. Nevertheless, according to the results, the classification performance of the current ANED implementation still has room for improvement. PMID:29023397

Top-down quantification of NOx emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Kerschbaumer, Andreas; Lauer, Axel; Lupascu, Aurelia; von Schneidemesser, Erika; Butler, Tim M.

2018-06-01

With NO2 limit values being frequently exceeded in European cities, complying with the European air quality regulations still poses a problem for many cities. Traffic is typically a major source of NOx emissions in urban areas. High-resolution chemistry transport modelling can help to assess the impact of high urban NOx emissions on air quality inside and outside of urban areas. However, many modelling studies report an underestimation of modelled NOx and NO2 compared with observations. Part of this model bias has been attributed to an underestimation of NOx emissions, particularly in urban areas. This is consistent with recent measurement studies quantifying underestimations of urban NOx emissions by current emission inventories, identifying the largest discrepancies when the contribution of traffic NOx emissions is high. This study applies a high-resolution chemistry transport model in combination with ambient measurements in order to assess the potential underestimation of traffic NOx emissions in a frequently used emission inventory. The emission inventory is based on officially reported values and the Berlin-Brandenburg area in Germany is used as a case study. The WRF-Chem model is used at a 3 km × 3 km horizontal resolution, simulating the whole year of 2014. The emission data are downscaled from an original resolution of ca. 7 km × 7 km to a resolution of 1 km × 1 km. An in-depth model evaluation including spectral decomposition of observed and modelled time series and error apportionment suggests that an underestimation in traffic emissions is likely one of the main causes of the bias in modelled NO2 concentrations in the urban background, where NO2 concentrations are underestimated by ca. 8 µg m-3 (-30 %) on average over the whole year. Furthermore, a diurnal cycle of the bias in modelled NO2 suggests that a more realistic treatment of the diurnal cycle of traffic emissions might be needed. Model problems in simulating the correct mixing in the urban planetary boundary layer probably play an important role in contributing to the model bias, particularly in summer. Also taking into account this and other possible sources of model bias, a correction factor for traffic NOx emissions of ca. 3 is estimated for weekday daytime traffic emissions in the core urban area, which corresponds to an overall underestimation of traffic NOx emissions in the core urban area of ca. 50 %. Sensitivity simulations for the months of January and July using the calculated correction factor show that the weekday model bias can be improved from -8.8 µg m-3 (-26 %) to -5.4 µg m-3 (-16 %) in January on average in the urban background, and -10.3 µg m-3 (-46 %) to -7.6 µg m-3 (-34 %) in July. In addition, the negative bias of weekday NO2 concentrations downwind of the city in the rural and suburban background can be reduced from -3.4 µg m-3 (-12 %) to -1.2 µg m-3 (-4 %) in January and from -3.0 µg m-3 (-22 %) to -1.9 µg m-3 (-14 %) in July. The results and their consistency with findings from other studies suggest that more research is needed in order to more accurately understand the spatial and temporal variability in real-world NOx emissions from traffic, and apply this understanding to the inventories used in high-resolution chemical transport models.

Environmental and biological monitoring of benzene in traffic policemen, police drivers and rural outdoor male workers.

PubMed

Manuela, Ciarrocca; Francesco, Tomei; Tiziana, Caciari; Assunta, Capozzella; Lara, Scimitto; Nadia, Nardone; Giorgia, Andreozzi; Barbara, Scala; Maria, Fiaschetti; Carlotta, Cetica; Valeria, Di Giorgio; Pia, Schifano Maria; Gianfranco, Tomei; Angela, Sancini

2012-05-01

To evaluate exposure to benzene in urban and rural areas, an investigation into personal exposure to benzene in traffic policemen, police drivers and rural (roadmen) male outdoor workers was carried out. Personal samples and data acquired using fixed monitoring stations located in different areas of the city were used to measure personal exposure to benzene in 62 non-smoker traffic policemen, 22 police drivers and 57 roadmen. Blood benzene, urinary trans-trans muconic acid (t,t-MA) and S-phenyl-mercapturic acid (S-PMA) were measured at the end of work shift in 62 non-smoker traffic policemen, 22 police drivers and 57 roadmen and 34 smoker traffic policemen, 21 police drivers and 53 roadmen. Exposure to benzene was similar among non-smoker traffic policemen and police drivers and higher among non-smoker urban workers compared to rural workers. Blood benzene, t,t-MA and S-PMA were similar among non-smoker traffic policemen and police drivers; blood benzene and t,t-MA were significantly higher in non-smoker urban workers compared to rural workers. Significant increases in t,t-MA were found in smokers vs. non-smokers. In non-smoker urban workers airborne benzene and blood benzene, and t,t-MA and S-PMA were significantly correlated. This study gives an evaluation of the exposure to benzene in an urban area, comparing people working in the street or in cars, to people working in a rural area. Benzene is a certain carcinogen for humans. The results we showed should lead to more in-depth studies about the effects on health of these categories of workers.

Methods to improve traffic flow and noise exposure estimation on minor roads.

PubMed

Morley, David W; Gulliver, John

2016-09-01

Address-level estimates of exposure to road traffic noise for epidemiological studies are dependent on obtaining data on annual average daily traffic (AADT) flows that is both accurate and with good geographical coverage. National agencies often have reliable traffic count data for major roads, but for residential areas served by minor roads, especially at national scale, such information is often not available or incomplete. Here we present a method to predict AADT at the national scale for minor roads, using a routing algorithm within a geographical information system (GIS) to rank roads by importance based on simulated journeys through the road network. From a training set of known minor road AADT, routing importance is used to predict AADT on all UK minor roads in a regression model along with the road class, urban or rural location and AADT on the nearest major road. Validation with both independent traffic counts and noise measurements show that this method gives a considerable improvement in noise prediction capability when compared to models that do not give adequate consideration to minor road variability (Spearman's rho. increases from 0.46 to 0.72). This has significance for epidemiological cohort studies attempting to link noise exposure to adverse health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Optimization Model for the Selection of Bus-Only Lanes in a City.

PubMed

Chen, Qun

2015-01-01

The planning of urban bus-only lane networks is an important measure to improve bus service and bus priority. To determine the effective arrangement of bus-only lanes, a bi-level programming model for urban bus lane layout is developed in this study that considers accessibility and budget constraints. The goal of the upper-level model is to minimize the total travel time, and the lower-level model is a capacity-constrained traffic assignment model that describes the passenger flow assignment on bus lines, in which the priority sequence of the transfer times is reflected in the passengers' route-choice behaviors. Using the proposed bi-level programming model, optimal bus lines are selected from a set of candidate bus lines; thus, the corresponding bus lane network on which the selected bus lines run is determined. The solution method using a genetic algorithm in the bi-level programming model is developed, and two numerical examples are investigated to demonstrate the efficacy of the proposed model.

Visualization of simulated urban spaces: inferring parameterized generation of streets, parcels, and aerial imagery.

PubMed

Vanegas, Carlos A; Aliaga, Daniel G; Benes, Bedrich; Waddell, Paul

2009-01-01

Urban simulation models and their visualization are used to help regional planning agencies evaluate alternative transportation investments, land use regulations, and environmental protection policies. Typical urban simulations provide spatially distributed data about number of inhabitants, land prices, traffic, and other variables. In this article, we build on a synergy of urban simulation, urban visualization, and computer graphics to automatically infer an urban layout for any time step of the simulation sequence. In addition to standard visualization tools, our method gathers data of the original street network, parcels, and aerial imagery and uses the available simulation results to infer changes to the original urban layout and produce a new and plausible layout for the simulation results. In contrast with previous work, our approach automatically updates the layout based on changes in the simulation data and thus can scale to a large simulation over many years. The method in this article offers a substantial step forward in building integrated visualization and behavioral simulation systems for use in community visioning, planning, and policy analysis. We demonstrate our method on several real cases using a 200 GB database for a 16,300 km2 area surrounding Seattle.

An efficient routing strategy for traffic dynamics on two-layer complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Wang, Huiling; Zhang, Zhuxi; Zhang, Yi; Duan, Congwen; Qi, Zhaohui; Liu, Yu

2018-05-01

In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.

Improving the roadside environment through integrating air quality and traffic-related data.

DOT National Transportation Integrated Search

2016-12-01

Urban arterial corridors are landscapes that give rise to short and long-term : exposures to transportation-related pollution. With high traffic volumes, congestion, and : a wide mix of road users and land uses at the road edge, urban arterial enviro...

Bicyclists' Uptake of Traffic-Related Air Pollution: Effects of the Urban Transportation System

DOT National Transportation Integrated Search

2014-10-27

While bicyclists and other active travelers obtain health benefits from increased physical activity, they also risk uptake of traffic-related air pollution. But pollution uptake by urban bicyclists is not well understood due to a lack of direct measu...

Wild growing mushrooms for the Edible City? Cadmium and lead content in edible mushrooms harvested within the urban agglomeration of Berlin, Germany.

PubMed

Schlecht, Martin Thomas; Säumel, Ina

2015-09-01

Health effects by consuming urban garden products are discussed controversially due to high urban pollution loads. We sampled wild edible mushrooms of different habitats and commercial mushroom cultivars exposed to high traffic areas within Berlin, Germany. We determined the content of cadmium and lead in the fruiting bodies and analysed how the local setting shaped the concentration patterns. EU standards for cultivated mushrooms were exceeded by 86% of the wild mushroom samples for lead and by 54% for cadmium but not by mushroom cultures. We revealed significant differences in trace metal content depending on species, trophic status, habitat and local traffic burden. Higher overall traffic burden increased trace metal content in the biomass of wild mushrooms, whereas cultivated mushrooms exposed to inner city high traffic areas had significantly lower trace metal contents. Based on these we discuss the consequences for the consumption of mushrooms originating from urban areas. Copyright © 2015 Elsevier Ltd. All rights reserved.

Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic, Validation and Extensions

PubMed Central

2017-01-01

Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels. PMID:29244762

A novel mobile monitoring approach to characterize spatial and temporal variation in traffic-related air pollutants in an urban community

NASA Astrophysics Data System (ADS)

Yu, Chang Ho; Fan, Zhihua; Lioy, Paul J.; Baptista, Ana; Greenberg, Molly; Laumbach, Robert J.

2016-09-01

Air concentrations of traffic-related air pollutants (TRAPs) vary in space and time within urban communities, presenting challenges for estimating human exposure and potential health effects. Conventional stationary monitoring stations/networks cannot effectively capture spatial characteristics. Alternatively, mobile monitoring approaches became popular to measure TRAPs along roadways or roadsides. However, these linear mobile monitoring approaches cannot thoroughly distinguish spatial variability from temporal variations in monitored TRAP concentrations. In this study, we used a novel mobile monitoring approach to simultaneously characterize spatial/temporal variations in roadside concentrations of TRAPs in urban settings. We evaluated the effectiveness of this mobile monitoring approach by performing concurrent measurements along two parallel paths perpendicular to a major roadway and/or along heavily trafficked roads at very narrow scale (one block away each other) within short time period (<30 min) in an urban community. Based on traffic and particulate matter (PM) source information, we selected 4 neighborhoods to study. The sampling activities utilized real-time monitors, including battery-operated PM2.5 monitor (SidePak), condensation particle counter (CPC 3007), black carbon (BC) monitor (Micro-Aethalometer), carbon monoxide (CO) monitor (Langan T15), and portable temperature/humidity data logger (HOBO U12), and a GPS-based tracker (Trackstick). Sampling was conducted for ∼3 h in the morning (7:30-10:30) in 7 separate days in March/April and 6 days in May/June 2012. Two simultaneous samplings were made at 5 spatially-distributed locations on parallel roads, usually distant one block each other, in each neighborhood. The 5-min averaged BC concentrations (AVG ± SD, [range]) were 2.53 ± 2.47 [0.09-16.3] μg/m3, particle number concentrations (PNC) were 33,330 ± 23,451 [2512-159,130] particles/cm3, PM2.5 mass concentrations were 8.87 ± 7.65 [0.27-46.5] μg/m3, and CO concentrations were 1.22 ± 0.60 [0.22-6.29] ppm in the community. The traffic-related air pollutants, BC and PNC, but not PM2.5 or CO, varied spatially depending on proximity to local stationary/mobile sources. Seasonal differences were observed for all four TRAPs, significantly higher in colder months than in warmer months. The coefficients of variation (CVs) in concurrent measurements from two parallel routes were calculated around 0.21 ± 0.17, and variations were attributed by meteorological variation (25%), temporal variability (19%), concentration level (6%), and spatial variability (2%), respectively. Overall study findings suggest this mobile monitoring approach could effectively capture and distinguish spatial/temporal characteristics in TRAP concentrations for communities impacted by heavy motor vehicle traffic and mixed urban air pollution sources.

Influences of traffic on Pb, Cu and Zn concentrations in roadside soils of an urban park in Dublin, Ireland.

PubMed

Dao, Ligang; Morrison, Liam; Zhang, Hongxuan; Zhang, Chaosheng

2014-06-01

Soils in the vicinity of roads are recipients of contaminants from traffic emissions. In order to obtain a better understanding of the impacts of traffic on soils, a total of 225 surface soil samples were collected from an urban park (Phoenix Park, Dublin, Ireland) in a grid system. Metal (Pb, Cu and Zn) concentrations were determined using a portable X-ray fluorescence analyzer. Strong spatial variations for the concentrations of Pb, Cu and Zn were observed. The spatial distribution maps created using geographical information system techniques revealed elevated metal concentrations close to the main traffic route in the park. The relationships between the accumulation of Pb, Cu and Zn in the roadside soils and the distance from the road were well fitted with an exponential model. Elevated metal concentrations from traffic pollution extended to a distance of approximately 40 m from the roadside. The results of this study provide useful information for the management of urban parks particularly in relation to policies aimed at reducing the impact of traffic related pollution on soils.

Neighborhood Social Inequalities in Road Traffic Injuries: The Influence of Traffic Volume and Road Design

PubMed Central

Gauvin, Lise; Plante, Céline; Fournier, Michel; Morency, Catherine

2012-01-01

Objectives. We examined the extent to which differential traffic volume and road geometry can explain social inequalities in pedestrian, cyclist, and motor vehicle occupant injuries across wealthy and poor urban areas. Methods. We performed a multilevel observational study of all road users injured over 5 years (n = 19 568) at intersections (n = 17 498) in a large urban area (Island of Montreal, Canada). We considered intersection-level (traffic estimates, major roads, number of legs) and area-level (population density, commuting travel modes, household income) characteristics in multilevel Poisson regressions that nested intersections in 506 census tracts. Results. There were significantly more injured pedestrians, cyclists, and motor vehicle occupants at intersections in the poorest than in the richest areas. Controlling for traffic volume, intersection geometry, and pedestrian and cyclist volumes greatly attenuated the event rate ratios between intersections in the poorest and richest areas for injured pedestrians (−70%), cyclists (−44%), and motor vehicle occupants (−44%). Conclusions. Roadway environment can explain a substantial portion of the excess rate of road traffic injuries in the poorest urban areas. PMID:22515869

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, H. M. Abdul; Ukkusuri, Satish V.

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE PAGES

Aziz, H. M. Abdul; Ukkusuri, Satish V.

2017-06-29

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

Behavioral Profiling of Scada Network Traffic Using Machine Learning Algorithms

DTIC Science & Technology

2014-03-27

BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS THESIS Jessica R. Werling, Captain, USAF AFIT-ENG-14-M-81 DEPARTMENT...subject to copyright protection in the United States. AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ...AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS Jessica R. Werling, B.S.C.S. Captain, USAF Approved

Dynamic baseline detection method for power data network service

NASA Astrophysics Data System (ADS)

Chen, Wei

2017-08-01

This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.

Smart urban design to reduce transportation impact in city centers

NASA Astrophysics Data System (ADS)

Fezzai, Soufiane; Mazouz, Said; Ahriz, Atef

2018-05-01

Air pollution is one of the most serious problems facing human being; urban wastes are in first range of energy consumption and emission of greenhouse gasses. Transportation or car traffic is one of the most consumer sectors of fuel, and most pollutant. Reducing energy consumption in transportation and the emission of pollutant gasses becomes an important objective for urban designers; many solutions may be proposed to help solving this problem in future designs, but it depend on other factors in existing urban space especially in city centers characterized with high occupation density. In this paper we investigate traffic rate in the city center of the case study, looking for the causes of the high traffic using gate count method and estimating fuel consumption. We try to propose some design solutions to reduce distances so fuel consumption and emission of pollutant gasses. We use space syntax techniques to evaluate urban configuration and verify the proposed solutions.

Exposure to urban stressor and effects on free testosterone in female workers.

PubMed

Tomei, Gianfranco; Ciarrocca, Manuela; Fiore, Pina; Rosati, Maria Valeria; Pimpinella, Benedetta; Anzani, Maria Francesca; Giubilati, Roberto; Cangemi, Chiara; Tomao, Enrico; Tomei, Francesco

2008-03-25

The aim of the study is to evaluate if occupational exposure to chemical, physical and psycho-social urban stressor could cause alterations in plasma free testosterone (T) levels and related diseases in female traffic police vs. control group. The research was carried out on initial sample of 468 female Municipal Police employees (209 traffic police and 259 controls). After excluding the principal confounding factors, traffic police were matched with controls by age, working life, menstrual cycle day, BMI, drinking habit, cigarette smoking habit, liquorice and soy intake in diet, habitual consumption of Italian coffee. There were 96 female traffic police and 96 controls included in the study. T mean levels were significantly higher in female traffic police compared to controls (p=0.000). The distribution of T values in traffic police and in controls was significant (p=0.000). No significant differences were found comparing the percentage in traffic police and controls concerning dystocial, premature and post-term birth. An increase in mental health disorders was found in traffic police compared to controls but the difference was not significant. The increase in T plasma levels observed in traffic police vs. controls can be due to a chronic working exposure to low doses of environmental chemical urban stressor. According to our previous researches T could be used as an early biological marker even before the onset of the related disorders.

Urban development control based on transportation carrying capacity

NASA Astrophysics Data System (ADS)

Miharja, M.; Sjafruddin, A. H.

2017-06-01

Severe transportation problems in Indonesian urban areas are stimulated by one fundamental factor, namely lack of awareness on transportation carrying capacity in these areas development control. Urban land use development towards more physical coverage is typically not related with the capability of transportation system to accommodate additional trips volume. Lack of clear connection between development permit with its implication on the transportation side has led to a phenomenon of exceeding transport demand over supply capacity. This paper discusses the concept of urban land use development control which will be related with transport carrying capacity. The discussion would cover both supply and demand sides of transportation. From supply side, the analysis regarding the capacity of transport system would take both existing as well as potential road network capacity could be developed. From demand side, the analysis would be through the control of a maximum floor area and public transport provision. Allowed maximum floor area for development would be at the level of generating traffic at reasonable volume. Ultimately, the objective of this paper is to introduce model to incorporate transport carrying capacity in Indonesian urban land use development control.

Exhaust Emissions Measured Under Real Traffic Conditions from Vehicles Fitted with Spark Ignition and Compression Ignition Engines

NASA Astrophysics Data System (ADS)

Merkisz, Jerzy; Lijewski, Piotr; Fuć, Paweł

2011-06-01

The tests performed under real traffic conditions provide invaluable information on the relations between the engine parameters, vehicle parameters and traffic conditions (traffic congestion) on one side and the exhaust emissions on the other. The paper presents the result of road tests obtained in an urban and extra-urban cycles for vehicles fitted with different engines, spark ignition engine and compression ignition engine. For the tests a portable emission analyzer SEMTECH DS. by SENSORS was used. This analyzer provides online measurement of the concentrations of exhaust emission components on a vehicle in motion under real traffic conditions. The tests were performed in city traffic. A comparative analysis has been presented of the obtained results for vehicles with individual powertrains.

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Takuma, Takehisa; Masugi, Masao

2009-03-01

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

Assessment of the influence of traffic-related particles in urban dust using sequential selective extraction and oral bioaccessibility tests.

PubMed

Patinha, C; Durães, N; Sousa, P; Dias, A C; Reis, A P; Noack, Y; Ferreira da Silva, E

2015-08-01

Urban dust is a heterogeneous mix, where traffic-related particles can combine with soil mineral compounds, forming a unique and site-specific material. These traffic-related particles are usually enriched in potentially harmful elements, enhancing the health risk for population by inhalation or ingestion. Urban dust samples from Estarreja city and traffic-related particles (brake dust and white traffic paint) were studied to understand the relative contribution of the traffic particles in the geochemical behaviour of urban dust and to evaluate the long-term impacts of the metals on an urban environment, as well as the risk to the populations. It was possible to distinguish two groups of urban dust samples according to Cu behaviour: (1) one group with low amounts of fine particles (<38 µm), low contents of organic material, high percentage of Cu in soluble phases, and low Cu bioaccessible fraction (Bf) values. This group showed similar chemical behaviour with the brake dust samples of low- to mid-range car brands (with more than 10 years old), composed by coarser wear particles; and (2) another group with greater amounts of fine particles (<38 µm), with low percentage of Cu associated with soluble phases, and with greater Cu Bf values. This group behaved similar to those found for brake dust of mid- to high-range car brands (with less than 10 years old). The results obtained showed that there is no direct correlation between the geoavailability of metals estimated by sequential selective chemical extraction (SSCE) and the in vitro oral bioaccessibility (UBM) test. Thus, oral bioaccessibility of urban dust is site specific. Geoavailability was greatly dependent on particle size, where the bioaccessibility tended to increase with a reduction in particle diameter. As anthropogenic particles showed high metal concentration and a smaller size than mineral particles, urban dusts are of major concern to the populations' health, since fine particles are easily re-suspended, easily ingested, and show high metal bioaccessibility. In addition, Estarreja is a coastal city often influenced by winds, which favours the re-suspension of small-sized contaminated particles. Even if the risk to the population does not represent an acute case, it should not be overlooked, and this study can serve as baseline study for cities under high traffic influence.

Network Traffic Generator for Low-rate Small Network Equipment Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lanzisera, Steven

2013-05-28

Application that uses the Python low-level socket interface to pass network traffic between devices on the local side of a NAT router and the WAN side of the NAT router. This application is designed to generate traffic that complies with the Energy Star Small Network Equipment Test Method.

Hybrid and electric low-noise cars cause an increase in traffic accidents involving vulnerable road users in urban areas.

PubMed

Brand, Stephan; Petri, Maximilian; Haas, Philipp; Krettek, Christian; Haasper, Carl

2013-01-01

Due to resource scarcity, the number of low-noise and electric cars is expected to increase rapidly. The frequent use of these cars will lead to a significant reduction of traffic related noise and pollution. On the other hand, due to the adaption and conditioning of vulnerable road users the number of traffic accidents involving pedestrians and bicyclists is postulated to increase as well. Children, older people with reduced eyesight and the blind are especially reliant on a combination of acoustic and visual warning signals with approaching or accelerating vehicles. This is even more evident in urban areas where the engine sound is the dominating sound up to 30 kph (kilometres per hour). Above this, tyre-road interaction is the main cause of traffic noise. With the missing typical engine sound a new sound design is necessary to prevent traffic accidents in urban areas. Drivers should not be able to switch the sound generator off.

Incidence of real-world automotive parent and halogenated PAH in urban atmosphere.

PubMed

Gao, Pan-Pan; Zhao, Yi-Bo; Ni, Hong-Gang

2018-06-01

This study reports results from a tunnel experiment impact of real-world traffic-related particle and gas parent and halogenated polycyclic aromatic hydrocarbons (PAHs and HPAHs) on urban air. The traffic related emission characteristics and subsequent environmental behavior of these compounds were investigated. To understand the significance of real-world transport emissions to the urban air, traffic-related mass emissions of PAHs and HPAHs were estimated based on measured emission factors. According to our results, PAHs and HPAHs emissions via particulate phase were greater than those via gaseous phase; particles in 2.1-3.3 μm size fraction, have the major contribution to particulate PAHs and HPAHs emissions. Over all, contribution of traffic-related emission of PAHs (only ∼3% of the total PAHs emission in China) is an overstated source of PAHs pollution in China. Actually, exhaust pipe emission contributed much less than the total traffic-related emission of pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.

Indiana freeway traffic characteristics and dynamic prediction of freeway traffic flows

DOT National Transportation Integrated Search

1999-12-01

Traffic volumes on Indiana's roadways have increased significantly in the past years. During the period between 1989 and 1993, traffic volumes increased 20.2% on Indiana's urban interstate freeways and expressways, and 13.1% on rural interstates. The...

Leveraging traffic and surveillance video cameras for urban traffic.

DOT National Transportation Integrated Search

2014-12-01

The objective of this project was to investigate the use of existing video resources, such as traffic : cameras, police cameras, red light cameras, and security cameras for the long-term, real-time : collection of traffic statistics. An additional ob...

Active Traffic Capture for Network Forensics

NASA Astrophysics Data System (ADS)

Slaviero, Marco; Granova, Anna; Olivier, Martin

Network traffic capture is an integral part of network forensics, but current traffic capture techniques are typically passive in nature. Under heavy loads, it is possible for a sniffer to miss packets, which affects the quality of forensic evidence.

Health impacts of frequent heavy automobile traffic on children and adolescents.

PubMed

Akpan, Akpan I

2004-01-01

This paper assesses the extent to which particulate, elemental and organic carbon emissions from heavy traffic in urban city roads affect the health of children and the adolescent health. Although the health effects of exposures may be cumulative, it is in the adolescence that the manifestations are realized. This paper therefore, assesses the best way forward for monitoring and preventing the environmental health impacts of heavy traffic on children and adolescents who live within the vicinity of urban city transportation systems. Major urban cities such as Houston, New York, and California are cited as examples of cities where health-related problems have already been reported. The particulate, elemental and organic carbon emissions are reviewed as the sources by which heavy traffic and the hazardous chemical emissions affect the health of the populace. The role of accessory loading and engine speed on idling emissions in direct health risks of children and adolescents is evaluated. The association of particulate, elemental, and organic carbon emission with respiratory effects (including, allergies and asthma), and the related behavior problems in children and the adolescents are discussed. The best strategies in preventing the effects of heavy traffic in the urban cities are suggested by introducing new effective monitoring techniques and exposure assessment methods. It is visualized that a more comprehensive research is needed to develop robust regulatory systems that would control the efficiency of automobiles and prevent the adverse health effects relating to heavy traffics in urban city roads. Strong city environmental health authorities-community partnerships relevant to exposure information should be encouraged.

Source apportionment of organic pollutants of a highway-traffic-influenced urban area in Bayreuth (Germany) using biomarker and stable carbon isotope signatures.

PubMed

Glaser, Bruno; Dreyer, Annekatrin; Bock, Michael; Fiedler, Stefan; Mehring, Marion; Heitmann, Tobias

2005-06-01

Traffic- and urban-influenced areas are prone to enhanced pollution with products of incomplete combustion of fossil fuels and biomass such as black carbon or polycyclic aromatic hydrocarbons (PAHs). Black carbon is composed of aromatic and graphitic structures and may act as a carrier for pollutants such as PAHs and heavy metals. However, little is known about possible contributions of traffic-derived black carbon to the black carbon inventory in soils. Similar uncertainties exist regarding the contribution of different pollutant sources to total PAH and black carbon contents. Therefore, the objective of this study was to quantify the importance of traffic pollution to black carbon and PAH inventories in soils. PAH contamination of soils adjacent to a major German highway in the urban area of Bayreuth with about 50,000 vehicles per day was in the same order of magnitude compared to highway-close soils reported in other studies. Using molecular (black carbon and PAHs) and compound-specific stable carbon isotope evidence (PAHs) it was demonstrated that this contamination originated not only from automobile exhausts, here primarily diesel, but also from tire abrasion and tailpipe soot which significantly contributed to the traffic-caused black carbon and PAH contamination. Low molecular weight PAHs were more widely transported than their heavy molecular counterparts (local distillation), whereas highway-traffic-caused black carbon contamination was distributed to at least 30 m from the highway. On the other hand, urban fire exhausts were distributed more homogeneously among the urban area.

Spatial distribution of traffic induced noise exposures in a US city: an analytic tool for assessing the health impacts of urban planning decisions

PubMed Central

Seto, Edmund Yet Wah; Holt, Ashley; Rivard, Tom; Bhatia, Rajiv

2007-01-01

Background: Vehicle traffic is the major source of noise in urban environments, which in turn has multiple impacts on health. In this paper we investigate the spatial distribution of community noise exposures and annoyance. Traffic data from the City of San Francisco were used to model noise exposure by neighborhood and road type. Remote sensing data were used in the model to estimate neighborhood-specific percentages of cars, trucks, and buses on arterial versus non-arterial streets. The model was validated on 235 streets. Finally, an exposure-response relationship was used to predict the prevalence of high annoyance for different neighborhoods. Results: Urban noise was found to increase 6.7 dB (p < 0.001) with 10-fold increased street traffic, with important contributors to noise being bus and heavy truck traffic. Living along arterial streets also increased risk of annoyance by 40%. The relative risk of annoyance in one of the City's fastest growing neighborhoods, the South of Market Area, was found to be 2.1 times that of lowest noise neighborhood. However, higher densities of exposed individuals were found in Chinatown and Downtown/Civic Center. Overall, we estimated that 17% of the city's population was at risk of high annoyance from traffic noise. Conclusion: The risk of annoyance from urban noise is large, and varies considerably between neighborhoods. Such risk should be considered in urban areas undergoing rapid growth. We present a relatively simple GIS-based noise model that may be used for routinely evaluating the health impacts of environmental noise. PMID:17584947

Urban Sprawl as a Risk Factor in Motor Vehicle Occupant and Pedestrian Fatalities

PubMed Central

Ewing, Reid; Schieber, Richard A.; Zegeer, Charles V.

2003-01-01

Objectives. We sought to determine the association between urban sprawl and traffic fatalities. Methods. We created a sprawl index by applying principal components analysis to data for 448 US counties in the largest 101 metropolitan areas. Regression analysis was used to determine associations between the index and traffic fatalities. Results. For every 1% increase in the index (i.e., more compact, less sprawl), all-mode traffic fatality rates fell by 1.49% (P < .001) and pedestrian fatality rates fell by 1.47% to 3.56%, after adjustment for pedestrian exposure (P < .001). Conclusions. Urban sprawl was directly related to traffic fatalities and pedestrian fatalities. Subsequent studies should investigate relationships at a finer geographic scale and should strive to improve on the measure of exposure used to adjust pedestrian fatality rates. PMID:12948977

Fully automated urban traffic system

NASA Technical Reports Server (NTRS)

Dobrotin, B. M.; Hansen, G. R.; Peng, T. K. C.; Rennels, D. A.

1977-01-01

The replacement of the driver with an automatic system which could perform the functions of guiding and routing a vehicle with a human's capability of responding to changing traffic demands was discussed. The problem was divided into four technological areas; guidance, routing, computing, and communications. It was determined that the latter three areas being developed independent of any need for fully automated urban traffic. A guidance system that would meet system requirements was not being developed but was technically feasible.

Plasma 17-alpha-OH-progesterone in female workers exposed to urban pollutants.

PubMed

Ciarrocca, M; Cerratti, D; Capozzella, A; Rosati, M V; Anzani, M F; Bernardini, A; Casale, T; Pimpinella, B; Tomei, G; Monti, C; Tomao, E; Tomei, F

2006-01-01

The aim of this study is to evaluate whether occupational exposure to urban pollutants could cause alteration in plasma 17-alpha-OH-P levels in female workers. After excluding the subjects with the principal confounding factors, traffic police and controls were matched by age, working life, age of menarche, menstrual cycle day, BMI, drinking habits, habitual consumption of soy and Italian coffee. 68 traffic police and 82 controls (7th day; follicular phase of the ovarian cycle), 37 traffic police and 20 controls (21st day; lutheal phase of the ovarian cycle) were included in the study and matched for the above mentioned variables. In follicular and lutheal phase of ovarian cycle, 17-alpha-OH-P mean levels and the distribution of 17-alpha-OH-P values were significantly higher in traffic police vs. controls. A higher instance of mental health disorders in traffic police vs. controls was found, although the difference was not significant. Considering that the potential confounding effect of extraneous factors was controlled by restricting the study population and by matching traffic police vs. controls on the above mentioned variables, our results suggest that occupational exposure to urban pollutants may alter plasma 17-alpha-OH-P concentrations. 17-alpha-OH-P could be used in an occupational setting as an early biomarker of exposure to urban pollutants, valuable for a group, even before the onset of related pathologies.

Assessment and management of human health risk from toxic metals and polycyclic aromatic hydrocarbons in urban stormwater arising from anthropogenic activities and traffic congestion.

PubMed

Ma, Yukun; Liu, An; Egodawatta, Prasanna; McGree, James; Goonetilleke, Ashantha

2017-02-01

Toxic metals (TMs) and polycyclic aromatic hydrocarbons (PAHs) in urban stormwater pose risk to human health, thereby constraining its reuse potential. Based on the hypothesis that stormwater quality is primarily influenced by anthropogenic activities and traffic congestion, the primary focus of the research study was to analyse the impacts on human health risk from TMs and PAHs in urban stormwater and thereby develop a quantitative risk assessment model. The study found that anthropogenic activities and traffic congestion exert influence on the risk posed by TMs and PAHs in stormwater from commercial and residential areas. Motor vehicle related businesses (FVS) and traffic congestion (TC) were identified as two parameters which need to be included as independent variables to improve the model. Based on the study outcomes, approaches for mitigating the risk associated with TMs and PAHs in urban stormwater are discussed. Additionally, a roadmap is presented for the assessment and management of the risk arising from these pollutants. The study outcomes are expected to contribute to reducing the human health risk associated urban stormwater pollution and thereby enhance its reuse potential. Copyright © 2016 Elsevier B.V. All rights reserved.

Traffic and nucleation events as main sources of ultrafine particles in high-insolation developed world cities

NASA Astrophysics Data System (ADS)

Brines, M.; Dall'Osto, M.; Beddows, D. C. S.; Harrison, R. M.; Gómez-Moreno, F.; Núñez, L.; Artíñano, B.; Costabile, F.; Gobbi, G. P.; Salimi, F.; Morawska, L.; Sioutas, C.; Querol, X.

2015-05-01

Road traffic emissions are often considered the main source of ultrafine particles (UFP, diameter smaller than 100 nm) in urban environments. However, recent studies worldwide have shown that - in high-insolation urban regions at least - new particle formation events can also contribute to UFP. In order to quantify such events we systematically studied three cities located in predominantly sunny environments: Barcelona (Spain), Madrid (Spain) and Brisbane (Australia). Three long-term data sets (1-2 years) of fine and ultrafine particle number size distributions (measured by SMPS, Scanning Mobility Particle Sizer) were analysed. Compared to total particle number concentrations, aerosol size distributions offer far more information on the type, origin and atmospheric evolution of the particles. By applying k-means clustering analysis, we categorized the collected aerosol size distributions into three main categories: "Traffic" (prevailing 44-63% of the time), "Nucleation" (14-19%) and "Background pollution and Specific cases" (7-22%). Measurements from Rome (Italy) and Los Angeles (USA) were also included to complement the study. The daily variation of the average UFP concentrations for a typical nucleation day at each site revealed a similar pattern for all cities, with three distinct particle bursts. A morning and an evening spike reflected traffic rush hours, whereas a third one at midday showed nucleation events. The photochemically nucleated particles' burst lasted 1-4 h, reaching sizes of 30-40 nm. On average, the occurrence of particle size spectra dominated by nucleation events was 16% of the time, showing the importance of this process as a source of UFP in urban environments exposed to high solar radiation. Nucleation events lasting for 2 h or more occurred on 55% of the days, this extending to > 4 h in 28% of the days, demonstrating that atmospheric conditions in urban environments are not favourable to the growth of photochemically nucleated particles. In summary, although traffic remains the main source of UFP in urban areas, in developed countries with high insolation urban nucleation events are also a main source of UFP. If traffic-related particle concentrations are reduced in the future, nucleation events will likely increase in urban areas, due to the reduced urban condensation sinks.

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials.

PubMed

Theofilatos, Athanasios

2017-06-01

The effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece. Random Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively. Regarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity. The study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms. The identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Using OpenSSH to secure mobile LAN network traffic

NASA Astrophysics Data System (ADS)

Luu, Brian B.; Gopaul, Richard D.

2002-08-01

Mobile Internet Protocol (IP) Local Area Network (LAN) is a technique, developed by the U.S. Army Research Laboratory, which allows a LAN to be IP mobile when attaching to a foreign IP-based network and using this network as a means to retain connectivity to its home network. In this paper, we describe a technique that uses Open Secure Shell (OpenSSH) software to ensure secure, encrypted transmission of a mobile LAN's network traffic. Whenever a mobile LAN, implemented with Mobile IP LAN, moves to a foreign network, its gateway (router) obtains an IP address from the new network. IP tunnels, using IP encapsulation, are then established from the gateway through the foreign network to a home agent on its home network. These tunnels provide a virtual two-way connection to the home network for the mobile LAN as if the LAN were connected directly to its home network. Hence, when IP mobile, a mobile LAN's tunneled network traffic must traverse one or more foreign networks that may not be trusted. This traffic could be subject to eavesdropping, interception, modification, or redirection by malicious nodes in these foreign networks. To protect network traffic passing through the tunnels, OpenSSH is used as a means of encryption because it prevents surveillance, modification, and redirection of mobile LAN traffic passing across foreign networks. Since the software is found in the public domain, is available for most current operating systems, and is commonly used to provide secure network communications, OpenSSH is the software of choice.

The inhabited environment, infrastructure development and advanced urbanization in China’s Yangtze River Delta Region

NASA Astrophysics Data System (ADS)

Zhu, Xiaoqing; Gao, Weijun; Zhou, Nan; Kammen, Daniel M.; Wu, Yiqun; Zhang, Yao; Chen, Wei

2016-12-01

This paper analyzes the relationship among the inhabited environment, infrastructure development and environmental impacts in China’s heavily urbanized Yangtze River Delta region. Using primary human environment data for the period 2006-2014, we examine factors affecting the inhabited environment and infrastructure development: urban population, GDP, built-up area, energy consumption, waste emission, transportation, real estate and urban greenery. Then we empirically investigate the impact of advanced urbanization with consideration of cities’ differences. Results from this study show that the growth rate of the inhabited environment and infrastructure development is strongly influenced by regional development structure, functional orientations, traffic network and urban size and form. The effect of advanced urbanization is more significant in large and mid-size cities than huge and mega cities. Energy consumption, waste emission and real estate in large and mid-size cities developed at an unprecedented rate with the rapid increase of economy. However, urban development of huge and mega cities gradually tended to be saturated. The transition development in these cities improved the inhabited environment and ecological protection instead of the urban construction simply. To maintain a sustainable advanced urbanization process, policy implications included urban sprawl control polices, ecological development mechanisms and reforming the economic structure for huge and mega cities, and construct major cross-regional infrastructure, enhance the carrying capacity and improvement of energy efficiency and structure for large and mid-size cities.

Mobile radio alternative systems study traffic model

NASA Astrophysics Data System (ADS)

Tucker, W. T.; Anderson, R. E.

1983-06-01

The markets for mobile radio services in non-urban areas of the United States are examined for the years 1985-2000. Three market categories are identified. New Services are defined as those for which there are different expressed ideas but which are not now met by any application of available technology. The complete fulfillment of the needs requires nationwide radio access to vehicles without knowledge of vehicle location, wideband data transmission from remote sites, one- and two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The commercial and public services market of interest to the study is drawn from existing users of mobile radio in non-urban areas who are dissatisfied with the geographical range or coverage of their systems. The mobile radio telephone market comprises potential users who require access to the public switched telephone network in areas that are not likely to be served by the traditional growth patterns of terrestrial mobile telephone services. Conservative, likely, and optimistic estimates of the markets are presented in terms of numbers of vehicles that will be served and the radio traffic they will generate.

Mobile radio alternative systems study. Volume 1: Traffic model

NASA Technical Reports Server (NTRS)

Tucker, W. T.; Anderson, R. E.

1983-01-01

The markets for mobile radio services in non-urban areas of the United States are examined for the years 1985-2000. Three market categories are identified. New Services are defined as those for which there are different expressed ideas but which are not now met by any application of available technology. The complete fulfillment of the needs requires nationwide radio access to vehicles without knowledge of vehicle location, wideband data transmission from remote sites, one- and two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The commercial and public services market of interest to the study is drawn from existing users of mobile radio in non-urban areas who are dissatisfied with the geographical range or coverage of their systems. The mobile radio telephone market comprises potential users who require access to the public switched telephone network in areas that are not likely to be served by the traditional growth patterns of terrestrial mobile telephone services. Conservative, likely, and optimistic estimates of the markets are presented in terms of numbers of vehicles that will be served and the radio traffic they will generate.

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

NASA Astrophysics Data System (ADS)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

Feasibility study on intersection in North Sumatera

NASA Astrophysics Data System (ADS)

Hastuty, I. P.; Sembiring, I. S.; Anas, R.; Lubis, A. S.

2018-02-01

Traffic congestion is one of the problems faced by big cities, One of them is Binjai city and Medan city in North Sumatera. One of the causes of congestion is intersection of roads with highway and roads with railroads. To ensure the smooth movement of vehicles, technical handling at the intersection is needed. Therefore, it is necessary to pre-study the feasibility of level crossing in Binjai and Medan to be able to assess the investment needs and the level of importance of road development in the region. The development of transportation infrastructure and facilities is based on the thought of improving the transportation network system. The necessity of systemical integrated transportation system handling is needed in creating a transportation efficiency. The purpose of this study is to identify and prioritize the needs of the railway crossings. The objective which we want to be achieved is to obtain a document that contains technical, economic and environmental ability indicators as a reference in the feasibility and planning studies. The methodology used is collecting the primary data, secondary data, introduction of study area as the initial analysis of the problem. From the study it can be concluded that the existence of railway interchange will move the movement through traffic so it will not interfere the movement of traffic within urban areas and it keeps the national road network performance is still good.

Real-Time SCADA Cyber Protection Using Compression Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lyle G. Roybal; Gordon H Rueff

2013-11-01

The Department of Energy’s Office of Electricity Delivery and Energy Reliability (DOE-OE) has a critical mission to secure the energy infrastructure from cyber attack. Through DOE-OE’s Cybersecurity for Energy Delivery Systems (CEDS) program, the Idaho National Laboratory (INL) has developed a method to detect malicious traffic on Supervisory, Control, and Data Acquisition (SCADA) network using a data compression technique. SCADA network traffic is often repetitive with only minor differences between packets. Research performed at the INL showed that SCADA network traffic has traits desirable for using compression analysis to identify abnormal network traffic. An open source implementation of a Lempel-Ziv-Welchmore » (LZW) lossless data compression algorithm was used to compress and analyze surrogate SCADA traffic. Infected SCADA traffic was found to have statistically significant differences in compression when compared against normal SCADA traffic at the packet level. The initial analyses and results are clearly able to identify malicious network traffic from normal traffic at the packet level with a very high confidence level across multiple ports and traffic streams. Statistical differentiation between infected and normal traffic level was possible using a modified data compression technique at the 99% probability level for all data analyzed. However, the conditions tested were rather limited in scope and need to be expanded into more realistic simulations of hacking events using techniques and approaches that are better representative of a real-world attack on a SCADA system. Nonetheless, the use of compression techniques to identify malicious traffic on SCADA networks in real time appears to have significant merit for infrastructure protection.« less

Application of the ACASA model for urban development studies

NASA Astrophysics Data System (ADS)

Marras, S.; Pyles, R. D.; Falk, M.; Snyder, R. L.; Paw U, K. T.; Blecic, I.; Trunfio, G. A.; Cecchini, A.; Spano, D.

2012-04-01

Since urban population is growing fast and urban areas are recognized as the major source of CO2 emissions, more attention has being dedicated to the topic of urban sustainability and its connection with the climate. Urban flows of energy, water and carbon have an important impact on climate change and their quantification is pivotal in the city design and management. Large effort has been devoted to quantitative estimates of the urban metabolism components, and several advanced models have been developed and used at different spatial and temporal scales for this purpose. However, it is necessary to develop suitable tools and indicators to effectively support urban planning and management with the goal of achieving a more sustainable metabolism in the urban environment. In this study, the multilayer model ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) was chosen to simulate the exchanges of heat, water vapour and CO2 within and above urban canopy. After several calibration and evaluation tests over natural and agricultural ecosystems, the model was recently modified for application in urban and peri-urban areas. New equations to account for the anthropogenic contribution to heat exchange and carbon production, as well as key parameterizations of leaf-facet scale interactions to separate both biogenic and anthropogenic flux sources and sinks, were added to test changes in land use or urban planning strategies. The analysis was based on the evaluation of the ACASA model performance in estimating urban metabolism components at local scale. Simulated sensible heat, latent heat, and carbon fluxes were compared with in situ Eddy Covariance measurements collected in the city centre of Florence (Italy). Statistical analysis was performed to test the model accuracy and reliability. Model sensitivity to soil types and increased population density values was conducted to investigate the potential use of ACASA for evaluating the impact of planning alternative scenarios. In this contest, an in progress application of ACASA for estimating carbon exchanges alternative scenarios is represented by its integration in a software framework composed by: (i) a Cellular Automata model to simulate the urban land-use dynamics; (ii) a transportation model, able to estimate the variation of the transportation network load; (iii) the ACASA model, and (iv) the mesoscale weather model WRF for the estimation of the relevant urban metabolism components at regional scale. The CA module is able to produce future land use maps, which represent a spatial distribution of the aggregate land-use demand consistent with the main rules governing the functioning of an urban system. Such future land use maps, together with the street network including the current traffic data, are used by the transportation module for estimating future traffic data coherent with the assumed land uses trends. All these information are then used by the coupled model WRF-ACASA for estimating future maps of CO2 fluxes in the urban area under consideration, allowing to estimate the impact of future planning strategies in reducing C emissions. The in-progress application of this system to the city of Florence is presented here.

a Cross-Sectional Study on Insomnia among Japanese Adult Women in Relation to Night-Time Road Traffic Noise

NASA Astrophysics Data System (ADS)

Kageyama, T.; Kabuto, M.; Nitta, N.; Kurokawa, Y.; Taira, K.; Suzuki, S.; Takemoto, T.

1997-08-01

In an effort to determine the contribution of night-time road traffic noise to insomnia in the general population, 3600 adult Japanese women living in urban residential areas were surveyed. Living near a road with a heavy traffic volume is one of the risk factors for insomnia. The risk for insomnia in the zones 0-20 m from the main roads increased linearly with the night-time traffic volume. This suggests that road traffic noise raises the sound level in bedrooms in such zones, and consequently the prevalence rate of insomnia among the residents, and that noise-induced insomnia is an important public health problem, at least in highly urbanized areas.

Determinant of Road Traffic Crash Fatalities in Iran: A Longitudinal Econometric Analysis.

PubMed

Rezaei, Satar; Bagheri Lankarani, Kamran; Karami Matin, Behzad; Bazyar, Mohammad; Hamzeh, Behrooz; Najafi, Farid

2015-01-01

Injuries and deaths from road traffic crashes are one of the main public health problems throughout the world. This study aimed to identify determinants of fatality traffic accident in Iran for the twenty-span year from 1991 to 2011. A time series analysis (1991-2011) was used to examine the effects of some of the key explanatory factors (GDP per capita, number of doctors per 10,000 populations, degree of urbanization, unemployment rate and motorization rate) on deaths from road traffic in Iran. In order to examine long- and short-run effects of variables, we employed autoregressive distributed lag (ARDL) approach and error correction method (ECM). The data for the study was obtained from the Central Bank of Iran (CBI), Iranian Statistical Center (ISC) and Legal medical organizations (LMO). GDP per capita, doctor per 10,000 populations, degree of urbanization and motorization rate had a significant impact on fatality from road traffic in Iran. We did not observe any short- and long-term effects of the unemployment rate on fatality from road traffic. GDP per capita, doctor per 10,000 populations, degree of urbanization and motorization rate were identified as main determinant of fatality from road traffic accidents in Iran. We hope the results of the current study enable health policy-makers to understand better the factors affecting deaths from road traffic accidents in the country.

Osm-Oriented Method of Multimodal Route Planning

NASA Astrophysics Data System (ADS)

Li, X.; Wu, Q.; Chen, L.; Xiong, W.; Jing, N.

2015-07-01

With the increasing pervasiveness of basic facilitate of transportation and information, the need of multimodal route planning is becoming more essential in the fields of communication and transportation, urban planning, logistics management, etc. This article mainly described an OSM-oriented method of multimodal route planning. Firstly, it introduced how to extract the information we need from OSM data and build proper network model and storage model; then it analysed the accustomed cost standard adopted by most travellers; finally, we used shortest path algorithm to calculate the best route with multiple traffic means.

Characterizing local traffic contributions to particulate air pollution in street canyons using mobile monitoring techniques

NASA Astrophysics Data System (ADS)

Zwack, Leonard M.; Paciorek, Christopher J.; Spengler, John D.; Levy, Jonathan I.

2011-05-01

Traffic within urban street canyons can contribute significantly to ambient concentrations of particulate air pollution. In these settings, it is challenging to separate within-canyon source contributions from urban and regional background concentrations given the highly variable and complex emissions and dispersion characteristics. In this study, we used continuous mobile monitoring of traffic-related particulate air pollutants to assess the contribution to concentrations, above background, of traffic in the street canyons of midtown Manhattan. Concentrations of both ultrafine particles (UFP) and fine particles (PM 2.5) were measured at street level using portable instruments. Statistical modeling techniques accounting for autocorrelation were used to investigate the presence of spatial heterogeneity of pollutant concentrations as well as to quantify the contribution of within-canyon traffic sources. Measurements were also made within Central Park, to examine the impact of offsets from major roadways in this urban environment. On average, an approximate 11% increase in concentrations of UFP and 8% increase in concentrations of PM 2.5 over urban background was estimated during high-traffic periods in street canyons as opposed to low traffic periods. Estimates were 8% and 5%, respectively, after accounting for temporal autocorrelation. Within Central Park, concentrations were 40% higher than background (5% after accounting for temporal autocorrelation) within the first 100 m from the nearest roadway for UFP, with a smaller but statistically significant increase for PM 2.5. Our findings demonstrate the viability of a mobile monitoring protocol coupled with spatiotemporal modeling techniques in characterizing local source contributions in a setting with street canyons.

Traffic Profiling in Wireless Sensor Networks

DTIC Science & Technology

2006-12-01

components, that can be used for traffic profiling and monitoring of a wireless sensor network . The work demostrates how the IDS should capture and...observed and analyzed. Finally, initial indications from basic analysis of wireless sensor network traffic demonstrated a high degree of self-similarity.

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN

PubMed Central

2018-01-01

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μController-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 16 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection. PMID:29677147

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN.

PubMed

Alsina-Pagès, Rosa Ma; Alías, Francesc; Socoró, Joan Claudi; Orga, Ferran

2018-04-20

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 1 6 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.

Network traffic anomaly prediction using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Ciptaningtyas, Hening Titi; Fatichah, Chastine; Sabila, Altea

2017-03-01

As the excessive increase of internet usage, the malicious software (malware) has also increase significantly. Malware is software developed by hacker for illegal purpose(s), such as stealing data and identity, causing computer damage, or denying service to other user[1]. Malware which attack computer or server often triggers network traffic anomaly phenomena. Based on Sophos's report[2], Indonesia is the riskiest country of malware attack and it also has high network traffic anomaly. This research uses Artificial Neural Network (ANN) to predict network traffic anomaly based on malware attack in Indonesia which is recorded by Id-SIRTII/CC (Indonesia Security Incident Response Team on Internet Infrastructure/Coordination Center). The case study is the highest malware attack (SQL injection) which has happened in three consecutive years: 2012, 2013, and 2014[4]. The data series is preprocessed first, then the network traffic anomaly is predicted using Artificial Neural Network and using two weight update algorithms: Gradient Descent and Momentum. Error of prediction is calculated using Mean Squared Error (MSE) [7]. The experimental result shows that MSE for SQL Injection is 0.03856. So, this approach can be used to predict network traffic anomaly.

A new traffic control design method for large networks with signalized intersections

NASA Technical Reports Server (NTRS)

Leininger, G. G.; Colony, D. C.; Seldner, K.

1979-01-01

The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.

The Impact of the Thai Motorcycle Transition on Road Traffic Injury: Thai Cohort Study Results

PubMed Central

Berecki-Gisolf, Janneke; Yiengprugsawan, Vasoontara; Kelly, Matthew; McClure, Roderick; Seubsman, Sam-ang; Sleigh, Adrian

2015-01-01

Objectives The aim of this study was to investigate the impact of motorcycle to car transitioning and urbanisation on traffic injury rates in Thailand. Design Analysis of two consecutive surveys of a large national cohort study. Setting Thailand. Participants The data derived from 57,154 Thai Cohort Study (TCS) participants who provided relevant data on both the 2005 and 2009 surveys. Primary and secondary outcome measures Motorcycle and car traffic crash injury self-reported in 2009, with twelve months’ recall. Results In 2009, 5608(10%) participants reported a traffic crash injury. Most crashes involved a motorcycle (74%). Car access increased and motorcycle use decreased between 2005 and 2009. Among those who used a motorcycle at both time points, traffic injury incidence was 2.8 times greater compared to those who did not use a motorcycle at either time point. Multivariable logistic regression models were used to test longitudinal and cross sectional factors associated with traffic crash injury: in the adjusted model, cars were negatively and motorcycles positively associated with injury. Living in an urban area was not injury protective in the adjusted model of traffic crash injury. Conclusions Ongoing urbanisation in Thailand can be expected to lead to further reductions in road traffic injuries based on transition from motorcycles to cars in urban areas. Cities, however, do not provide an intrinsically safer traffic environment. To accommodate a safe transition to car use in Thailand, traffic infrastructural changes anticipating the growing car density in urban areas is warranted. PMID:25826214

A method to estimate spatiotemporal air quality in an urban traffic corridor.

PubMed

Singh, Nongthombam Premananda; Gokhale, Sharad

2015-12-15

Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. Copyright © 2015 Elsevier B.V. All rights reserved.

Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network

PubMed Central

Al-Mayouf, Yusor Rafid Bahar; Ismail, Mahamod; Abdullah, Nor Fadzilah; Wahab, Ainuddin Wahid Abdul; Mahdi, Omar Adil; Khan, Suleman; Choo, Kim-Kwang Raymond

2016-01-01

Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destination node via multi-hop routing techniques. An appropriate, efficient, and stable routing algorithm must be developed for various VANET applications to address the issues of dynamic topology and intermittent connectivity. Therefore, this paper proposes a novel routing algorithm called efficient and stable routing algorithm based on user mobility and node density (ESRA-MD). The proposed algorithm can adapt to significant changes that may occur in the urban vehicular environment. This algorithm works by selecting an optimal route on the basis of hop count and link duration for delivering data from source to destination, thereby satisfying various quality of service considerations. The validity of the proposed algorithm is investigated by its comparison with ARP-QD protocol, which works on the mechanism of optimal route finding in VANETs in urban environments. Simulation results reveal that the proposed ESRA-MD algorithm shows remarkable improvement in terms of delivery ratio, delivery delay, and communication overhead. PMID:27855165

Characterizing the influence of transportation infrastructure on Emergency Medical Services (EMS) in urban area-A case study of Seoul, South Korea.

PubMed

Cho, Jungwoo; You, Myoungsoon; Yoon, Yoonjin

2017-01-01

In highly urbanized area where traffic condition fluctuates constantly, transportation infrastructure is one of the major contributing factors to Emergency Medical Service (EMS) availability and patient outcome. In this paper, we assess the impact of traffic fluctuation to the EMS first response availability in urban area, by evaluating the k-minute coverage under 21 traffic scenarios. The set of traffic scenarios represents the time-of-day and day-of-week effects, and is generated by combining road link speed information from multiple historical speed databases. In addition to the k-minute area coverage calculation, the k-minute population coverage is also evaluated for every 100m by 100m grid that partitions the case study area of Seoul, South Korea. In the baseline case of traveling at the speed limit, both the area and population coverage reached nearly 100% when compared to the five-minute travel time national target. Employing the proposed LoST (Loss of Serviceability due to Traffic) index, which measures coverage reduction in percentage compared to the baseline case, we find that the citywide average LoST for area and population coverage are similar at 34.2% and 33.8%. However, district-wise analysis reveals that such reduction varies significantly by district, and the magnitude of area and population coverage reduction is not always proportional. We conclude that the effect of traffic variation is significant to successful urban EMS first response performance, and regional variation is evident among local districts. Complexity in the urban environment requires a more adaptive approach in public health resource management and EMS performance target determination.

Understanding the T2 traffic in CMS during Run-1

NASA Astrophysics Data System (ADS)

T, Wildish

2015-12-01

In the run-up to Run-1 CMS was operating its facilities according to the MONARC model, where data-transfers were strictly hierarchical in nature. Direct transfers between Tier-2 nodes was excluded, being perceived as operationally intensive and risky in an era where the network was expected to be a major source of errors. By the end of Run-1 wide-area networks were more capable and stable than originally anticipated. The original data-placement model was relaxed, and traffic was allowed between Tier-2 nodes. Tier-2 to Tier-2 traffic in 2012 already exceeded the amount of Tier-2 to Tier-1 traffic, so it clearly has the potential to become important in the future. Moreover, while Tier-2 to Tier-1 traffic is mostly upload of Monte Carlo data, the Tier-2 to Tier-2 traffic represents data moved in direct response to requests from the physics analysis community. As such, problems or delays there are more likely to have a direct impact on the user community. Tier-2 to Tier-2 traffic may also traverse parts of the WAN that are at the 'edge' of our network, with limited network capacity or reliability compared to, say, the Tier-0 to Tier-1 traffic which goes the over LHCOPN network. CMS is looking to exploit technologies that allow us to interact with the network fabric so that it can manage our traffic better for us, this we hope to achieve before the end of Run-2. Tier-2 to Tier-2 traffic would be the most interesting use-case for such traffic management, precisely because it is close to the users' analysis and far from the 'core' network infrastructure. As such, a better understanding of our Tier-2 to Tier-2 traffic is important. Knowing the characteristics of our data-flows can help us place our data more intelligently. Knowing how widely the data moves can help us anticipate the requirements for network capacity, and inform the dynamic data placement algorithms we expect to have in place for Run-2. This paper presents an analysis of the CMS Tier-2 traffic during Run 1.

Urban pavement surface temperature. Comparison of numerical and statistical approach

NASA Astrophysics Data System (ADS)

Marchetti, Mario; Khalifa, Abderrahmen; Bues, Michel; Bouilloud, Ludovic; Martin, Eric; Chancibaut, Katia

2015-04-01

The forecast of pavement surface temperature is very specific in the context of urban winter maintenance. to manage snow plowing and salting of roads. Such forecast mainly relies on numerical models based on a description of the energy balance between the atmosphere, the buildings and the pavement, with a canyon configuration. Nevertheless, there is a specific need in the physical description and the numerical implementation of the traffic in the energy flux balance. This traffic was originally considered as a constant. Many changes were performed in a numerical model to describe as accurately as possible the traffic effects on this urban energy balance, such as tires friction, pavement-air exchange coefficient, and infrared flux neat balance. Some experiments based on infrared thermography and radiometry were then conducted to quantify the effect fo traffic on urban pavement surface. Based on meteorological data, corresponding pavement temperature forecast were calculated and were compared with fiels measurements. Results indicated a good agreement between the forecast from the numerical model based on this energy balance approach. A complementary forecast approach based on principal component analysis (PCA) and partial least-square regression (PLS) was also developed, with data from thermal mapping usng infrared radiometry. The forecast of pavement surface temperature with air temperature was obtained in the specific case of urban configurtation, and considering traffic into measurements used for the statistical analysis. A comparison between results from the numerical model based on energy balance, and PCA/PLS was then conducted, indicating the advantages and limits of each approach.

Traffic on complex networks: Towards understanding global statistical properties from microscopic density fluctuations

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka; Thurner, Stefan; Rodgers, G. J.

2004-03-01

We study the microscopic time fluctuations of traffic load and the global statistical properties of a dense traffic of particles on scale-free cyclic graphs. For a wide range of driving rates R the traffic is stationary and the load time series exhibits antipersistence due to the regulatory role of the superstructure associated with two hub nodes in the network. We discuss how the superstructure affects the functioning of the network at high traffic density and at the jamming threshold. The degree of correlations systematically decreases with increasing traffic density and eventually disappears when approaching a jamming density Rc. Already before jamming we observe qualitative changes in the global network-load distributions and the particle queuing times. These changes are related to the occurrence of temporary crises in which the network-load increases dramatically, and then slowly falls back to a value characterizing free flow.

A novel interacting multiple model based network intrusion detection scheme

NASA Astrophysics Data System (ADS)

Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

2006-04-01

In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.

How healthy is urban horticulture in high traffic areas? Trace metal concentrations in vegetable crops from plantings within inner city neighbourhoods in Berlin, Germany.

PubMed

Säumel, Ina; Kotsyuk, Iryna; Hölscher, Marie; Lenkereit, Claudia; Weber, Frauke; Kowarik, Ingo

2012-06-01

Food production by urban dwellers is of growing importance in developing and developed countries. Urban horticulture is associated with health risks as crops in urban settings are generally exposed to higher levels of pollutants than those in rural areas. We determined the concentration of trace metals in the biomass of different horticultural crops grown in the inner city of Berlin, Germany, and analysed how the local setting shaped the concentration patterns. We revealed significant differences in trace metal concentrations depending on local traffic, crop species, planting style and building structures, but not on vegetable type. Higher overall traffic burden increased trace metal content in the biomass. The presence of buildings and large masses of vegetation as barriers between crops and roads reduced trace metal content in the biomass. Based on this we discuss consequences for urban horticulture, risk assessment, and planting and monitoring guidelines for cultivation and consumption of crops. Copyright © 2012 Elsevier Ltd. All rights reserved.

Toward observationally constrained high space and time resolution CO2 urban emission inventories

NASA Astrophysics Data System (ADS)

Maness, H.; Teige, V. E.; Wooldridge, P. J.; Weichsel, K.; Holstius, D.; Hooker, A.; Fung, I. Y.; Cohen, R. C.

2013-12-01

The spatial patterns of greenhouse gas (GHG) emission and sequestration are currently studied primarily by sensor networks and modeling tools that were designed for global and continental scale investigations of sources and sinks. In urban contexts, by design, there has been very limited investment in observing infrastructure, making it difficult to demonstrate that we have an accurate understanding of the mechanism of emissions or the ability to track processes causing changes in those emissions. Over the last few years, our team has built a new high-resolution observing instrument to address urban CO2 emissions, the BErkeley Atmospheric CO2 Observing Network (BEACON). The 20-node network is constructed on a roughly 2 km grid, permitting direct characterization of the internal structure of emissions within the San Francisco East Bay. Here we present a first assessment of BEACON's promise for evaluating the effectiveness of current and upcoming local emissions policy. Within the next several years, a variety of locally important changes are anticipated--including widespread electrification of the motor vehicle fleet and implementation of a new power standard for ships at the port of Oakland. We describe BEACON's expected performance for detecting these changes, based on results from regional forward modeling driven by a suite of projected inventories. We will further describe the network's current change detection capabilities by focusing on known high temporal frequency changes that have already occurred; examples include a week of significant freeway traffic congestion following the temporary shutdown of the local commuter rail (the Bay Area Rapid Transit system).

Performance Analysis of Modified Accelerative Preallocation MAC Protocol for Passive Star-Coupled WDMA Networks

NASA Astrophysics Data System (ADS)

Yun, Changho; Kim, Kiseon

2006-04-01

For the passive star-coupled wavelength-division multiple-access (WDMA) network, a modified accelerative preallocation WDMA (MAP-WDMA) media access control (MAC) protocol is proposed, which is based on AP-WDMA. To show the advantages of MAP-WDMA as an adequate MAC protocol for the network over AP-WDMA, the channel utilization, the channel-access delay, and the latency of MAP-WDMA are investigated and compared with those of AP-WDMA under various data traffic patterns, including uniform, quasi-uniform type, disconnected type, mesh type, and ring type data traffics, as well as the assumption that a given number of network stations is equal to that of channels, in other words, without channel sharing. As a result, the channel utilization of MAP-WDMA can be competitive with respect to that of AP-WDMA at the expense of insignificantly higher latency. Namely, if the number of network stations is small, MAP-WDMA provides better channel utilization for uniform, quasi-uniform-type, and disconnected-type data traffics at all data traffic loads, as well as for mesh and ring-type data traffics at low data traffic loads. Otherwise, MAP-WDMA only outperforms AP-WDMA for the first three data traffics at higher data traffic loads. In the aspect of channel-access delay, MAP-WDMA gives better performance than AP-WDMA, regardless of data traffic patterns and the number of network stations.

LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.

Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the datamore » in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.« less

Analysis of adaptive algorithms for an integrated communication network

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Barr, Matthew; Chong-Kwon, Kim

1985-01-01

Techniques were examined that trade communication bandwidth for decreased transmission delays. When the network is lightly used, these schemes attempt to use additional network resources to decrease communication delays. As the network utilization rises, the schemes degrade gracefully, still providing service but with minimal use of the network. Because the schemes use a combination of circuit and packet switching, they should respond to variations in the types and amounts of network traffic. Also, a combination of circuit and packet switching to support the widely varying traffic demands imposed on an integrated network was investigated. The packet switched component is best suited to bursty traffic where some delays in delivery are acceptable. The circuit switched component is reserved for traffic that must meet real time constraints. Selected packet routing algorithms that might be used in an integrated network were simulated. An integrated traffic places widely varying workload demands on a network. Adaptive algorithms were identified, ones that respond to both the transient and evolutionary changes that arise in integrated networks. A new algorithm was developed, hybrid weighted routing, that adapts to workload changes.

Modeling the coevolution of topology and traffic on weighted technological networks

NASA Astrophysics Data System (ADS)

Xie, Yan-Bo; Wang, Wen-Xu; Wang, Bing-Hong

2007-02-01

For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.

Weighted complex network analysis of the Beijing subway system: Train and passenger flows

NASA Astrophysics Data System (ADS)

Feng, Jia; Li, Xiamiao; Mao, Baohua; Xu, Qi; Bai, Yun

2017-05-01

In recent years, complex network theory has become an important approach to the study of the structure and dynamics of traffic networks. However, because traffic data is difficult to collect, previous studies have usually focused on the physical topology of subway systems, whereas few studies have considered the characteristics of traffic flows through the network. Therefore, in this paper, we present a multi-layer model to analyze traffic flow patterns in subway networks, based on trip data and an operation timetable obtained from the Beijing Subway System. We characterize the patterns in terms of the spatiotemporal flow size distributions of both the train flow network and the passenger flow network. In addition, we describe the essential interactions between these two networks based on statistical analyses. The results of this study suggest that layered models of transportation systems can elucidate fundamental differences between the coexisting traffic flows and can also clarify the mechanism that causes these differences.

Spatially- explicit Fossil Fuel Carbon Dioxide Inventories for Transportation in the U.S.

NASA Astrophysics Data System (ADS)

Hutchins, M.; Gurney, K. R.

2016-12-01

The transportation sector is the second largest source of Fossil Fuel CO2 (FFCO2) emissions, and is unique in that federal, state, and municipal levels of government are all able to enact transportation policy. However, since data related to transportation activities are reported by multiple different government agencies, the data are not always consistent. As a result, the methods and data used to inventory and account for transportation related FFCO2 emissions have important implications for both science and policy. Aggregate estimates of transportation related FFCO2 emissions can be spatially distributed using traffic data, such as the Highway Performance Monitoring System (HPMS) Average Annual Daily Traffic (AADT). There are currently two datasets that estimate the spatial distribution of transportation related FFCO2 in the United States- Vulcan 3.0 and the Database of Road Transportation Emissions (DARTE). Both datasets are at 1 km resolution, for the year 2011, and utilize HPMS AADT traffic data. However, Vulcan 3.0 and DARTE spatially distribute emissions using different methods and inputs, resulting in a number of differences. Vulcan 3.0 and DARTE estimate national transportation related FFCO2 emissions within 2.5% of each other, with more significant differences at the county and state level. The differences are most notable in urban versus rural regions, and for specific road classes. The origin of these differences are explored in depth to understand the implication of using specific data sources, such as the National Emissions Inventory and other aggregate transportation statistics from the Federal Highway Administration (FHWA). In addition to comparing Vulcan 3.0 and DARTE to each other, the results from both data sets are compared to independent traffic volume measurements acquired from the FHWA Continuous Count Station (CCS) network. The CCS records hourly traffic counts at fixed locations in space throughout the U.S. We calculate transportation related FFCO2 emissions at a CCS stations using fuel specific emissions factors combined with the raw traffic counts. The CCS network provides a unique opportunity to compare spatially explicit, "bottom-up" models of transportation related FFCO2 emissions to measured traffic volume at over 300 specific locations.

[HYGIENIC ASSESSMENT OF NOISE FACTOR OF THE LARGE CITY].

PubMed

Chubirko, M L; Stepkin, Yu I; Seredenko, O V

2015-01-01

The article is devoted to the problem of the negative impact of traffic noise on the health and living conditions of the population in conditions of the large city. Every day on the streets there are appeared more and more different modes of transport, and to date almost all transportation network has reached his traffic performance. The increase in traffic noise certainly has an impact on the human body. The most common and intense noise is caused by the traffic of urban automobile and electric transport. This is explained by the existence of the heavy traffic (2-3 thousand crews/h) on almost all main roads in historically emerged parts of the city. In addition, sources of external noise in the city can be a railway running in residential zone, access roads, industrial enterprises, located in close proximity to residential areas and on the borders of residential zones, planes of military and civil aviation. For the evaluation of the different noises sound levels were measured with the use of sound level meters. The most common parameter for the assessment ofthe noise generatedfrom motor vehicles on residential areas and usedfor the noise characteristics of the traffic flows, is the equivalent sound level/A EQ dB. This parameter is used in the majority of normative-technical documentation as hygienic noise standard. With the aim of the assessment of noise exposure there were selected 122 control points at intersections of roads of different traffic performance where there were made instrumental measurements the equivalent sound level, followed by its comparison with permissible levels.

Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

NASA Astrophysics Data System (ADS)

Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.

Traffic evacuation time under nonhomogeneous conditions.

PubMed

Fazio, Joseph; Shetkar, Rohan; Mathew, Tom V

2017-06-01

During many manmade and natural crises such as terrorist threats, floods, hazardous chemical and gas leaks, emergency personnel need to estimate the time in which people can evacuate from the affected urban area. Knowing an estimated evacuation time for a given crisis, emergency personnel can plan and prepare accordingly with the understanding that the actual evacuation time will take longer. Given the urban area to be evacuated, street widths exiting the area's perimeter, the area's population density, average vehicle occupancy, transport mode share and crawl speed, an estimation of traffic evacuation time can be derived. Peak-hour traffic data collected at three, midblock, Mumbai sites of varying geometric features and traffic composition were used in calibrating a model that estimates peak-hour traffic flow rates. Model validation revealed a correlation coefficient of +0.98 between observed and predicted peak-hour flow rates. A methodology is developed that estimates traffic evacuation time using the model.

Influence of Environmental Pollution on Leaf Properties of Urban Plane Trees, Platanus orientalis L.

PubMed Central

Pourkhabbaz, Alireza; Rastin, Nayerah; Olbrich, Andrea; Langenfeld-Heyser, Rosemarie

2010-01-01

To investigate whether leaves of plane trees (Platanus orientalis) are damaged by traffic pollution, trees from a megacity (Mashhad, Iran) and a rural area were investigated. Soil and air from the urban centre showed enrichment of several toxic elements, but only lead was enriched in leaves. Leaf size and stomata density were lower at the urban site. At the urban site leaf surfaces were heavily loaded by dust particles but the stomata were not occluded; the cuticle was thinner; other anatomical properties were unaffected suggesting that plane trees can cope with traffic exhaust in megacities. PMID:20577871

Influence of environmental pollution on leaf properties of urban plane trees, Platanus orientalis L.

PubMed

Pourkhabbaz, Alireza; Rastin, Nayerah; Olbrich, Andrea; Langenfeld-Heyser, Rosemarie; Polle, Andrea

2010-09-01

To investigate whether leaves of plane trees (Platanus orientalis) are damaged by traffic pollution, trees from a megacity (Mashhad, Iran) and a rural area were investigated. Soil and air from the urban centre showed enrichment of several toxic elements, but only lead was enriched in leaves. Leaf size and stomata density were lower at the urban site. At the urban site leaf surfaces were heavily loaded by dust particles but the stomata were not occluded; the cuticle was thinner; other anatomical properties were unaffected suggesting that plane trees can cope with traffic exhaust in megacities.

A video-based real-time adaptive vehicle-counting system for urban roads.

PubMed

Liu, Fei; Zeng, Zhiyuan; Jiang, Rong

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.

A video-based real-time adaptive vehicle-counting system for urban roads

PubMed Central

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios. PMID:29135984

Establishing a link between vehicular PM sources and PM measurements in urban street canyons.

PubMed

Eisner, Alfred D; Richmond-Bryant, Jennifer; Wiener, Russell W; Hahn, Intaek; Drake-Richman, Zora E; Ellenson, William D

2009-12-01

The Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, conducted in Brooklyn, NY, USA, in 2005, was designed with multiple goals in mind, two of which were contaminant source characterization and street canyon transport and dispersion monitoring. In the portion of the study described here, synchronized wind velocity and azimuth as well as particulate matter (PM) concentrations at multiple locations along 33rd Street were used to determine the feasibility of using traffic emissions in a complex urban topography as a sole tracer for studying urban contaminant transport. We demonstrate in this paper that it is possible to link downwind concentrations of contaminants in an urban street canyon to the vehicular traffic cycle using Eigen-frequency analysis. In addition, multivariable circular histograms are used to establish directional frequency maxima for wind velocity and contaminant concentration.

Network traffic behaviour near phase transition point

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-03-01

We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.

Relationship between road traffic noisescape and urban form in Hong Kong.

PubMed

Lam, Kin-Che; Ma, Weichun; Chan, Pak Kin; Hui, Wing Chi; Chung, King Lam; Chung, Yi-tak Teresa; Wong, Chun Yin; Lin, Hui

2013-12-01

This paper reports on a study which explored the possible relationship between road traffic noisescape and urban form in Hong Kong. A total of 212 residential complexes from 11 contrasting urban forms were sampled, and their noise levels assessed both at dwelling and neighbourhood scales by noise mapping. Its findings indicate that residential complexes with different urban forms have significantly different noisescape attributes. There is a strong correlation between the noise characteristics and morphological indicators at the dwelling scale. A less obstreperous noisescape is associated with urban forms with lower road and building densities, and with building arrangements which provide self-noise screening. These findings suggest that urban form is an influential determinant of the noisescape in the urban environment, and they point to the need to rethink the conventional approach to managing the urban acoustic environment.

Realities of weather extremes on daily life in urban India - How quantified impacts infer sensible adaptation options

NASA Astrophysics Data System (ADS)

Reckien, D.

2012-12-01

Emerging and developing economies are currently undergoing one of the profoundest socio-spatial transitions in their history, with strong urbanization and weather extremes bringing about changes in the economy, forms of living and living conditions, but also increasing risks and altered social divides. The impacts of heat waves and strong rain events are therefore differently perceived among urban residents. Addressing the social differences of climate change impacts1 and expanding targeted adaptation options have emerged as urgent policy priorities, particularly for developing and emerging economies2. This paper discusses the perceived impacts of weather-related extreme events on different social groups in New Delhi and Hyderabad, India. Using network statistics and scenario analysis on Fuzzy Cognitive Maps (FCMs) as part of a vulnerability analysis, the investigation provides quantitative and qualitative measures to compare impacts and adaptation strategies for different social groups. Impacts of rain events are stronger than those of heat in both cities and affect the lower income classes particularly. Interestingly, the scenario analysis (comparing altered networks in which the alteration represents a possible adaptation measure) shows that investments in the water infrastructure would be most meaningful and more effective than investments in, e.g., the traffic infrastructure, despite the stronger burden from traffic disruptions and the resulting concentration of planning and policy on traffic ease and investments. The method of Fuzzy Cognitive Mapping offers a link between perception and modeling, and the possibility to aggregate and analyze the views of a large number of stakeholders. Our research has shown that planners and politicians often know about many of the problems, but are often overwhelmed by the problems in their respective cities and look for a prioritization of adaptation options. FCM provides this need and identifies priority adaptation options when resources are scarce. 1 Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) (2007) Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge New York. 2 TERI (2007) Adaptation to Climate Change in the context of Sustainable Development. Background Paper to the conference ''Climate Change and Sustainable Development: An international workshop to strengthen research and understanding'', 7-8 April 2006, The Energy and Resources Institute, New Delhi.

Improved Efficient Routing Strategy on Scale-Free Networks

NASA Astrophysics Data System (ADS)

Jiang, Zhong-Yuan; Liang, Man-Gui

Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási-Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

Large-scale measurement and modeling of backbone Internet traffic

NASA Astrophysics Data System (ADS)

Roughan, Matthew; Gottlieb, Joel

2002-07-01

There is a brewing controversy in the traffic modeling community concerning how to model backbone traffic. The fundamental work on self-similarity in data traffic appears to be contradicted by recent findings that suggest that backbone traffic is smooth. The traffic analysis work to date has focused on high-quality but limited-scope packet trace measurements; this limits its applicability to high-speed backbone traffic. This paper uses more than one year's worth of SNMP traffic data covering an entire Tier 1 ISP backbone to address the question of how backbone network traffic should be modeled. Although the limitations of SNMP measurements do not permit us to comment on the fine timescale behavior of the traffic, careful analysis of the data suggests that irrespective of the variation at fine timescales, we can construct a simple traffic model that captures key features of the observed traffic. Furthermore, the model's parameters are measurable using existing network infrastructure, making this model practical in a present-day operational network. In addition to its practicality, the model verifies basic statistical multiplexing results, and thus sheds deep insight into how smooth backbone traffic really is.

Statistical Traffic Anomaly Detection in Time-Varying Communication Networks

DTIC Science & Technology

2015-02-01

methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types

Statistical Traffic Anomaly Detection in Time Varying Communication Networks

DTIC Science & Technology

2015-02-01

methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types

Integrated coding-aware intra-ONU scheduling for passive optical networks with inter-ONU traffic

NASA Astrophysics Data System (ADS)

Li, Yan; Dai, Shifang; Wu, Weiwei

2016-12-01

Recently, with the soaring of traffic among optical network units (ONUs), network coding (NC) is becoming an appealing technique for improving the performance of passive optical networks (PONs) with such inter-ONU traffic. However, in the existed NC-based PONs, NC can only be implemented by buffering inter-ONU traffic at the optical line terminal (OLT) to wait for the establishment of coding condition, such passive uncertain waiting severely limits the effect of NC technique. In this paper, we will study integrated coding-aware intra-ONU scheduling in which the scheduling of inter-ONU traffic within each ONU will be undertaken by the OLT to actively facilitate the forming of coding inter-ONU traffic based on the global inter-ONU traffic distribution, and then the performance of PONs with inter-ONU traffic can be significantly improved. We firstly design two report message patterns and an inter-ONU traffic transmission framework as the basis for the integrated coding-aware intra-ONU scheduling. Three specific scheduling strategies are then proposed for adapting diverse global inter-ONU traffic distributions. The effectiveness of the work is finally evaluated by both theoretical analysis and simulations.

Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerner, Boris S.

It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliable used for control and optimization in traffic networks. It is shown that generally accepted fundamentals and methodologies of traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of traffic and transportation theory belong (i) Lighthill-Whitham-Richards (LWR) theory, (ii) the General Motors (GM) model class (formore » example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular stochastic value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of traffic and transportation theory, we discuss three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.« less

How congestion shapes cities: from mobility patterns to scaling

PubMed Central

Louf, Rémi; Barthelemy, Marc

2014-01-01

The recent availability of data for cities has allowed scientists to exhibit scalings which present themselves in the form of a power-law dependence on population of various socio-economical and structural indicators. We propose here a stochastic theory of urban growth which accounts for some of the observed scalings and we confirm these predictions on US and OECD empirical data. In particular, we show that the dependence on population size of the total number of miles driven daily, the total length of the road network, the total traffic delay, the total consumption of gasoline, the quantity of CO2 emitted and the relation between area and population of cities, are all governed by a single parameter which characterizes the sensitivity to congestion. Our results suggest that diseconomies associated with congestion scale superlinearly with population size, implying that –despite polycentrism– cities whose transportation infrastructure rely heavily on traffic sensitive modes are unsustainable. PMID:24990624

Traffic sign recognition by color segmentation and neural network

NASA Astrophysics Data System (ADS)

Surinwarangkoon, Thongchai; Nitsuwat, Supot; Moore, Elvin J.

2011-12-01

An algorithm is proposed for traffic sign detection and identification based on color filtering, color segmentation and neural networks. Traffic signs in Thailand are classified by color into four types: namely, prohibitory signs (red or blue), general warning signs (yellow) and construction area warning signs (amber). A color filtering method is first used to detect traffic signs and classify them by type. Then color segmentation methods adapted for each color type are used to extract inner features, e.g., arrows, bars etc. Finally, neural networks trained to recognize signs in each color type are used to identify any given traffic sign. Experiments show that the algorithm can improve the accuracy of traffic sign detection and recognition for the traffic signs used in Thailand.

Optimal topologies for maximizing network transmission capacity

NASA Astrophysics Data System (ADS)

Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.

2018-04-01

It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.

Fast Drawing of Traffic Sign Using Mobile Mapping System

NASA Astrophysics Data System (ADS)

Yao, Q.; Tan, B.; Huang, Y.

2016-06-01

Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a traffic sign.The proposed algorithm is tested with a diverse set of images that are taken inWuhan, China with theMMS ofWuhan University. Experimental results demonstrate that the proposed algorithm can detect traffic signs at the rate of over 80% in around 10 milliseconds. It is promising for the large-scale traffic sign survey and change detection using the mobile mapping system.

Traffic engineering and regenerator placement in GMPLS networks with restoration

NASA Astrophysics Data System (ADS)

Yetginer, Emre; Karasan, Ezhan

2002-07-01

In this paper we study regenerator placement and traffic engineering of restorable paths in Generalized Multipro-tocol Label Switching (GMPLS) networks. Regenerators are necessary in optical networks due to transmission impairments. We study a network architecture where there are regenerators at selected nodes and we propose two heuristic algorithms for the regenerator placement problem. Performances of these algorithms in terms of required number of regenerators and computational complexity are evaluated. In this network architecture with sparse regeneration, offline computation of working and restoration paths is studied with bandwidth reservation and path rerouting as the restoration scheme. We study two approaches for selecting working and restoration paths from a set of candidate paths and formulate each method as an Integer Linear Programming (ILP) prob-lem. Traffic uncertainty model is developed in order to compare these methods based on their robustness with respect to changing traffic patterns. Traffic engineering methods are compared based on number of additional demands due to traffic uncertainty that can be carried. Regenerator placement algorithms are also evaluated from a traffic engineering point of view.

Common Traffic Violations of Bus Drivers in Urban China: An Observational Study.

PubMed

Wang, Qiqi; Zhang, Wei; Yang, Rendong; Huang, Yuanxiu; Zhang, Lin; Ning, Peishan; Cheng, Xunjie; Schwebel, David C; Hu, Guoqing; Yao, Hongyan

2015-01-01

To report common traffic violations in bus drivers and the factors that influence those violations in urban China. We conducted an observational study to record three types of traffic violations among bus drivers in Changsha City, China: illegal stopping at bus stations, violating traffic light signals, and distracted driving. The behaviors of bus drivers on 32 routes (20% of bus routes in the city) were observed. A two-level Poisson regression examined factors that predicted bus driver violations. The incidence of illegal stopping at bus stations was 20.2%. Illegal stopping was less frequent on weekends, sunny days, and at stations with cameras, with adjusted incidence rate ratios (IRRs) of 0.81, 0.65 and 0.89, respectively. The incidence of violating traffic light signals was 2.2%, and was lower on cloudy than sunny days (adjusted IRR: 0.60). The incidence of distracted driving was 3.3%. The incidence of distracted driving was less common on cloudy days, rainy or snowy days, and foggy/windy/dusty days compared to sunny days, with adjusted IRRs of 0.54, 0.55 and 0.07, respectively. Traffic violations are common in bus drivers in urban China and they are associated with the date, weather, and presence of traffic cameras at bus station. Further studies are recommended to understand the behavioral mechanisms that may explain bus driver violations and to develop feasible prevention measures.

Investigation of schedules for traffic signal timing optimization.

DOT National Transportation Integrated Search

2005-01-01

Traffic signal optimization is recognized as one of the most cost-effective ways to improve urban mobility; however the extent of the benefits realized could significantly depend on how often traffic signal re-optimization occurs. Using a case study ...

Manual of Transit and Traffic Studies

DOT National Transportation Integrated Search

1947-01-01

This first edition of the "Manual of Transit and Traffic Studies" has been designed to assist transit companies and traffic engineers in the conduct and application of studies deemed essential to a solution of present and future problems of urban tra...

Value of Information and Information Services

DOT National Transportation Integrated Search

1975-10-01

The report describes the salient features of the SCOT (Simulation of Corridor Traffic) model and a successful calibration and validation. SCOT is a computer model that may be applied to an urban traffic corridor and will simulate vehicular traffic on...

Traffic flow simulation for an urban freeway corridor

DOT National Transportation Integrated Search

1998-01-01

The objective of this paper is to develop a realistic and operational macroscopic traffic flow simulation model which requires relatively less data collection efforts. Such a model should be capable of delineating the dynamics of traffic flow created...

Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods.

PubMed

Arcos-García, Álvaro; Álvarez-García, Juan A; Soria-Morillo, Luis M

2018-03-01

This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial and temporal disaggregation of the on-road vehicle emission inventory in a medium-sized Andean city. Comparison of GIS-based top-down methodologies

NASA Astrophysics Data System (ADS)

Gómez, C. D.; González, C. M.; Osses, M.; Aristizábal, B. H.

2018-04-01

Emission data is an essential tool for understanding environmental problems associated with sources and dynamics of air pollutants in urban environments, especially those emitted from vehicular sources. There is a lack of knowledge about the estimation of air pollutant emissions and particularly its spatial and temporal distribution in South America, mainly in medium-sized cities with population less than one million inhabitants. This work performed the spatial and temporal disaggregation of the on-road vehicle emission inventory (EI) in the medium-sized Andean city of Manizales, Colombia, with a spatial resolution of 1 km × 1 km and a temporal resolution of 1 h. A reported top-down methodology, based on the analysis of traffic flow levels and road network distribution, was applied. Results obtained allowed the identification of several hotspots of emission at the downtown zone and the residential and commercial area of Manizales. Downtown exhibited the highest percentage contribution of emissions normalized by its total area, with values equal to 6% and 5% of total CO and PM10 emissions per km2 respectively. These indexes were higher than those obtained in residential-commercial area with values of 2%/km2 for both pollutants. Temporal distribution showed strong relationship with driving patterns at rush hours, as well as an important influence of passenger cars and motorcycles in emissions of CO both at downtown and residential-commercial areas, and the impact of public transport in PM10 emissions in the residential-commercial zone. Considering that detailed information about traffic counts and road network distribution is not always available in medium-sized cities, this work compares other simplified top-down methods for spatially assessing the on-road vehicle EI. Results suggested that simplified methods could underestimate the spatial allocation of downtown emissions, a zone dominated by high traffic of vehicles. The comparison between simplified methods based on total traffic counts and road density distribution suggested that the use of total traffic counts in a simplified form could enhance higher uncertainties in the spatial disaggregation of emissions. Results obtained could add new information that help to improve the air pollution management system in the city and contribute to local public policy decisions. Additionally, this work provides appropriate resolution emission fluxes for ongoing research in atmospheric modeling in the city, with the aim to improve the understanding of transport, transformation and impacts of pollutant emissions in urban air quality.

Traffic pollution exposure is associated with altered brain connectivity in school children.

PubMed

Pujol, Jesus; Martínez-Vilavella, Gerard; Macià, Dídac; Fenoll, Raquel; Alvarez-Pedrerol, Mar; Rivas, Ioar; Forns, Joan; Blanco-Hinojo, Laura; Capellades, Jaume; Querol, Xavier; Deus, Joan; Sunyer, Jordi

2016-04-01

Children are more vulnerable to the effects of environmental elements due to their active developmental processes. Exposure to urban air pollution has been associated with poorer cognitive performance, which is thought to be a result of direct interference with brain maturation. We aimed to assess the extent of such potential effects of urban pollution on child brain maturation using general indicators of vehicle exhaust measured in the school environment and a comprehensive imaging evaluation. A group of 263 children, aged 8 to 12 years, underwent MRI to quantify regional brain volumes, tissue composition, myelination, cortical thickness, neural tract architecture, membrane metabolites, functional connectivity in major neural networks and activation/deactivation dynamics during a sensory task. A combined measurement of elemental carbon and NO2 was used as a putative marker of vehicle exhaust. Air pollution exposure was associated with brain changes of a functional nature, with no evident effect on brain anatomy, structure or membrane metabolites. Specifically, a higher content of pollutants was associated with lower functional integration and segregation in key brain networks relevant to both inner mental processes (the default mode network) and stimulus-driven mental operations. Age and performance (motor response speed) both showed the opposite effect to that of pollution, thus indicating that higher exposure is associated with slower brain maturation. In conclusion, urban air pollution appears to adversely affect brain maturation in a critical age with changes specifically concerning the functional domain. Copyright © 2016 Elsevier Inc. All rights reserved.

Traffic signal synchronization in the saturated high-density grid road network.

PubMed

Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

Spatial analysis of bus transport networks using network theory

NASA Astrophysics Data System (ADS)

Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

2018-07-01

In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison of the simulation and the empirical data provides useful information on how bus operators can better plan their routes and deploy stops considering the geographically significant nodes.

Recognition Stage for a Speed Supervisor Based on Road Sign Detection

PubMed Central

Carrasco, Juan-Pablo; de la Escalera, Arturo; Armingol, José María

2012-01-01

Traffic accidents are still one of the main health problems in the World. A number of measures have been applied in order to reduce the number of injuries and fatalities in roads, i.e., implementation of Advanced Driver Assistance Systems (ADAS) based on image processing. In this paper, a real time speed supervisor based on road sign recognition that can work both in urban and non-urban environments is presented. The system is able to recognize 135 road signs, belonging to the danger, yield, prohibition obligation and indication types, and sends warning messages to the driver upon the combination of two pieces of information: the current speed of the car and the road sign symbol. The core of this paper is the comparison between the two main methods which have been traditionally used for detection and recognition of road signs: template matching (TM) and neural networks (NN). The advantages and disadvantages of the two approaches will be shown and commented. Additionally we will show how the use of well-known algorithms to avoid illumination issues reduces the amount of images needed to train a neural network.

Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network

NASA Astrophysics Data System (ADS)

Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang

2015-12-01

Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.

Road network - land use interaction model: Malang City in Indonesian case

NASA Astrophysics Data System (ADS)

Waloejo, B. S.

2017-06-01

Urban population in Indonesia is significantly increasing from 44% of total population in 2002 to approximately 60% in 2015. Rapid population growth has resulted in rapid urban land use changes. The problems became more complicated since the changes created mixed use development along the main urban corridors that resulted in higher trip generation and attraction while urban land very limited that made road widening and creation of new road less possible. This led to an accumulation of movement, worse road’s level of service and congestion in the main urban corridor. The aims of the research are to analyse trip generation/attraction of the mixed- land uses of the main corridors Malang City; and to formulate road network - land use interaction model in the case of Malang (a nearly 1 million population city in 2015). The selected corridors in Malang City a main road in the west district of Malang City - Indonesia. Correlational method (Pearson Product Moment) and regression method (stepwise, anova for land use’s trip generation/attraction), and analysis of road’s level of service (LOS), using Indonesian Road Capacity Manual, are employed in this research. The research formulated the interaction model as: \\begin{eqnarray}\\begin{array}{lll}{V}{total} & = & \\displaystyle \\sum {V}{internal}+\\displaystyle \\sum {V}{external} {Where}\\ \\displaystyle \\sum {V}{internal} & = & {e}{residential}{Y}{residential}+{e}{schools}{Y}{schools}+{e}{unis}{Y}{unis}+{e}{offices}{Y}{offices}+{e}{hospital}{Y}{hospital}+{e}{chemists}{Y}{chemists}+{e}{commercial}{Y}{commercial}+{e}{market}{Y}{market}+{e}{fuel {station}}{Y}{fuel {station}}+{e}{bus {station}}{Y}{bus {station}} {and}\\ \\displaystyle \\sum {V}{external} & = & \\displaystyle \\sum {V}{local {roads}}+{V}{continous {traffic} {flow}}\\end{array}\\end{eqnarray} The research showed that V_total=23,033 car unit/day (internal) + 32,746 car unit/day (external) = 55,779 car unit/day. The trip higher than the road’s capacity (C) which 40.695 car unit/day. The levels of services of road’s segments dominantly F (congested). The simulation of the model showed that traffic engineering can be used to increase road’s capacity while land use changes (reduction of the variety of mixed land uses), particularly mix land uses at frontage area, can improve level of services (from F to C).

Urban compaction vs city sprawl: impact of road traffic on air quality in the greater Paris

NASA Astrophysics Data System (ADS)

Etuman Arthur, Elessa; Isabelle, Coll; Vincent, Viguie; Nicolas, Coulombel; Julie, Prud'homme

2017-04-01

Urban pollution remains a major sanitary and economic concern. In France, particulate pollution is known to cause 48,000 premature deaths every year (Santé Publique France, 2016), while the economic cost of air pollution reaches almost 25 billion euros per year (CGDD, 2012). In the Greater Paris, despite strengthened emission standards, restricted traffic areas, car-sharing and incentives for electric vehicle use, road transport plays a substantial role in the exposure of inhabitants to high levels of pollutants. In this context, urban planning could possibly constitute an innovative strategy to reduce emissions from road traffic, through its actions on transport demand, travel distances, modal shift (public transportation, cycling, walking...) or even proximity to emitters. We have developed a multi-scalar modeling of urban pollution by coupling an urban economic growth model NEDUM (CIRED), a model for urban mobility (LISA), a traffic emission model (LISA) and the CHIMERE Chemistry-Transport model (CTM) for air quality simulation (LISA). The innovative aspect of this modeling system is to integrate into a classic CTM the mechanisms underlying the dynamics of an urban system. This way, we establish a quantitative and comprehensive link between a given urban scenario, the associated public and individual transport matrix, and local air quality. We then make it possible to highlight the levers of energy consumption reductions inside compact or sprawled cities. We have been working on the Ile de France region (centered on the Paris agglomeration) which relies on a broad urban structure of megacity, a high density of housing and an expanding urban peripheral zone, clearly raising the issue of transport demand, mobility and traffic congestion. Two scenarios, considering opposite urban development policies from the 1960s to 2010, have been simulated over the whole modelling chain. The first one promotes a dense and compact city while the second favors city spread, though restricted by a green belt. In our results, we compare the local air quality simulated in these scenarios with our reference situation (the current 2010 situation). The spreading or densification of the city contribute a little to the air quality and therefore a reflection on a real mix of the urban canvas is probably an influencing factor for the reduction of the motorized mobility. We should also consider more advanced scenarios (in the course of production) for the reduction of individual transport like encouraging car-pooling, which has a maximum daily trip reduction potential of 16% in urban areas (CGDD, 2014).

Capacity-constrained traffic assignment in networks with residual queues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lam, W.H.K.; Zhang, Y.

2000-04-01

This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less

Cooperative Learning for Distributed In-Network Traffic Classification

NASA Astrophysics Data System (ADS)

Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.

2017-04-01

Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

Research on spatial difference in the effecting factors of the urban flow

NASA Astrophysics Data System (ADS)

Liang, Jian; Li, Feixue; Xu, Jiangang; Li, Manchun

2007-06-01

Urban flow is a phenomenon of the interaction and relation between the cities in the region based on the transport network and urban synthetic strength. And, because of the difference in traffic conditions and the level of economic development in different city, the intensity of the urban flow of each city is different and the primary effecting factor is dissimilar. The traditional analysis on the effecting factors of urban flow concerns the background of the entire region as a whole entity, which would be too vague and ignore the difference in the effecting factors of different cities as well as the micro differences and spatial non-stationarity in the dominant factor. The research on spatial difference in the effecting factors of the urban flow in this paper focused on the analysis of the diverse effecting factors of urban flow caused by the regional disparity; found out the primary factors; and analyzed the spatial characteristics of effecting factors using GIS. We established a mathematical model, which was applied to the urban agglomeration of the Yangtze River Delta, the intensity of the urban flow of every city in this district was figured and the regression model was constructed. The principal effecting factor of the urban flow of every city and its characteristic of the spatial distribution was analyzed. we summarized the effecting factors of the urban flow is an indication of the persistence of spatial difference among Yangtze River Delta, and the spatial pattern of it was investigated.

General Dynamics of Topology and Traffic on Weighted Technological Networks

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Wang, Bing-Hong; Hu, Bo; Yan, Gang; Ou, Qing

2005-05-01

For most technical networks, the interplay of dynamics, traffic, and topology is assumed crucial to their evolution. In this Letter, we propose a traffic-driven evolution model of weighted technological networks. By introducing a general strength-coupling mechanism under which the traffic and topology mutually interact, the model gives power-law distributions of degree, weight, and strength, as confirmed in many real networks. Particularly, depending on a parameter W that controls the total weight growth of the system, the nontrivial clustering coefficient C, degree assortativity coefficient r, and degree-strength correlation are all consistent with empirical evidence.

Outside and inside noise exposure in urban and suburban areas

Treesearch

Dwight E. Bishop; Myles A. Simpson

1977-01-01

In urban and suburban areas of the United States (away from major airports), the outdoor noise environment usually depends strongly on local vehicular traffic. By relating traffic flow to population density, a model of outdoor noise exposure has been developed for estimating the cumulative 24-hour noise exposure based upon the population density of the area. This noise...

Traveller Information System for Heterogeneous Traffic Condition: A Case Study in Thiruvananthapuram City, India

NASA Astrophysics Data System (ADS)

Satyakumar, M.; Anil, R.; Sreeja, G. S.

2017-12-01

Traffic in Kerala has been growing at a rate of 10-11% every year, resulting severe congestion especially in urban areas. Because of the limitation of spaces it is not always possible to construct new roads. Road users rely on travel time information for journey planning and route choice decisions, while road system managers are increasingly viewing travel time as an important network performance indicator. More recently Advanced Traveler Information Systems (ATIS) are being developed to provide real-time information to roadway users. For ATIS various methodologies have been developed for dynamic travel time prediction. For this work the Kalman Filter Algorithm was selected for dynamic travel time prediction of different modes. The travel time data collected using handheld GPS device were used for prediction. Congestion Index were calculated and Range of CI values were determined according to the percentage speed drop. After prediction using Kalman Filter, the predicted values along with the GPS data was integrated to GIS and using Network Analysis of ArcGIS the offline route navigation guide was prepared. Using this database a program for route navigation based on travel time was developed. This system will help the travelers with pre-trip information.

Recognition of Damaged Arrow-Road Markings by Visible Light Camera Sensor Based on Convolutional Neural Network.

PubMed

Vokhidov, Husan; Hong, Hyung Gil; Kang, Jin Kyu; Hoang, Toan Minh; Park, Kang Ryoung

2016-12-16

Automobile driver information as displayed on marked road signs indicates the state of the road, traffic conditions, proximity to schools, etc. These signs are important to insure the safety of the driver and pedestrians. They are also important input to the automated advanced driver assistance system (ADAS), installed in many automobiles. Over time, the arrow-road markings may be eroded or otherwise damaged by automobile contact, making it difficult for the driver to correctly identify the marking. Failure to properly identify an arrow-road marker creates a dangerous situation that may result in traffic accidents or pedestrian injury. Very little research exists that studies the problem of automated identification of damaged arrow-road marking painted on the road. In this study, we propose a method that uses a convolutional neural network (CNN) to recognize six types of arrow-road markings, possibly damaged, by visible light camera sensor. Experimental results with six databases of Road marking dataset, KITTI dataset, Málaga dataset 2009, Málaga urban dataset, Naver street view dataset, and Road/Lane detection evaluation 2013 dataset, show that our method outperforms conventional methods.

Recognition of Damaged Arrow-Road Markings by Visible Light Camera Sensor Based on Convolutional Neural Network

PubMed Central

Vokhidov, Husan; Hong, Hyung Gil; Kang, Jin Kyu; Hoang, Toan Minh; Park, Kang Ryoung

2016-01-01

Automobile driver information as displayed on marked road signs indicates the state of the road, traffic conditions, proximity to schools, etc. These signs are important to insure the safety of the driver and pedestrians. They are also important input to the automated advanced driver assistance system (ADAS), installed in many automobiles. Over time, the arrow-road markings may be eroded or otherwise damaged by automobile contact, making it difficult for the driver to correctly identify the marking. Failure to properly identify an arrow-road marker creates a dangerous situation that may result in traffic accidents or pedestrian injury. Very little research exists that studies the problem of automated identification of damaged arrow-road marking painted on the road. In this study, we propose a method that uses a convolutional neural network (CNN) to recognize six types of arrow-road markings, possibly damaged, by visible light camera sensor. Experimental results with six databases of Road marking dataset, KITTI dataset, Málaga dataset 2009, Málaga urban dataset, Naver street view dataset, and Road/Lane detection evaluation 2013 dataset, show that our method outperforms conventional methods. PMID:27999301

Development of «Park-and-Ride» system as a tool for sustainable access control managing

NASA Astrophysics Data System (ADS)

Danilina, Nina; Vlasov, Denis

2017-10-01

Large cities, whereby people use private transport, are facing the same challenges related to traffic congestion, reliability of public transportation and parking demand. Managing urban traffic and transport has become the most relevant police in transport planning. The article deals with the potential for further implementation in Russian Federation of «Park-and- Ride» recognized as an essential part of the overall transport and parking offer and successful planning tool to reducing congestion for any urban area around the world. The studies have been carried out in Moscow acknowledged as the city core of Moscow agglomeration — the largest and most populous in Russia. The research aims to support for the development of «Park-and-Ride» system applying the methodical approach adapted by the authors for the study to make it relevant for cities. A three-steps access control is offered to reduce private cars use in the city center. The results of the studies shows that such traffic management tool can help successfully in balancing the traffic demand and supply and, consequently, in resolving transport congestion and the number of coherent social, urban and economic challenges addressed to the sustainable development of urban areas.

Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network

NASA Astrophysics Data System (ADS)

Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.

2016-12-01

City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.

Influence of urban vegetation on air pollution and noise exposure - A case study in Gothenburg, Sweden.

PubMed

Klingberg, Jenny; Broberg, Malin; Strandberg, Bo; Thorsson, Pontus; Pleijel, Håkan

2017-12-01

Air pollution levels (NO 2 , PAHs, O 3 ) were investigated, before (BLE) and after (ALE) leaf emergence, in the urban landscape of Gothenburg, Sweden. The aims were to study the 1) spatial and temporal variation in pollution levels between urban green areas, 2) effect of urban vegetation on air pollution levels at the same distance from a major emission source (traffic route), 3) improvement of urban air quality in urban parks compared to adjacent sites near traffic, 4) correlation between air pollution and noise in a park. O 3 varied little over the urban landscape. NO 2 varied strongly and was higher in situations strongly influenced by traffic. Four PAH variables were included: total PAH, total particle-bound PAH, the quantitatively important gaseous phenanthrene and the highly toxic particle-bound benzo(a)pyrene. The variation of PAHs was similar to NO 2 , but for certain PAHs the difference between highly and less polluted sites was larger than for NO 2 . At a vegetated site, NO 2 and particulate PAH levels were lower than at a non-vegetated site at a certain distance from a busy traffic route. This effect was significantly larger ALE compared to BLE for NO 2 , indicating green leaf area to be highly significant factor for air quality improvement. For particulate PAHs, the effect was similar BLE and ALE, indicating that tree bark and branches also could be an important factor in reducing air pollution. Parks represented considerably cleaner local environments (park effect), which is likely to be a consequence of both a dilution (distance effect) and deposition. Noise and air pollution (NO 2 and PAH) levels were strongly correlated. Comparison of noise levels BLE and ALE also showed that the presence of leaves significantly reduced noise levels. Our results are evidence that urban green spaces are beneficial for urban environmental quality, which is important to consider in urban planning. Copyright © 2017 Elsevier B.V. All rights reserved.

Luteinizing hormone (LH) levels in male workers exposed to urban stressors.

PubMed

Tomao, Enrico; Tomei, Gianfranco; Rosati, Maria Valeria; Caciari, Tiziana; Danese, Daniele; Gamberale, Daniele; Vacca, Daniele; Palermo, Paola; Anzelmo, Vincenza; Tomei, Francesco

2009-08-01

The aim of the study is to evaluate if occupational exposure to urban stressors could cause alterations in luteinizing hormone (LH) plasma levels in male traffic policemen vs. administrative staff of Municipal Police.After excluding the subjects with the main confounding factors, male traffic police and administrative staff of Municipal Police were matched by age, working life, body mass index (BMI), alcohol drinking habit, cigarette smoking habit and habitual consumption of Italian coffee.In 166 male traffic police mean LH values were significantly higher compared to 166 male administrative employees. The distribution of LH values in traffic police and in administrative employees was statistically significant.Our results suggest that recent exposure to urban stressors (chemical, physical and psycho-social) can alter the plasma concentration of LH. In agreement with our previous research, levels of plasma LH may be used as early biological markers, valuable for the group, used in occupational set before the appearance of the disease.

Forecasting short-term data center network traffic load with convolutional neural networks.

PubMed

Mozo, Alberto; Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution.

Switching performance of OBS network model under prefetched real traffic

NASA Astrophysics Data System (ADS)

Huang, Zhenhua; Xu, Du; Lei, Wen

2005-11-01

Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.

Forecasting short-term data center network traffic load with convolutional neural networks

PubMed Central

Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution. PMID:29408936

Assessment of Indoor and Outdoor PM Species at Schools and Residences in a High-Altitude Ecuadorian Urban Center

PubMed Central

Raysoni, Amit U.; Armijos, Rodrigo X.; Weigel, M. Margaret; Montoya, Teresa; Eschanique, Patricia; Racines, Marcia; Li, Wen-Whai

2016-01-01

An air monitoring campaign to assess children’s environmental exposures in schools and residences, both indoors and outdoors, was conducted in 2010 in three low-income neighborhoods in Z1(north), Z2(central), and Z3(southeast) zones of Quito, Ecuador - a major urban center of 2.2 million inhabitants situated 2850 meters above sea level in a narrow mountainous basin. Z1 zone, located in northern Quito, historically experienced emissions from quarries and moderate traffic. Z2 zone was influenced by heavy traffic in contrast to Z3 zone which experienced low traffic densities. Weekly averages of PM samples were collected at schools (one in each zone) and residences (Z1=47, Z2=45, and Z3=41) every month, over a twelve-month period at the three zones. Indoor PM2.5 concentrations ranged from 10.6±4.9 μg/m3 (Z1 school) to 29.0±30.5 μg/m3 (Z1 residences) and outdoor PM2.5 concentrations varied from 10.9±3.2 μg/m3 (Z1 school) to 14.3±10.1 μg/m3 (Z2 residences), across the three zones. The lowest values for PM10–2.5 for indoor and outdoor microenvironments were recorded at Z2 school, 5.7±2.8 μg/m3 and 7.9±2.2 μg/m3, respectively. Outdoor school PM concentrations exhibited stronger associations with corresponding indoor values making them robust proxies for indoor exposures in naturally ventilated Quito public schools. Correlation analysis between the school and residential PM size fractions and the various pollutant and meteorological parameters from central ambient monitoring (CAM) sites suggested varying degrees of temporal relationship. Strong positive correlation was observed for outdoor PM2.5 at Z2 school and its corresponding CAM site (r=0.77) suggesting common traffic related emissions. Spatial heterogeneity in PM2.5 concentrations between CAM network and sampled sites was assessed using Coefficient of Divergence (COD) analysis. COD values were lower when CAM sites were paired with outdoor measurements (< 0.2) and higher when CAM and indoor values were compared (> 0.2), suggesting that CAM network in Quito may not represent actual indoor exposures. PMID:27149144

High-speed and high-fidelity system and method for collecting network traffic

DOEpatents

Weigle, Eric H [Los Alamos, NM

2010-08-24

A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.

Queuing theory models for computer networks

NASA Technical Reports Server (NTRS)

Galant, David C.

1989-01-01

A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

Traffic prediction using wireless cellular networks : final report.

DOT National Transportation Integrated Search

2016-03-01

The major objective of this project is to obtain traffic information from existing wireless : infrastructure. : In this project freeway traffic is identified and modeled using data obtained from existing : wireless cellular networks. Most of the prev...

Impact of urban land use on the bacterial phyllosphere of ivy (Hedera sp.)

NASA Astrophysics Data System (ADS)

Smets, Wenke; Wuyts, Karen; Oerlemans, Eline; Wuyts, Sander; Denys, Siegfried; Samson, Roeland; Lebeer, Sarah

2016-12-01

The surface of the aerial parts of the plant, also termed the phyllosphere, is a selective habitat for microbes. The bacterial composition of the phyllosphere depends on host plant species, leaf characteristics, season, climate, and geographic location of the host plant. In this study, we investigated the effect of an urban environment on the bacterial composition of phyllosphere communities. We performed a passive biomonitoring experiment in which leaves were sampled from ivy (Hedera sp.), a common evergreen climber species, in urban and non-urban locations. Exposure to traffic-generated particulate matter was estimated using leaf biomagnetic analyses. The bacterial community composition was determined using 16S rRNA gene sequencing on the Illumina MiSeq. The phyllosphere microbial communities of ivy differed greatly between urban and non-urban locations, as we observed a shift in several of the dominant taxa: Beijerinckia and Methylocystaceae were most abundant in the non-urban phyllosphere, whereas Hymenobacter and Sphingomonadaceae were dominating the urban ivy phyllosphere. The richness, diversity and composition of the communities showed greater variability in the urban than in the non-urban locations, where traffic-generated PM was lower. Interestingly, the relative abundances of eight of the ten most dominant taxa correlated well with leaf magnetism, be it positive or negative. The results of this study indicate that an urban environment can greatly affect the local phyllosphere community composition. Although other urban-related factors cannot be ruled out, the relative abundance of most of the dominant taxa was significantly correlated with exposure to traffic-generated PM.

Network Level Carbon Dioxide Emissions From On-road Sources in the Portland OR, (USA) Metropolitan Area

NASA Astrophysics Data System (ADS)

Powell, J.; Butenhoff, C. L.; Rice, A. L.

2014-12-01

To mitigate climate change, governments at multiple levels are developing policies to decrease anthropogenic carbon dioxide (CO2) emissions. The City of Portland (Oregon) and Multnomah County have adopted a Climate Action Plan with a stated goal of reducing emissions to 80% below 1990 levels by 2050. The transportation sector alone accounts for about 40% of total emissions in the Portland metropolitan area. Here we show a new street-level model of on-road mobile CO2 emissions for the Portland, OR metropolitan region. The model uses hourly traffic counter recordings made by the Portland Bureau of Transportation at 9,352 sites over 21 years (1986-2006), augmented with freeway loop detector data from the Portland Regional Transportation Archive Listing (PORTAL) transportation data archive. We constructed a land use regression model to fill in traffic network gaps with traffic counts as the dependent variable using GIS data such as road class (32 categories) and population density. The Environmental Protection Agency (EPA) MOtor Vehicle Emission Simulator (MOVES) model was used to estimate transportation CO2 emissions. The street-level emissions can be aggregated and gridded and used as input to atmospheric transport models for comparison with atmospheric measurements. This model also provides an independent assessment of top-down inventories that determine emissions from fuel sales, while being an important component of our ongoing effort to assess the effectiveness of emission mitigation strategies at the urban scale.

Systematic Hybrid Network Scheduling for Multiple Traffic Classes with Host Timing and Phase Constraints

NASA Technical Reports Server (NTRS)

Hall, Brendan (Inventor); Bonk, Ted (Inventor); Varadarajan, Srivatsan (Inventor); Smithgall, William Todd (Inventor); DeLay, Benjamin F. (Inventor)

2017-01-01

Systems and methods for systematic hybrid network scheduling for multiple traffic classes with host timing and phase constraints are provided. In certain embodiments, a method of scheduling communications in a network comprises scheduling transmission of virtual links pertaining to a first traffic class on a global schedule to coordinate transmission of the virtual links pertaining to the first traffic class across all transmitting end stations on the global schedule; and scheduling transmission of each virtual link pertaining to a second traffic class on a local schedule of the respective transmitting end station from which each respective virtual link pertaining to the second traffic class is transmitted such that transmission of each virtual link pertaining to the second traffic class is coordinated only at the respective end station from which each respective virtual link pertaining to the second traffic class is transmitted.

Comprehensive evaluation of environmental and economic benefits of China's urban underground transportation construction projects.

PubMed

Yang, Xiaobin; Chen, Zhilong; Guo, Dongjun

2015-07-01

Urban underground transportation projects are introduced to address problems of scarce green land and traffic pollution. As construction of urban underground transportation is still in its infancy, there is no definite quantitative measurement on whether the construction is beneficial and what influences it will place on the region in China. This study intends to construct a comprehensive evaluation method for evaluating social, economic and environmental benefits of urban underground transportation projects and proposes the concept, role and principle for evaluation of environmental and economic benefits. It figures out relationship between the environment and factors of city development. It also summarizes three relevant factors, including transportation, biophysics and social economy, and works out indicators to evaluate the influence of urban underground transportation construction. Based on Contingent Valuation Method (CVM), Cost of Illness Approach (CIA), Human Capital Approach (HCA), this paper constructs 13 monetization calculation models for social, economic and environmental benefits in response to seven aspects, namely, reducing noise pollution and air pollution, using land efficiently, improving traffic safety, reducing traffic congestion, saving shipping time and minimizing transportation costs.

An analysis on the impact of rubbernecking on urban freeway traffic.

DOT National Transportation Integrated Search

2004-08-01

An incident influences traffic not only in the incident direction but also in the : opposite direction. There has been research on the influence of incidents on the traffic in : the incident direction. However, research relating to the influence on t...

Analysis of routine traffic count stations to optimize locations and frequency : final report.

DOT National Transportation Integrated Search

1981-06-01

This report describes a grouping of statewide permanent and key traffic counters on the basis of their geographic variations in traffic flow. Several factors were considered including the distance between clusters and urban versus rural areas. : Traf...

Optimising UK urban road verge contributions to biodiversity and ecosystem services with cost-effective management.

PubMed

O'Sullivan, Odhran S; Holt, Alison R; Warren, Philip H; Evans, Karl L

2017-04-15

Urban road verges can contain significant biodiversity, contribute to structural connectivity between other urban greenspaces, and due to their proximity to road traffic are well placed to provide ecosystem services. Using the UK as a case study we review and critically evaluate a broad range of evidence to assess how this considerable potential can be enhanced despite financial, contractual and public opinion constraints. Reduced mowing frequency and other alterations would enhance biodiversity, aesthetics and pollination services, whilst delivering costs savings and potentially being publically acceptable. Retaining mature trees and planting additional ones is favourable to residents and would enhance biodiversity, pollution and climate regulation, carbon storage, and stormwater management. Optimising these services requires improved selection of tree species, and creating a more diverse tree stock. Due to establishment costs additional tree planting and maintenance could benefit from payment for ecosystem service schemes. Verges could also provide areas for cultivation of biofuels and possibly food production. Maximising the contribution of verges to urban biodiversity and ecosystem services is economical and becoming an increasingly urgent priority as the road network expands and other urban greenspace is lost, requiring enhancement of existing greenspace to facilitate sustainable urban development. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Comparative analysis of characteristics and risk factors of traffic injury in aged people from urban and rural areas in Chongqing.

PubMed

Zhang, Liang; Zhou, Ji-Hong; Qiu, Jun; Zhang, Xiu-Zhu; Yuan, Dan-Feng; Gao, Zhi-Ming; Dai, Wei

2012-01-01

To study the epidemiologic characteristics of traffic injuries among people over 60 years old in the Nan'an district (urban) and Jiangjin district (rural) of Chongqing, and to discuss the corresponding strategies for its prevention and cure. Records of traffic injuries in people over 60 years old registered by the traffic police between 2000 and 2006 in Nan'an district and Jiangjin district were collected in the Database of Road Traffic Accidents and Traffic Injuries. Epidemiologic characteristics of traffic injuries among the aged people were analyzed and compared. Between the year 2000 and 2006, the average annual incidence of traffic injuries and mortality rate in the aged people in Nan'an district were 124.62/100 000 and 13.85/ 100 000 respectively, higher than that in Jiangjin district (27.49/ 100 000, 7.13/100 000, P less than 0.01). However, the mortality rate for the aged people who were involved in traffic injuries in Jiangjin district was 20.60%, higher than that in Nan'an district (10.00%, P less than 0.01). Head injury was the primary cause of death. Totally 76.58% of casualties were pede-strians. Over 90% of the traffic accidents occurred in the areas with no traffic signal or traffic control system. The traffic environment is unfavorable to the aged people. It is important to enhance traffic safety consciousness of drivers and the elderly and to strengthen traffic safety system and traffic law, so as to provide a safe road traffic environment for the aged people.

Isotopic Recorders of Pollution in Heterogeneous Urban Areas

NASA Astrophysics Data System (ADS)

Pataki, D. E.; Cobley, L.; Smith, R. M.; Ehleringer, J. R.; Chritz, K.

2017-12-01

A significant difficulty in quantifying urban pollution lies in the extreme spatial and temporal heterogeneity of cities. Dense sources of both point and non-point source pollution as well as the dynamic role of human activities, which vary over very short time scales and small spatial scales, complicate efforts to establish long-term urban monitoring networks that are relevant at neighborhood, municipal, and regional scales. Fortunately, the natural abundance of isotopes of carbon, nitrogen, and other elements provides a wealth of information about the sources and fate of urban atmospheric pollution. In particular, soils and plant material integrate pollution sources and cycling over space and time, and have the potential to provide long-term records of pollution dynamics that extend back before atmospheric monitoring data are available. Similarly, sampling organic material at high spatial resolution can provide "isoscapes" that shed light on the spatial heterogeneity of pollutants in different urban parcels and neighborhoods, along roads of varying traffic density, and across neighborhoods of varying affluence and sociodemographic composition. We have compiled numerous datasets of the isotopic composition of urban organic matter that illustrate the potential for isotopic monitoring of urban areas as a means of understanding hot spots and hot moments in urban atmospheric biogeochemistry. Findings to date already reveal the critical role of affluence, economic activity, demographic change, and land management practices in influencing urban pollution sources and sinks, and suggest an important role of stable isotope and radioisotope measurements in urban atmospheric and biogeochemical monitoring.

Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

PubMed Central

Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN. PMID:25663835

On the Impact of Anomalous Noise Events on Road Traffic Noise Mapping in Urban and Suburban Environments.

PubMed

Orga, Ferran; Alías, Francesc; Alsina-Pagès, Rosa Ma

2017-12-23

Noise pollution is a critical factor affecting public health, the relationship between road traffic noise (RTN) and several diseases in urban areas being especially disturbing. The Environmental Noise Directive 2002/49/EC and the CNOSSOS-EU framework are the main instruments of the European Union to identify and combat noise pollution, requiring Member States to compose and publish noise maps and noise management action plans every five years. Nowadays, the noise maps are starting to be tailored by means of Wireless Acoustic Sensor Networks (WASN). In order to exclusively monitor the impact of RTN on the well-being of citizens through WASN-based approaches, those noise sources unrelated to RTN denoted as Anomalous Noise Events (ANEs) should be removed from the noise map generation. This paper introduces an analysis methodology considering both Signal-to-Noise Ratio (SNR) and duration of ANEs to evaluate their impact on the A-weighted equivalent RTN level calculation for different integration times. The experiments conducted on 9 h of real-life data from the WASN-based DYNAMAP project show that both individual high-impact events and aggregated medium-impact events bias significantly the equivalent noise levels of the RTN map, making any derived study about public health impact inaccurate.

On the Impact of Anomalous Noise Events on Road Traffic Noise Mapping in Urban and Suburban Environments

PubMed Central

2017-01-01

Noise pollution is a critical factor affecting public health, the relationship between road traffic noise (RTN) and several diseases in urban areas being especially disturbing. The Environmental Noise Directive 2002/49/EC and the CNOSSOS-EU framework are the main instruments of the European Union to identify and combat noise pollution, requiring Member States to compose and publish noise maps and noise management action plans every five years. Nowadays, the noise maps are starting to be tailored by means of Wireless Acoustic Sensor Networks (WASN). In order to exclusively monitor the impact of RTN on the well-being of citizens through WASN-based approaches, those noise sources unrelated to RTN denoted as Anomalous Noise Events (ANEs) should be removed from the noise map generation. This paper introduces an analysis methodology considering both Signal-to-Noise Ratio (SNR) and duration of ANEs to evaluate their impact on the A-weighted equivalent RTN level calculation for different integration times. The experiments conducted on 9 h of real-life data from the WASN-based DYNAMAP project show that both individual high-impact events and aggregated medium-impact events bias significantly the equivalent noise levels of the RTN map, making any derived study about public health impact inaccurate. PMID:29295492

Price of anarchy on heterogeneous traffic-flow networks.

PubMed

Rose, A; O'Dea, R; Hopcraft, K I

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability-parameterized by the proportion of variable-cost links in the network-changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

Spatial spreading of infectious disease via local and national mobility networks in South Korea

NASA Astrophysics Data System (ADS)

Kwon, Okyu; Son, Woo-Sik

2017-12-01

We study the spread of infectious disease based on local- and national-scale mobility networks. We construct a local mobility network using data on urban bus services to estimate local-scale movement of people. We also construct a national mobility network from orientation-destination data of vehicular traffic between highway tollgates to evaluate national-scale movement of people. A metapopulation model is used to simulate the spread of epidemics. Thus, the number of infected people is simulated using a susceptible-infectious-recovered (SIR) model within the administrative division, and inter-division spread of infected people is determined through local and national mobility networks. In this paper, we consider two scenarios for epidemic spread. In the first, the infectious disease only spreads through local-scale movement of people, that is, the local mobility network. In the second, it spreads via both local and national mobility networks. For the former, the simulation results show infected people sequentially spread to neighboring divisions. Yet for the latter, we observe a faster spreading pattern to distant divisions. Thus, we confirm the national mobility network enhances synchronization among the incidence profiles of all administrative divisions.

An auxiliary graph based dynamic traffic grooming algorithm in spatial division multiplexing enabled elastic optical networks with multi-core fibers

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Tian, Rui; Yu, Xiaosong; Zhang, Jiawei; Zhang, Jie

2017-03-01

A proper traffic grooming strategy in dynamic optical networks can improve the utilization of bandwidth resources. An auxiliary graph (AG) is designed to solve the traffic grooming problem under a dynamic traffic scenario in spatial division multiplexing enabled elastic optical networks (SDM-EON) with multi-core fibers. Five traffic grooming policies achieved by adjusting the edge weights of an AG are proposed and evaluated through simulation: maximal electrical grooming (MEG), maximal optical grooming (MOG), maximal SDM grooming (MSG), minimize virtual hops (MVH), and minimize physical hops (MPH). Numeric results show that each traffic grooming policy has its own features. Among different traffic grooming policies, an MPH policy can achieve the lowest bandwidth blocking ratio, MEG can save the most transponders, and MSG can obtain the fewest cores for each request.

Common Traffic Violations of Bus Drivers in Urban China: An Observational Study

PubMed Central

Yang, Rendong; Huang, Yuanxiu; Zhang, Lin; Ning, Peishan; Cheng, Xunjie; Schwebel, David C.

2015-01-01

Objective To report common traffic violations in bus drivers and the factors that influence those violations in urban China. Methods We conducted an observational study to record three types of traffic violations among bus drivers in Changsha City, China: illegal stopping at bus stations, violating traffic light signals, and distracted driving. The behaviors of bus drivers on 32 routes (20% of bus routes in the city) were observed. A two-level Poisson regression examined factors that predicted bus driver violations. Results The incidence of illegal stopping at bus stations was 20.2%. Illegal stopping was less frequent on weekends, sunny days, and at stations with cameras, with adjusted incidence rate ratios (IRRs) of 0.81, 0.65 and 0.89, respectively. The incidence of violating traffic light signals was 2.2%, and was lower on cloudy than sunny days (adjusted IRR: 0.60). The incidence of distracted driving was 3.3%. The incidence of distracted driving was less common on cloudy days, rainy or snowy days, and foggy/windy/dusty days compared to sunny days, with adjusted IRRs of 0.54, 0.55 and 0.07, respectively. Conclusion Traffic violations are common in bus drivers in urban China and they are associated with the date, weather, and presence of traffic cameras at bus station. Further studies are recommended to understand the behavioral mechanisms that may explain bus driver violations and to develop feasible prevention measures. PMID:26372105

Magnetic-Based NDE of Prestressed and Post-Tensioned Concrete Members: The MFL System.

DOT National Transportation Integrated Search

1997-07-01

Many metropolitan areas have begun or are planning to implement traffic monitoring programs to meet the many demands for traffic data. The purpose of this project is to document a series of examples of urban traffic monitoring data collection program...

Evaluation of the performance of the Sydney Coordinated Adaptive Traffic System (SCATS) on Powell Boulevard in Portland, OR.

DOT National Transportation Integrated Search

2013-07-01

The Sydney Coordinated Adaptive Traffic System (SCATS) is used to mitigate traffic congestion along urban arterial corridors. Although there : has been research on SCATS performance, this report combines three different areas of research about SCA...

Impact of traffic volume and composition on the air quality and pedestrian exposure in urban street canyon

NASA Astrophysics Data System (ADS)

Rakowska, Agata; Wong, Ka Chun; Townsend, Thomas; Chan, Ka Lok; Westerdahl, Dane; Ng, Simon; Močnik, Griša; Drinovec, Luka; Ning, Zhi

2014-12-01

Vehicle emissions are identified as a major source of air pollution in metropolitan areas. Emission control programs in many cities have been implemented as part of larger scale transport policy interventions to control traffic pollutants and reduce public health risks. These interventions include provision of traffic-free and low emission zones and congestion charging. Various studies have investigated the impact of urban street configurations, such as street canyon in urban centers, on pollutants dispersion and roadside air quality. However, there are few investigations in the literature to study the impact of change of fleet composition and street canyon effects on the on-road pollutants concentrations and associated roadside pedestrian exposure to the pollutants. This study presents an experimental investigation on the traffic related gas and particle pollutants in and near major streets in one of the most developed business districts in Hong Kong, known as Central. Both street canyon and open roadway configurations were included in the study design. Mobile measurement techniques were deployed to monitor both on-road and roadside pollutants concentrations at different times of the day and on different days of a week. Multiple traffic counting points were also established to concurrently collect data on traffic volume and fleet composition on individual streets. Street canyon effects were evident with elevated on-road pollutants concentrations. Diesel vehicles were found to be associated with observed pollutant levels. Roadside black carbon concentrations were found to correlate with their on-road levels but with reduced concentrations. However, ultrafine particles showed very high concentrations in roadside environment with almost unity of roadside/on-road ratios possibly due to the accumulation of primary emissions and secondary PM formation. The results from the study provide useful information for the effective urban transport design and bus route reorganization to minimize the impact of traffic emissions on the urban air quality and public health. Observations on the elevated ultrafine particle concentrations in roadside pedestrian levels also demonstrate the urgent need to improve roadside air quality to reduce pedestrians' health risks especially inside street canyon.

Methodology for designing and implementing a class for service for the transmission of medical images over a common network

NASA Astrophysics Data System (ADS)

Dimond, David A.; Burgess, Robert; Barrios, Nolan; Johnson, Neil D.

2000-05-01

Traditionally, to guarantee the network performance of medical image data transmission, imaging traffic was isolated on a separate network. Organizations are depending on a new generation of multi-purpose networks to transport both normal information and image traffic as they expand access to images throughout the enterprise. These organi want to leverage their existing infrastructure for imaging traffic, but are not willing to accept degradations in overall network performance. To guarantee 'on demand' network performance for image transmissions anywhere at any time, networks need to be designed with the ability to 'carve out' bandwidth for specific applications and to minimize the chances of network failures. This paper will present the methodology Cincinnati Children's Hospital Medical Center (CHMC) used to enhance the physical and logical network design of the existing hospital network to guarantee a class of service for imaging traffic. PACS network designs should utilize the existing enterprise local area network i.e. (LAN) infrastructure where appropriate. Logical separation or segmentation provides the application independence from other clinical and administrative applications as required, ensuring bandwidth and service availability.

Traffic Generator (TrafficGen) Version 1.4.2: Users Guide

DTIC Science & Technology

2016-06-01

events, the user has to enter them manually . We will research and implement a way to better define and organize the multicast addresses so they can be...the network with Transmission Control Protocol and User Datagram Protocol Internet Protocol traffic. Each node generating network traffic in an...TrafficGen Graphical User Interface (GUI) 3 3.1 Anatomy of the User Interface 3 3.2 Scenario Configuration and MGEN Files 4 4. Working with

Modelling NOX concentrations through CFD-RANS in an urban hot-spot using high resolution traffic emissions and meteorology from a mesoscale model

NASA Astrophysics Data System (ADS)

Sanchez, Beatriz; Santiago, Jose Luis; Martilli, Alberto; Martin, Fernando; Borge, Rafael; Quaassdorff, Christina; de la Paz, David

2017-08-01

Air quality management requires more detailed studies about air pollution at urban and local scale over long periods of time. This work focuses on obtaining the spatial distribution of NOx concentration averaged over several days in a heavily trafficked urban area in Madrid (Spain) using a computational fluid dynamics (CFD) model. A methodology based on weighted average of CFD simulations is applied computing the time evolution of NOx dispersion as a sequence of steady-state scenarios taking into account the actual atmospheric conditions. The inputs of emissions are estimated from the traffic emission model and the meteorological information used is derived from a mesoscale model. Finally, the computed concentration map correlates well with 72 passive samplers deployed in the research area. This work reveals the potential of using urban mesoscale simulations together with detailed traffic emissions so as to provide accurate maps of pollutant concentration at microscale using CFD simulations.

Ant colony optimization algorithm for signal coordination of oversaturated traffic networks.

DOT National Transportation Integrated Search

2010-05-01

Traffic congestion is a daily and growing problem of the modern era in mostly all major cities in the world. : Increasing traffic demand strains the existing transportation system, leading to oversaturated network : conditions, especially at peak hou...

Dynamic autonomous routing technology for IP-based satellite ad hoc networks

NASA Astrophysics Data System (ADS)

Wang, Xiaofei; Deng, Jing; Kostas, Theresa; Rajappan, Gowri

2014-06-01

IP-based routing for military LEO/MEO satellite ad hoc networks is very challenging due to network and traffic heterogeneity, network topology and traffic dynamics. In this paper, we describe a traffic priority-aware routing scheme for such networks, namely Dynamic Autonomous Routing Technology (DART) for satellite ad hoc networks. DART has a cross-layer design, and conducts routing and resource reservation concurrently for optimal performance in the fluid but predictable satellite ad hoc networks. DART ensures end-to-end data delivery with QoS assurances by only choosing routing paths that have sufficient resources, supporting different packet priority levels. In order to do so, DART incorporates several resource management and innovative routing mechanisms, which dynamically adapt to best fit the prevailing conditions. In particular, DART integrates a resource reservation mechanism to reserve network bandwidth resources; a proactive routing mechanism to set up non-overlapping spanning trees to segregate high priority traffic flows from lower priority flows so that the high priority flows do not face contention from low priority flows; a reactive routing mechanism to arbitrate resources between various traffic priorities when needed; a predictive routing mechanism to set up routes for scheduled missions and for anticipated topology changes for QoS assurance. We present simulation results showing the performance of DART. We have conducted these simulations using the Iridium constellation and trajectories as well as realistic military communications scenarios. The simulation results demonstrate DART's ability to discriminate between high-priority and low-priority traffic flows and ensure disparate QoS requirements of these traffic flows.

Enrichment and sources of trace metals in roadside soils in Shanghai, China: A case study of two urban/rural roads.

PubMed

Yan, Geng; Mao, Lingchen; Liu, Shuoxun; Mao, Yu; Ye, Hua; Huang, Tianshu; Li, Feipeng; Chen, Ling

2018-08-01

The road traffic has become one of the main sources of urban pollution and could directly affect roadside soils. To understand the level of contamination and potential sources of trace metals in roadside soils of Shanghai, 10 trace metals (Sb, Cr, Co, Ni, Cu, Cd, Pb, Hg, Mn and Zn) from two urban/rural roads (Hutai Road and Wunign-Caoan Road) were analyzed in this study. Antimony, Ni, Cu, Cd, Pb, Hg and Zn concentrations were higher than that of soil background values of Shanghai, whereas accumulation of Cr, Co and Mn were minimal. Significantly higher Sb, Cd, Pb contents were found in samples from urban areas than those from suburban area, suggesting the impact from urbanization. The concentrations of Sb and Cd in older road (Hutai) were higher than that in younger road (Wunign-Caoan). Multivariate statistical analysis revealed that Sb, Cu, Cd, Pb and Zn were mainly controlled by traffic activities (e.g. brake wear, tire wear, automobile exhaust) with high contamination levels found near traffic-intensive areas; Cr, Co, Ni and Mn derived primarily from soil parent materials; Hg was related to industrial activities. Besides, the enrichment of Sb, Cd, Cu, Pb and Zn showed a decreasing trend with distance to the road edges. According to the enrichment factors (EF s ), 78.5% of Sb, Cu, Cd, Pb and Zn were in moderate or significant pollution, indicating considerable traffic contribution. In particular, recently introduced in automotive technology, accumulation of Sb has been recognized in 42.9% samples of both roads. The accumulation of these traffic-derived metals causes potential negative impact to human health and ecological environment and should be concerned, especially the emerging trace elements like Sb. Copyright © 2018 Elsevier B.V. All rights reserved.

Mixed Traffic Information Collection System based on Pressure Sensor

NASA Astrophysics Data System (ADS)

Liao, Wenzhe; Liu, Mingsheng; Meng, Qingli

The traffic information collection is the base of Intelligent Traffic.At present, there exist mixed traffic situation in urban road in China. This paper researched and implemented a system through collecting the vehicle and bicycle mixed traffic flow parameters based on pressure sensor. According to information collection requirements, we selected pressure sensor, designed the data collection, storage and other hardware circuitries and information processing software. The experiment shows that the system can meet the demand of traffic information collection in the actual.

Collective Human Mobility Pattern from Taxi Trips in Urban Area

PubMed Central

Peng, Chengbin; Jin, Xiaogang; Wong, Ka-Chun; Shi, Meixia; Liò, Pietro

2012-01-01

We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously. PMID:22529917

Network-wide BGP route prediction for traffic engineering

NASA Astrophysics Data System (ADS)

Feamster, Nick; Rexford, Jennifer

2002-07-01

The Internet consists of about 13,000 Autonomous Systems (AS's) that exchange routing information using the Border Gateway Protocol (BGP). The operators of each AS must have control over the flow of traffic through their network and between neighboring AS's. However, BGP is a complicated, policy-based protocol that does not include any direct support for traffic engineering. In previous work, we have demonstrated that network operators can adapt the flow of traffic in an efficient and predictable fashion through careful adjustments to the BGP policies running on their edge routers. Nevertheless, many details of the BGP protocol and decision process make predicting the effects of these policy changes difficult. In this paper, we describe a tool that predicts traffic flow at network exit points based on the network topology, the import policy associated with each BGP session, and the routing advertisements received from neighboring AS's. We present a linear-time algorithm that computes a network-wide view of the best BGP routes for each destination prefix given a static snapshot of the network state, without simulating the complex details of BGP message passing. We describe how to construct this snapshot using the BGP routing tables and router configuration files available from operational routers. We verify the accuracy of our algorithm by applying our tool to routing and configuration data from AT&T's commercial IP network. Our route prediction techniques help support the operation of large IP backbone networks, where interdomain routing is an important aspect of traffic engineering.

Investigation of powered 2-wheeler accident involvement in urban arterials by considering real-time traffic and weather data.

PubMed

Theofilatos, Athanasios; Yannis, George

2017-04-03

Understanding the various factors that affect accident risk is of particular concern to decision makers and researchers. The incorporation of real-time traffic and weather data constitutes a fruitful approach when analyzing accident risk. However, the vast majority of relevant research has no specific focus on vulnerable road users such as powered 2-wheelers (PTWs). Moreover, studies using data from urban roads and arterials are scarce. This study aims to add to the current knowledge by considering real-time traffic and weather data from 2 major urban arterials in the city of Athens, Greece, in order to estimate the effect of traffic, weather, and other characteristics on PTW accident involvement. Because of the high number of candidate variables, a random forest model was applied to reveal the most important variables. Then, the potentially significant variables were used as input to a Bayesian logistic regression model in order to reveal the magnitude of their effect on PTW accident involvement. The results of the analysis suggest that PTWs are more likely to be involved in multivehicle accidents than in single-vehicle accidents. It was also indicated that increased traffic flow and variations in speed have a significant influence on PTW accident involvement. On the other hand, weather characteristics were found to have no effect. The findings of this study can contribute to the understanding of accident mechanisms of PTWs and reduce PTW accident risk in urban arterials.

Assessment of long-term and large-scale even-odd license plate controlled plan effects on urban air quality and its implication

NASA Astrophysics Data System (ADS)

Zhao, Suping; Yu, Ye; Qin, Dahe; Yin, Daiying; He, Jianjun

2017-12-01

To solve traffic congestion and to improve urban air quality, long-lasting and large-scale even-odd license plate controlled plan was implemented by local government during 20 November to 26 December 2016 in urban Lanzhou, a semi-arid valley city of northwest China. The traffic control measures provided an invaluable opportunity to evaluate its effects on urban air quality in less developed cities of northwest China. Based on measured simultaneously air pollutants and meteorological parameters, the abatement of traffic-related pollutants induced by the implemented control measures such as CO, PM2.5 and PM10 (the particulate matter with diameter less than 2.5 μm and 10 μm) concentrations were firstly quantified by comparing the air quality data in urban areas with those in rural areas (uncontrolled zones). The concentrations of CO, NO2 from motor vehicles and fine particulate matter (PM2.5) were shown to have significant decreases of 15%-23% during traffic control period from those measured before control period with hourly maximum CO, PM2.5, and NO2/SO2 reduction of 43%, 35% and 141.4%, respectively. The influence of the control measures on AQI (air quality index) and ozone was less as compared to its effect on other air pollutants. Therefore, to alleviate serious winter haze pollution in China and to protect human health, the stringent long-term and large-scale even-odd license plate controlled plan should be implemented aperiodically in urban areas, especially for the periods with poor diffusion conditions.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

Perfluorooctane sulfonate (PFOS) contamination of fish in urban lakes: a prioritization methodology for lake management.

PubMed

Xiao, Feng; Gulliver, John S; Simcik, Matt F

2013-12-15

The contamination of urban lakes by anthropogenic pollutants such as perfluorooctane sulfonate (PFOS) is a worldwide environmental problem. Large-scale, long-term monitoring of urban lakes requires careful prioritization of available resources, focusing efforts on potentially impaired lakes. Herein, a database of PFOS concentrations in 304 fish caught from 28 urban lakes was used for development of an urban-lake prioritization framework by means of exploratory data analysis (EDA) with the aid of a geographical information system. The prioritization scheme consists of three main tiers: preliminary classification, carried out by hierarchical cluster analysis; predictor screening, fulfilled by a regression tree method; and model development by means of a neural network. The predictive performance of the newly developed model was assessed using a training/validation splitting method and determined by an external validation set. The application of the model in the U.S. state of Minnesota identified 40 urban lakes that may contain elevated levels of PFOS; these lakes were not previously considered in PFOS monitoring programs. The model results also highlight ongoing industrial/commercial activities as a principal determinant of PFOS pollution in urban lakes, and suggest vehicular traffic as an important source and surface runoff as a primary pollution carrier. In addition, the EDA approach was further compared to a spatial interpolation method (kriging), and their advantages and disadvantages were discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adaptive route choice modeling in uncertain traffic networks with real-time information.

DOT National Transportation Integrated Search

2013-03-01

The objective of the research is to study travelers' route choice behavior in uncertain traffic networks : with real-time information. The research is motivated by two observations of the traffic system: 1) : the system is inherently uncertain with r...

Transportation noise and annoyance related to road traffic in the French RECORD study

PubMed Central

2013-01-01

Road traffic and related noise is a major source of annoyance and impairment to health in urban areas. Many areas exposed to road traffic noise are also exposed to rail and air traffic noise. The resulting annoyance may depend on individual/neighborhood socio-demographic factors. Nevertheless, few studies have taken into account the confounding or modifying factors in the relationship between transportation noise and annoyance due to road traffic. In this study, we address these issues by combining Geographic Information Systems and epidemiologic methods. Street network buffers with a radius of 500 m were defined around the place of residence of the 7290 participants of the RECORD Cohort in Ile-de-France. Estimated outdoor traffic noise levels (road, rail, and air separately) were assessed at each place of residence and in each of these buffers. Higher levels of exposure to noise were documented in low educated neighborhoods. Multilevel logistic regression models documented positive associations between road traffic noise and annoyance due to road traffic, after adjusting for individual/neighborhood socioeconomic conditions. There was no evidence that the association was of different magnitude when noise was measured at the place of residence or in the residential neighborhood. However, the strength of the association between neighborhood noise exposure and annoyance increased when considering a higher percentile in the distribution of noise in each neighborhood. Road traffic noise estimated at the place of residence and road traffic noise in the residential neighborhood (75th percentile) were independently associated with annoyance, when adjusted for each other. Interactions of effects indicated that the relationship between road traffic noise exposure in the residential neighborhood and annoyance was stronger in affluent and high educated neighborhoods. Overall, our findings suggest that it is useful to take into account (i) the exposure to transportation noise in the residential neighborhood rather than only at the residence, (ii) different percentiles of noise exposure in the residential neighborhood, and (iii) the socioeconomic characteristics of the residential neighborhood to explain variations in annoyance due to road traffic in the neighborhood. PMID:24088229

A smartphone-based platform to test the performance of wireless mobile networks and preliminary findings

NASA Astrophysics Data System (ADS)

Geng, Xinli; Xu, Hao; Qin, Xiaowei

2016-10-01

During the last several years, the amount of wireless network traffic data increased fast and relative technologies evolved rapidly. In order to improve the performance and Quality of Experience (QoE) of wireless network services, the analysis of field network data and existing delivery mechanisms comes to be a promising research topic. In order to achieve this goal, a smartphone based platform named Monitor and Diagnosis of Mobile Applications (MDMA) was developed to collect field data. Based on this tool, the web browsing service of High Speed Downlink Packet Access (HSDPA) network was tested. The top 200 popular websites in China were selected and loaded on smartphone for thousands times automatically. Communication packets between the smartphone and the cell station were captured for various scenarios (e.g. residential area, urban roads, bus station etc.) in the selected city. A cross-layer database was constructed to support the off-line analysis. Based on the results of client-side experiments and analysis, the usability of proposed portable tool was verified. The preliminary findings and results for existing web browsing service were also presented.

Rethinking Traffic Management: Design of Optimizable Networks

DTIC Science & Technology

2008-06-01

Though this paper used optimization theory to design and analyze DaVinci , op- timization theory is one of many possible tools to enable a grounded...dynamically allocate bandwidth shares. The distributed protocols can be implemented using DaVinci : Dynamically Adaptive VIrtual Networks for a Customized...Internet. In DaVinci , each virtual network runs traffic-management protocols optimized for a traffic class, and link bandwidth is dynamically allocated

A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr; Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr

2015-03-10

We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap schememore » is introduced to numerically approximate the model’s flow equations.« less

Spatial-spectral flexible optical networking: enabling switching solutions for a simplified and efficient SDM network platform

NASA Astrophysics Data System (ADS)

Tomkos, I.; Zakynthinos, P.; Klonidis, D.; Marom, D.; Sygletos, S.; Ellis, A.; Salvadori, E.; Siracusa, D.; Angelou, M.; Papastergiou, G.; Psaila, N.; Ferran, J. F.; Ben-Ezra, S.; Jimenez, F.; Fernández-Palacios, J. P.

2013-12-01

The traffic carried by core optical networks grows at a steady but remarkable pace of 30-40% year-over-year. Optical transmissions and networking advancements continue to satisfy the traffic requirements by delivering the content over the network infrastructure in a cost and energy efficient manner. Such core optical networks serve the information traffic demands in a dynamic way, in response to requirements for shifting of traffics demands, both temporally (day/night) and spatially (business district/residential). However as we are approaching fundamental spectral efficiency limits of singlemode fibers, the scientific community is pursuing recently the development of an innovative, all-optical network architecture introducing the spatial degree of freedom when designing/operating future transport networks. Spacedivision- multiplexing through the use of bundled single mode fibers, and/or multi-core fibers and/or few-mode fibers can offer up to 100-fold capacity increase in future optical networks. The EU INSPACE project is working on the development of a complete spatial-spectral flexible optical networking solution, offering the network ultra-high capacity, flexibility and energy efficiency required to meet the challenges of delivering exponentially growing traffic demands in the internet over the next twenty years. In this paper we will present the motivation and main research activities of the INSPACE consortium towards the realization of the overall project solution.

Traffic-driven epidemic spreading on scale-free networks with tunable degree distribution

NASA Astrophysics Data System (ADS)

Yang, Han-Xin; Wang, Bing-Hong

2016-04-01

We study the traffic-driven epidemic spreading on scale-free networks with tunable degree distribution. The heterogeneity of networks is controlled by the exponent γ of power-law degree distribution. It is found that the epidemic threshold is minimized at about γ=2.2. Moreover, we find that nodes with larger algorithmic betweenness are more likely to be infected. We expect our work to provide new insights in to the effect of network structures on traffic-driven epidemic spreading.

Urban traffic noise and self-reported health.

PubMed

Gómez-Jacinto, L; Moral-Toranzo, F

1999-06-01

This paper analyzed urban traffic noise effects on health at two different levels: intense noise and moderate noise. 42 residents of the area responded to questions on perceived noise and psychological and behavior disturbance before and after acoustic insulation was constructed. Analysis of self-reports indicated that perceived noise was associated with lower health. Also these perceived effects on health did not decrease after the acoustic isolation work was finished.

Traffic signal coordination and queue management in oversaturated intersection.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network : performance by reducing delay, increasing network throughput, reducing number of stops, or : increasing average speed in the network. The optimization can be...

Traffic signal coordination and queue management in oversaturated intersections.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network performance by reducing delay, increasing network throughput, reducing number of stops, or increasing average speed in the network. The optimization can become...

Analyzing lead concentration in the sycamore tree species in high- and low-traffic areas of Rasht, Iran.

PubMed

Hashemi, Seyed Armin; Alinejad, Farzaneh; FallahChay, Mozaffar

2015-06-01

Important heavy metals such as lead and cadmium are part of the pollutants produced by cars and are spread in the urban environment by traffic flow. In order to study the amount of contamination in the trees along the streets and to determine the traffic parameters that affect the lead content in sycamore leaves in Rasht, four stations on the margins of the city streets were selected for this case study in terms of traffic volume (low or high). Traffic parameters including three high-traffic stations considering daily and monthly traffic volumes and one low-traffic station were selected. First, 32 sycamore bases were randomly chosen at the intervals of 10-15 m from the whole range of tree canopy in order to determine the absorption of lead; and then, 20 g of each sample were tested to determine the amount of lead absorption. The results of this study, on the amount of lead absorption by the sycamore tree species at three high-traffic and one control station, showed that Takhti station had the highest amount of lead absorption (37.19 ppm) compared with other three stations. Therefore, the sycamore tree species can be an appropriate one for the margins of urban streets. © The Author(s) 2013.

Reasons underlying behaviour of motorcyclists disregarding traffic regulations in urban areas of Indonesia.

PubMed

Susilo, Yusak O; Joewono, Tri Basuki; Vandebona, Upali

2015-02-01

Over the last decade, motorcycle use has been rapidly increasing in Indonesia as have violations of traffic rules committed by motorcyclists. This study aims to explore the impacts of motorcyclists' attitudes, habits, preferences, and travel patterns on their behaviour in disregarding traffic regulations in three cities in Indonesia. The theory of planned behaviour and structural equation modelling are employed to explore these relationships. Consistent with results from previous studies in developed countries, an individual's beliefs and attitudes, social norms and perceived behaviour control significantly influence behaviour in disregarding traffic rules. Young adults and students are found to be more likely to frequently violate traffic regulations. However, unlike previous findings from developed countries, in Indonesia, males are less likely to disregard traffic rules than females. Overall, pushing the motorcycle through a (very) narrow gap, speeding, driving recklessly, and overtaking on the wrong side are the most frequent traffic violations that make up repetitive violation behaviour among urban motorcyclists in Indonesia. The results highlight the need to revisit Indonesian National Traffic Law traffic violation classification and penalties and separate violations that are likely to cause fatal results, thus requiring tougher law enforcement, from violations that are unlikely to have fatal consequences. Copyright © 2014 Elsevier Ltd. All rights reserved.

Determination of network origin-destination matrices using partial link traffic counts and virtual sensor information in an integrated corridor management framework.

DOT National Transportation Integrated Search

2014-04-01

Trip origin-destination (O-D) demand matrices are critical components in transportation network : modeling, and provide essential information on trip distributions and corresponding spatiotemporal : traffic patterns in traffic zones in vehicular netw...

Traffic handling capability of a broadband indoor wireless network using CDMA multiple access

NASA Astrophysics Data System (ADS)

Zhang, Chang G.; Hafez, H. M.; Falconer, David D.

1994-05-01

CDMA (code division multiple access) may be an attractive technique for wireless access to broadband services because of its multiple access simplicity and other appealing features. In order to investigate traffic handling capabilities of a future network providing a variety of integrated services, this paper presents a study of a broadband indoor wireless network supporting high-speed traffic using CDMA multiple access. The results are obtained through the simulation of an indoor environment and the traffic capabilities of the wireless access to broadband 155.5 MHz ATM-SONET networks using the mm-wave band. A distributed system architecture is employed and the system performance is measured in terms of call blocking probability and dropping probability. The impacts of the base station density, traffic load, average holding time, and variable traffic sources on the system performance are examined. The improvement of system performance by implementing various techniques such as handoff, admission control, power control and sectorization are also investigated.

An optimal routing strategy on scale-free networks

NASA Astrophysics Data System (ADS)

Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin

Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

Realistic Data-Driven Traffic Flow Animation Using Texture Synthesis.

PubMed

Chao, Qianwen; Deng, Zhigang; Ren, Jiaping; Ye, Qianqian; Jin, Xiaogang

2018-02-01

We present a novel data-driven approach to populate virtual road networks with realistic traffic flows. Specifically, given a limited set of vehicle trajectories as the input samples, our approach first synthesizes a large set of vehicle trajectories. By taking the spatio-temporal information of traffic flows as a 2D texture, the generation of new traffic flows can be formulated as a texture synthesis process, which is solved by minimizing a newly developed traffic texture energy. The synthesized output captures the spatio-temporal dynamics of the input traffic flows, and the vehicle interactions in it strictly follow traffic rules. After that, we position the synthesized vehicle trajectory data to virtual road networks using a cage-based registration scheme, where a few traffic-specific constraints are enforced to maintain each vehicle's original spatial location and synchronize its motion in concert with its neighboring vehicles. Our approach is intuitive to control and scalable to the complexity of virtual road networks. We validated our approach through many experiments and paired comparison user studies.

10 CFR 420.15 - Minimum criteria for required program activities for plans.

Code of Federal Regulations, 2014 CFR

2014-01-01

.../vanpool matching and promotion campaign; (ii) Park-and-ride lots; (iii) Preferential traffic control for... employees; (x) Urban area traffic restrictions; (xi) Geographical or time restrictions on automobile use; or... efficiency standards for renovated buildings. (e) A traffic law or regulation which permits the operator of a...

10 CFR 420.15 - Minimum criteria for required program activities for plans.

Code of Federal Regulations, 2013 CFR

2013-01-01

.../vanpool matching and promotion campaign; (ii) Park-and-ride lots; (iii) Preferential traffic control for... employees; (x) Urban area traffic restrictions; (xi) Geographical or time restrictions on automobile use; or... efficiency standards for renovated buildings. (e) A traffic law or regulation which permits the operator of a...

10 CFR 420.15 - Minimum criteria for required program activities for plans.

Code of Federal Regulations, 2012 CFR

2012-01-01

.../vanpool matching and promotion campaign; (ii) Park-and-ride lots; (iii) Preferential traffic control for... employees; (x) Urban area traffic restrictions; (xi) Geographical or time restrictions on automobile use; or... efficiency standards for renovated buildings. (e) A traffic law or regulation which permits the operator of a...

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

PubMed

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.

Using simple agent-based modeling to inform and enhance neighborhood walkability.

PubMed

Badland, Hannah; White, Marcus; Macaulay, Gus; Eagleson, Serryn; Mavoa, Suzanne; Pettit, Christopher; Giles-Corti, Billie

2013-12-11

Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory 'what-if' scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate. This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input. The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking speeds and wait time at intersections. The tool has the capacity to influence planning and public health advocacy and practice, and by using open-access source software, it is available for use locally and internationally. There is also scope to extend this version of the tool from a simple to a complex model, which includes agents (i.e., simulated pedestrians) 'learning' and incorporating other environmental attributes that enhance walkability (e.g., residential density, mixed land use, traffic volume).

[Cycling in Zagreb].

PubMed

Matos, Stipan; Krapac, Ladislav; Krapac, Josip

2007-01-01

Cycling in Zagreb, as means of urban transport inside and outside the city, has a bright past, hazy presence but a promising future. Every day, aggressive citizens who lack urban traffic culture mistreat many cyclists but also many pedestrians. Sedentary way of living, unhealthy eating habits and inadequate recreation would surely be reduced if Zagreb had a network of cycling tracks (190 cm) or lanes (80 cm). Main city roads were constructed at the beginning of the 20th century. Today, the lack of cycling tracks is particularly evident in terms of missing connections between northern and southern parts of the city. Transportation of bikes in public vehicles, parking of bikes as well as cycling along the foot of the mountains Medvednica and Zumberacko gorje is not adequately organized. Better organization is necessary not only because of the present young generation but also because of the young who will shortly become citizens of the EU, where cycling is enormously popular. Cycling tourism is not known in Zagreb, partly due to inadequate roads. The surroundings of Zagreb are more suitable for cycling tourism and attractive brochures and tourist guides offer information to tourists on bikes. Professional, acrobatic and sports cycling do not have a tradition in Zagreb and in Croatia. The same holds true for recreational cycling and indoor exercise cycling. The authors discuss the impact of popularization of cycling using print and electronic media. The role of district and local self-government in the construction and improvement of traffic roads in Zagreb is very important. It is also significant for the implementation of legal regulations that must be obeyed by all traffic participants in order to protect cyclists, the most vulnerable group of traffic participants besides passengers. Multidisciplinary action of all benevolent experts would surely increase safety and pleasure of cycling in the city and its surroundings. This would also help reduce daily stress and improve the quality of living in the capital of Croatia.

Quantitative assessment of human health risk posed by polycyclic aromatic hydrocarbons in urban road dust.

PubMed

Ma, Yukun; Liu, An; Egodawatta, Prasanna; McGree, James; Goonetilleke, Ashantha

2017-01-01

Among the numerous pollutants present in urban road dust, polycyclic aromatic hydrocarbons (PAHs) are among the most toxic chemical pollutants and can pose cancer risk to humans. The primary aim of the study was to develop a quantitative model to assess the cancer risk from PAHs in urban road dust based on traffic and land use factors and thereby to characterise the risk posed by PAHs in fine (<150μm) and coarse (>150μm) particles. The risk posed by PAHs was quantified as incremental lifetime cancer risk (ILCR), which was modelled as a function of traffic volume and percentages of different urban land uses. The study outcomes highlighted the fact that cancer risk from PAHs in urban road dust is primarily influenced by PAHs associated with fine solids. Heavy PAHs with 5 to 6 benzene rings, especially dibenzo[a,h]anthracene (D[a]A) and benzo[a]pyrene (B[a]P) in the mixture contribute most to the risk. The quantitative model developed based on traffic and land use factors will contribute to informed decision making in relation to the management of risk posed by PAHs in urban road dust. Copyright © 2016 Elsevier B.V. All rights reserved.

Perceptual assessment of quality of urban soundscapes with combined noise sources and water sounds.

PubMed

Jeon, Jin Yong; Lee, Pyoung Jik; You, Jin; Kang, Jian

2010-03-01

In this study, urban soundscapes containing combined noise sources were evaluated through field surveys and laboratory experiments. The effect of water sounds on masking urban noises was then examined in order to enhance the soundscape perception. Field surveys in 16 urban spaces were conducted through soundwalking to evaluate the annoyance of combined noise sources. Synthesis curves were derived for the relationships between noise levels and the percentage of highly annoyed (%HA) and the percentage of annoyed (%A) for the combined noise sources. Qualitative analysis was also made using semantic scales for evaluating the quality of the soundscape, and it was shown that the perception of acoustic comfort and loudness was strongly related to the annoyance. A laboratory auditory experiment was then conducted in order to quantify the total annoyance caused by road traffic noise and four types of construction noise. It was shown that the annoyance ratings were related to the types of construction noise in combination with road traffic noise and the level of the road traffic noise. Finally, water sounds were determined to be the best sounds to use for enhancing the urban soundscape. The level of the water sounds should be similar to or not less than 3 dB below the level of the urban noises.

Price of anarchy on heterogeneous traffic-flow networks

NASA Astrophysics Data System (ADS)

Rose, A.; O'Dea, R.; Hopcraft, K. I.

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability—parameterized by the proportion of variable-cost links in the network—changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

Evaluation of the social and economic burden of road traffic noise-attributed myocardial infarction in Bulgarian urban population.

PubMed

Dzhambov, Angel M; Dimitrova, Donka D

2015-03-01

Road traffic noise is a widely studied environmental risk factor for ischaemic heart disease and myocardial infarction in particular. Given that myocardial infarction is a leading disability and mortality cause in Bulgaria and that a significant proportion of the urban population is exposed to high noise levels, quantification of the burden of disease attributable to traffic noise is essential for environmental health policy making and noise control engineering. This study aimed at estimating the burden of the myocardial infarction cases attributable to road traffic noise in the Bulgarian urban population. We used the methodology for estimating the burden of disease attributable to environmental noise outlined by the World Health Organization. Risk data were extracted from a recently published meta-analysis providing updated exposure-response relationship between traffic noise and the risk for myocardial infarction. Based on these data we calculated the fraction of myocardial infarction cases attributable to traffic noise, loss of quality-adjusted life-years (QALYs), and the economic burden, assuming € 12,000 per QALY. About 2.9 % or 101 of all myocardial infarction cases could be attributed to road traffic noise. Fifty-five of these were fatal. Nine hundred and sixty-eight QALYs were lost to these cases. The monetary value of these QALYs was about € 11.6 million. Although the measures used in this study are crude and give only an approximation of the real burden of disease from road traffic noise, they are indicative of the important social and economic aspect of noise pollution in Bulgaria. Hopefully, these results will direct the attention of epidemiologists, environmental hygienists, and health economists to this pivotal environmental issue.

Polycyclic aromatic hydrocarbons (PAHs) concentration levels, pattern, source identification and soil toxicity assessment in urban traffic soil of Dhanbad, India.

PubMed

Suman, Swapnil; Sinha, Alok; Tarafdar, Abhrajyoti

2016-03-01

Present study was carried out to assess and understand potential health risk and to examine the impact of vehicular traffic on the contamination status of urban traffic soils in Dhanbad City with respect to polycyclic aromatic hydrocarbons (PAHs). Eight urban traffic sites and two control/rural site surface soils were analyzed and the contents of 13 priority PAHs was determined. Total PAH concentration at traffic sites ranged from 1.019 μg g(-1) to 10.856 μg g(-1) with an average value of 3.488 μg g(-1). At control/rural site, average concentration of total PAHs was found to be 0.640 μg g(-1). PAH pattern was dominated by four- and five-ring PAHs (contributing >50% to the total PAHs) at all the eight traffic sites. On the other hand, rural soil showed a predominance of low molecular weight three-ring PAHs (contributing >30% to the total PAHs). Indeno[123-cd]pyrene/benz[ghi]perylene (IP/BgP) ratio indicated that PAH load at the traffic sites is predominated by the gasoline-driven vehicles. The ratio of Ant/(Ant+Phe) varied from 0.03 to 0.44, averaging 0.10; Fla/(Fla+Pyr) from 0.39 to 0.954, averaging 0.52; BaA/(BaA+Chry) from 0.156 to 0.60, averaging 0.44; and IP/(IP+BgP) from 0.176 to 0.811, averaging 0.286. The results indicated that vehicular emission was the major source for PAHs contamination with moderate effect of coal combustion and biomass combustion. Carcinogenic potency of PAH load in traffic soil was nearly 6.15 times higher as compared to the control/rural soil. Copyright © 2015 Elsevier B.V. All rights reserved.

Air quality: from observation to applied studies

NASA Astrophysics Data System (ADS)

Weber, Christiane H.; Wania, Annett; Hirsch, Jacky; Bruse, Michael

2004-10-01

Air qualities studies in urban areas embrace several directions that are strongly associated with urban complexity. In the last centuries cities evolution implied changes in urbanization trends: urban sprawl has modified the relationship between cities and surroundings settlements. The existence and protection of urban green and open areas is promoted as a mean to improve the quality of life of their citizens and increase the satisfactory level of the inhabitants against pollution and noise adverse effects. This paper outlines the methods and approaches used in the EU research project Benefits of Urban Green Space (BUGS). The main target of BUGS is to assess the role of urban green spaces in alleviating the adverse effects of urbanization trends by developing an integrative methodology, ranging from participatory planning tools to numerical simulation models. The influence of urban structures on atmospheric pollutants distribution is investigated as a multi-scale problem ranging from micro to macro/regional scale. Traditionally, air quality models are applied on a single scale, seldom considering the joint effects of traffic network and urban development together. In BUGS, several numerical models are applied to cope with urban complexity and to provide quantitative and qualitative results. The differing input data requirements for the various models demanded a methodology which ensures a coherent data extraction and application procedure. In this paper, the stepwise procedure used for BUGS is presented after a general presentation of the research project and the models implied. A discussion part will highlight the statements induced by the choices made and a conclusive part bring to the stage some insights for future investigations.

Stereo-based Collision Avoidance System for Urban Traffic

NASA Astrophysics Data System (ADS)

Moriya, Takashi; Ishikawa, Naoto; Sasaki, Kazuyuki; Nakajima, Masato

2002-11-01

Numerous car accidents occur on urban road. However, researches done so far on driving assistance are subjecting highways whose environment is relatively simple and easy to handle, and new approach for urban settings is required. Our purpose is to extend its support to the following conditions in city traffic: the presence of obstacles such as pedestrians and telephone poles; the lane mark is not always drawn on a road; drivers may lack the sense of awareness of the lane mark. We propose a collision avoidance system, which can be applied to both highways and urban traffic environment. In our system, stereo cameras are set in front of a vehicle and the captured images are processed through a computer. We create a Projected Disparity Map (PDM) from stereo image pair, which is a disparity histogram taken along ordinate direction of obtained disparity image. When there is an obstacle in front, we can detect it by finding a peak appeared in the PDM. With a speed meter and a steering sensor, the stop distance and the radius of curvature of the self-vehicle are calculated, in order to set the observation-required area, which does not depend on lane marks, within a PDM. A danger level will be computed from the distance and the relative speed to the closest approaching object detected within the observation-required area. The method has been tested in urban traffic scenes and has shown to be effective for judging dangerous situation, and gives proper alarm to a driver.

A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

PubMed Central

Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

2015-01-01

It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. PMID:26076404

Teaching Network Security with IP Darkspace Data

ERIC Educational Resources Information Center

Zseby, Tanja; Iglesias Vázquez, Félix; King, Alistair; Claffy, K. C.

2016-01-01

This paper presents a network security laboratory project for teaching network traffic anomaly detection methods to electrical engineering students. The project design follows a research-oriented teaching principle, enabling students to make their own discoveries in real network traffic, using data captured from a large IP darkspace monitor…

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data

PubMed Central

Ran, Bin; Song, Li; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%. PMID:27448326

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data.

PubMed

Ran, Bin; Song, Li; Zhang, Jian; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.

Traffic Management in ATM Networks Over Satellite Links

NASA Technical Reports Server (NTRS)

Goyal, Rohit; Jain, Raj; Goyal, Mukul; Fahmy, Sonia; Vandalore, Bobby; vonDeak, Thomas

1999-01-01

This report presents a survey of the traffic management Issues in the design and implementation of satellite Asynchronous Transfer Mode (ATM) networks. The report focuses on the efficient transport of Transmission Control Protocol (TCP) traffic over satellite ATM. First, a reference satellite ATM network architecture is presented along with an overview of the service categories available in ATM networks. A delay model for satellite networks and the major components of delay and delay variation are described. A survey of design options for TCP over Unspecified Bit Rate (UBR), Guaranteed Frame Rate (GFR) and Available Bit Rate (ABR) services in ATM is presented. The main focus is on traffic management issues. Several recommendations on the design options for efficiently carrying data services over satellite ATM networks are presented. Most of the results are based on experiments performed on Geosynchronous (GEO) latencies. Some results for Low Earth Orbits (LEO) and Medium Earth Orbit (MEO) latencies are also provided.

Inside the Mechanics of Network Development: How Competition and Strategy Reorganize European Air Traffic

NASA Technical Reports Server (NTRS)

Huber, Hans

2006-01-01

Air transport forms complex networks that can be measured in order to understand its structural characteristics and functional properties. Recent models for network growth (i.e., preferential attachment, etc.) remain stochastic and do not seek to understand other network-specific mechanisms that may account for their development in a more microscopic way. Air traffic is made up of many constituent airlines that are either privately or publicly owned and that operate their own networks. They follow more or less similar business policies each. The way these airline networks organize among themselves into distinct traffic distributions reveals complex interaction among them, which in turn can be aggregated into larger (macro-) traffic distributions. Our approach allows for a more deterministic methodology that will assess the impact of airline strategies on the distinct distributions for air traffic, particularly inside Europe. One key question this paper is seeking to answer is whether there are distinct patterns of preferential attachment for given classes of airline networks to distinct types of European airports. Conclusions about the advancing degree of concentration in this industry and the airline operators that accelerate this process can be drawn.

Traffic-aware energy saving scheme with modularization supporting in TWDM-PON

NASA Astrophysics Data System (ADS)

Xiong, Yu; Sun, Peng; Liu, Chuanbo; Guan, Jianjun

2017-01-01

Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.

Traffic modeling of transit oriented development : evaluation of transit friendly strategies and innovative intersection designs in West Valley City, UT.

DOT National Transportation Integrated Search

2014-07-01

Street networks designed to support Transit Oriented Development (TOD) increase accessibility for non-motorized traffic. However, the implications of TOD supportive networks for still dominant vehicular : traffic are rarely addressed. Due to this lac...

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2012 CFR

2012-04-01

... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2013 CFR

2013-04-01

... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...

23 CFR 658.21 - Identification of National Network.

Code of Federal Regulations, 2014 CFR

2014-04-01

... the efficiency of the total traffic flow, such as time of day prohibitions, or lane use controls. (2....21 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC... National Network shall be signed. All signs shall conform to the Manual on Uniform Traffic Control Devices...

Transport and public health in China: the road to a healthy future

PubMed Central

Jiang, Baoguo; Liang, Song; Peng, Zhong-Ren; Cong, Haozhe; Levy, Morgan; Cheng, Qu; Wang, Tianbing; Remais, Justin

2017-01-01

Transportation-related risk factors are a major source of morbidity and mortality in China, where expansion of road networks and surges in personal vehicle ownership are having profound effects on public health. Road traffic injuries and fatalities have increased alongside motorized transport in China, and accident injury risk is aggravated by inadequate emergency response systems and trauma care. National air quality standards and emission control technologies are having a positive effect, yet persistent air pollution is increasingly attributable to a growing and outdated vehicle fleet, and famously congested roads. Urban design favors motorized transport, and physical activity and its associated health benefits are hindered by poor urban infrastructure. Transport emissions of greenhouse gases contribute substantially to regional and global climate change, which compound public health risks from multiple factors. Despite these complex challenges, technological advances and innovations in planning and policy stand to make China a leader in sustainable, healthy transportation. PMID:29047445

Development of a Quantitative Methodology to Assess the Impacts of Urban Transport Interventions and Related Noise on Well-Being

PubMed Central

Braubach, Matthias; Tobollik, Myriam; Mudu, Pierpaolo; Hiscock, Rosemary; Chapizanis, Dimitris; Sarigiannis, Denis A.; Keuken, Menno; Perez, Laura; Martuzzi, Marco

2015-01-01

Well-being impact assessments of urban interventions are a difficult challenge, as there is no agreed methodology and scarce evidence on the relationship between environmental conditions and well-being. The European Union (EU) project “Urban Reduction of Greenhouse Gas Emissions in China and Europe” (URGENCHE) explored a methodological approach to assess traffic noise-related well-being impacts of transport interventions in three European cities (Basel, Rotterdam and Thessaloniki) linking modeled traffic noise reduction effects with survey data indicating noise-well-being associations. Local noise models showed a reduction of high traffic noise levels in all cities as a result of different urban interventions. Survey data indicated that perception of high noise levels was associated with lower probability of well-being. Connecting the local noise exposure profiles with the noise-well-being associations suggests that the urban transport interventions may have a marginal but positive effect on population well-being. This paper also provides insight into the methodological challenges of well-being assessments and highlights the range of limitations arising from the current lack of reliable evidence on environmental conditions and well-being. Due to these limitations, the results should be interpreted with caution. PMID:26016437

Development of a quantitative methodology to assess the impacts of urban transport interventions and related noise on well-being.

PubMed

Braubach, Matthias; Tobollik, Myriam; Mudu, Pierpaolo; Hiscock, Rosemary; Chapizanis, Dimitris; Sarigiannis, Denis A; Keuken, Menno; Perez, Laura; Martuzzi, Marco

2015-05-26

Well-being impact assessments of urban interventions are a difficult challenge, as there is no agreed methodology and scarce evidence on the relationship between environmental conditions and well-being. The European Union (EU) project "Urban Reduction of Greenhouse Gas Emissions in China and Europe" (URGENCHE) explored a methodological approach to assess traffic noise-related well-being impacts of transport interventions in three European cities (Basel, Rotterdam and Thessaloniki) linking modeled traffic noise reduction effects with survey data indicating noise-well-being associations. Local noise models showed a reduction of high traffic noise levels in all cities as a result of different urban interventions. Survey data indicated that perception of high noise levels was associated with lower probability of well-being. Connecting the local noise exposure profiles with the noise-well-being associations suggests that the urban transport interventions may have a marginal but positive effect on population well-being. This paper also provides insight into the methodological challenges of well-being assessments and highlights the range of limitations arising from the current lack of reliable evidence on environmental conditions and well-being. Due to these limitations, the results should be interpreted with caution.

Characterizing heavy metal build-up on urban road surfaces: implication for stormwater reuse.

PubMed

Liu, An; Liu, Liang; Li, Dunzhu; Guan, Yuntao

2015-05-15

Stormwater reuse is increasingly popular in the worldwide. In terms of urban road stormwater, it commonly contains toxic pollutants such as heavy metals, which could undermine the reuse safety. The research study investigated heavy metal build-up characteristics on urban roads in a typical megacity of South China. The research outcomes show the high variability in heavy metal build-up loads among different urban road sites. The degree of traffic congestion and road surface roughness was found to exert a more significant influence on heavy metal build-up rather than traffic volume. Due to relatively higher heavy metal loads, stormwater from roads with more congested traffic conditions or rougher surfaces might be suitable for low-water-quality required activities while the stormwater from by-pass road sections could be appropriate for relatively high-water-quality required purposes since the stormwater could be relatively less polluted. Based on the research outcomes, a decision-making process for heavy metals based urban road stormwater reuse was proposed. The new finding highlights the importance to undertaking a "fit-for-purpose" road stormwater reuse strategy. Additionally, the research results can also contribute to enhancing stormwater reuse safety. Copyright © 2015 Elsevier B.V. All rights reserved.

Enhanced Framework for Modeling Urban Truck Trips

DOT National Transportation Integrated Search

1998-09-16

Recently there has been renewed interest in modeling urban truck movements. : This is potentially important for improving traffic forecasts as well as for a : host of other applications including ITS. There are unique aspects of urban : freight movem...

Assessing the resilience of urban areas to traffic-related air pollution: Application in Greater Paris.

PubMed

Cariolet, Jean-Marie; Colombert, Morgane; Vuillet, Marc; Diab, Youssef

2018-02-15

Recent studies report that outdoor air pollution will become the main environmental cause of premature death over the next few decades (OECD, 2012; WHO, 2014; World Bank, 2016). Cities are considered hot spots and urban populations are particularly exposed. There is therefore an urgent need to adapt urban systems and urban design to tackle this issue. While most European cities have introduced measures to reduce emissions, action is still required to reduce concentrations and exposure, and a holistic approach to urban design is badly needed. The concept of urban resilience, defined by Holling (1987) as the ability of a city to absorb a disturbance while maintaining its functions and structures, may offer a new paradigm for tackling urban air pollution. We propose to adapt the concept of urban resilience to outdoor air pollution. A method has been developed to assess the resilience of an urban area to outdoor air pollution. Three "resilience capacities" have been identified: the capacity of an urban area to decrease air pollution emissions, the capacity to decrease concentrations and the capacity to decrease exposure. The calculation is based on the analysis of urban design, defined as the pattern of buildings as well as the structural elements that define an urban area (urban morphology; transport network, services and land use). For each resilience capacity, indicators are calculated using a Geographic Information System (GIS) and a grid-based approach. This method has been implemented in the Greater Paris area within a 500m grid-cell system. Greater Paris is one of the densest urban areas in Europe and experiences high air pollution levels. The proposed "quick scan" method helps to localize areas where specific action is needed. Copyright © 2017 Elsevier B.V. All rights reserved.

[Reduction of automobile traffic: urgent health promotion policy].

PubMed

Tapia Granados, J A

1998-03-01

During the last few decades, traffic injuries have become one of the leading causes of death and disability in the world. In urban areas, traffic congestion, noise, and emissions from motor vehicles produce subjective disturbances and detectable pathological effects. More than one billion people are exposed to harmful levels of environmental pollution. Because its combustion engine generates carbon dioxide (CO2), the automobile is one of the chief sources of the gases that are causing the greenhouse effect. The latter has already caused a rise in the average ambient temperature, and over the next decades it will predictable cause significant climatic changes whose consequences, though uncertain, are likely to be harmful and possibly catastrophic. Aside from the greenhouse effect, the relentless growth of parking zones, traffic, and the roadway infrastructure in urban and rural areas is currently one of the leading causes of environmental degradation. Urban development, which is nearly always "planned" around traffic instead of people, leads to a significant deterioration in the quality of life, while it also destroys the social fabric. Unlike the private automobile, public transportation, bicycles, and walking help reduce pollution, congestion, and traffic volume, as well as the morbidity and mortality resulting from injuries and ailments related to pollution. Non-automobile transportation also encourages physical activity--with its positive effect on general health--and helps reduce the greenhouse effect. The drop in traffic volume and the increased use of alternate means of transportation are thus an integrated health promotion policy which should become an inherent part of the movement for the promotion of healthy cities and of transportation policies and economic policy in general.

Active transportation safety features around schools in Canada.

PubMed

Pinkerton, Bryn; Rosu, Andrei; Janssen, Ian; Pickett, William

2013-10-31

The purpose of this study was to describe the presence and quality of active transportation safety features in Canadian school environments that relate to pedestrian and bicycle safety. Variations in these features and associated traffic concerns as perceived by school administrators were examined by geographic status and school type. The study was based on schools that participated in 2009/2010 Health Behaviour in School-aged Children (HBSC) survey. ArcGIS software version 10 and Google Earth were used to assess the presence and quality of ten different active transportation safety features. Findings suggest that there are crosswalks and good sidewalk coverage in the environments surrounding most Canadian schools, but a dearth of bicycle lanes and other traffic calming measures (e.g., speed bumps, traffic chokers). Significant urban/rural inequities exist with a greater prevalence of sidewalk coverage, crosswalks, traffic medians, and speed bumps in urban areas. With the exception of bicycle lanes, the active transportation safety features that were present were generally rated as high quality. Traffic was more of a concern to administrators in urban areas. This study provides novel information about active transportation safety features in Canadian school environments. This information could help guide public health efforts aimed at increasing active transportation levels while simultaneously decreasing active transportation injuries.

Active Transportation Safety Features around Schools in Canada

PubMed Central

Pinkerton, Bryn; Rosu, Andrei; Janssen, Ian; Pickett, William

2013-01-01

The purpose of this study was to describe the presence and quality of active transportation safety features in Canadian school environments that relate to pedestrian and bicycle safety. Variations in these features and associated traffic concerns as perceived by school administrators were examined by geographic status and school type. The study was based on schools that participated in 2009/2010 Health Behaviour in School-aged Children (HBSC) survey. ArcGIS software version 10 and Google Earth were used to assess the presence and quality of ten different active transportation safety features. Findings suggest that there are crosswalks and good sidewalk coverage in the environments surrounding most Canadian schools, but a dearth of bicycle lanes and other traffic calming measures (e.g., speed bumps, traffic chokers). Significant urban/rural inequities exist with a greater prevalence of sidewalk coverage, crosswalks, traffic medians, and speed bumps in urban areas. With the exception of bicycle lanes, the active transportation safety features that were present were generally rated as high quality. Traffic was more of a concern to administrators in urban areas. This study provides novel information about active transportation safety features in Canadian school environments. This information could help guide public health efforts aimed at increasing active transportation levels while simultaneously decreasing active transportation injuries. PMID:24185844

Preliminary results of the aerosol optical depth retrieval in Johor, Malaysia

NASA Astrophysics Data System (ADS)

Lim, H. Q.; Kanniah, K. D.; Lau, A. M. S.

2014-02-01

Monitoring of atmospheric aerosols over the urban area is important as tremendous amounts of pollutants are released by industrial activities and heavy traffic flow. Air quality monitoring by satellite observation provides better spatial coverage, however, detailed aerosol properties retrieval remains a challenge. This is due to the limitation of aerosol retrieval algorithm on high reflectance (bright surface) areas. The aim of this study is to retrieve aerosol optical depth over urban areas of Iskandar Malaysia; the main southern development zone in Johor state, using Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m resolution data. One of the important steps is the aerosol optical depth retrieval is to characterise different types of aerosols in the study area. This information will be used to construct a Look Up Table containing the simulated aerosol reflectance and corresponding aerosol optical depth. Thus, in this study we have characterised different aerosol types in the study area using Aerosol Robotic Network (AERONET) data. These data were processed using cluster analysis and the preliminary results show that the area is consisting of coastal urban (65%), polluted urban (27.5%), dust particles (6%) and heavy pollution (1.5%) aerosols.

Driving simulator evaluation of drivers' response to intersections with dynamic use of exit-lanes for left-turn.

PubMed

Zhao, Jing; Yun, Meiping; Zhang, H Michael; Yang, Xiaoguang

2015-08-01

With the worsening of urban traffic congestion in large cities around the world, researchers have been looking for unconventional designs and/or controls to squeeze more capacity out of intersections, the most common bottlenecks of the road network. One of these innovative intersection designs, known as the exit-lanes for left-turn (EFL), opens up exit-lanes to be used by left-turn traffic with the help of an additional traffic light installed at the median opening (the pre-signal). This paper studies how drivers respond to EFL intersections with a series of driving simulator experiments. In our experiments, 64 drivers were recruited and divided into two groups. One group is trained to use the EFL while the other group is not. In addition, four scenarios were considered with different sign and marking designs and traffic conditions in the experiments. Results indicate that drivers show certain amount of confusion and hesitation when encountering an EFL intersection for the first time. They can be overcome, however, by increasing exposure through driver education or by cue provided from other vehicles. Moreover, drivers unfamiliar with EFL operation can make a left turn using the conventional left-turn lanes as usual. The EFL operation is not likely to pose any serious safety risk of the intersection in real life operations. Copyright © 2015 Elsevier Ltd. All rights reserved.