Adaptive traffic signal control system (ACS-Lite) for Wolf Road, Albany, New York.

DOT National Transportation Integrated Search

2014-10-01

Adaptive Control Software Lite (ACS : - : Lite) is a : traffic : signal timing optimization system that : dynamically adjusts : traffic : signal timing : s : to meet current traffic demands. : The purpose of this : research project : was : to : deplo...

How do Air Traffic Controllers Use Automation and Tools Differently During High Demand Situations?

NASA Technical Reports Server (NTRS)

Kraut, Joshua M.; Mercer, Joey; Morey, Susan; Homola, Jeffrey; Gomez, Ashley; Prevot, Thomas

2013-01-01

In a human-in-the-loop simulation, two air traffic controllers managed identical airspace while burdened with higher than average workload, and while using advanced tools and automation designed to assist with scheduling aircraft on multiple arrival flows to a single meter fix. This paper compares the strategies employed by each controller, and investigates how the controllers' strategies change while managing their airspace under more normal workload conditions and a higher workload condition. Each controller engaged in different methods of maneuvering aircraft to arrive on schedule, and adapted their strategies to cope with the increased workload in different ways. Based on the conclusions three suggestions are made: that quickly providing air traffic controllers with recommendations and information to assist with maneuvering and scheduling aircraft when burdened with increased workload will improve the air traffic controller's effectiveness, that the tools should adapt to the strategy currently employed by a controller, and that training should emphasize which traffic management strategies are most effective given specific airspace demands.

Trajectory Planning by Preserving Flexibility: Metrics and Analysis

NASA Technical Reports Server (NTRS)

Idris, Husni R.; El-Wakil, Tarek; Wing, David J.

2008-01-01

In order to support traffic management functions, such as mitigating traffic complexity, ground and airborne systems may benefit from preserving or optimizing trajectory flexibility. To help support this hypothesis trajectory flexibility metrics have been defined in previous work to represent the trajectory robustness and adaptability to the risk of violating safety and traffic management constraints. In this paper these metrics are instantiated in the case of planning a trajectory with the heading degree of freedom. A metric estimation method is presented based on simplifying assumptions, namely discrete time and heading maneuvers. A case is analyzed to demonstrate the estimation method and its use in trajectory planning in a situation involving meeting a time constraint and avoiding loss of separation with nearby traffic. The case involves comparing path-stretch trajectories, in terms of adaptability and robustness along each, deduced from a map of estimated flexibility metrics over the solution space. The case demonstrated anecdotally that preserving flexibility may result in enhancing certain factors that contribute to traffic complexity, namely reducing proximity and confrontation.

Drivers' safety needs, behavioural adaptations and acceptance of new driving support systems.

PubMed

Saad, Farida; Van Elslande, Pierre

2012-01-01

The aim of this paper is to discuss the contribution of two complementary approaches for designing and evaluating new driver support systems likely to improve the operation and safety of the road traffic system. The first approach is based on detailed analyses of traffic crashes so as to estimate drivers' needs for assistance and the situational constraints that safety functions should address to be efficient. The second approach is based on in depth-analyses of behavioral adaptations induced by the usage of new driver support systems in regular driving situations and on drivers' acceptance of the assistance provided by the systems.

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.

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

PubMed Central

Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.

2017-01-01

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. PMID:28445398

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

PubMed

Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

2017-04-26

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

Cooperative Vehicular Traffic Monitoring in Realistic Low Penetration Scenarios: The COLOMBO Experience

PubMed Central

Caselli, Federico; Corradi, Antonio

2018-01-01

The relevance of effective and efficient solutions for vehicle traffic surveillance is widely recognized in order to enable advanced strategies for traffic management, e.g., based on dynamically adaptive and decentralized traffic light management. However, most related solutions in the literature, based on the powerful enabler of cooperative vehicular communications, assume the complete penetration rate of connectivity/communication technologies (and willingness to participate in the collaborative surveillance service) over the targeted vehicle population, thus making them not applicable nowadays. The paper originally proposes an innovative solution for cooperative traffic surveillance based on vehicular communications capable of: (i) working with low penetration rates of the proposed technology and (ii) of collecting a large set of monitoring data about vehicle mobility in targeted areas of interest. The paper presents insights and lessons learnt from the design and implementation work of the proposed solution. Moreover, it reports extensive performance evaluation results collected on realistic simulation scenarios based on the usage of iTETRIS with real traces of vehicular traffic of the city of Bologna. The reported results show the capability of our proposal to consistently estimate the real vehicular traffic even with low penetration rates of our solution (only 10%). PMID:29522427

Decision-making tool for applying adaptive traffic control systems : final report.

DOT National Transportation Integrated Search

2016-03-01

Adaptive traffic signal control technologies have been increasingly deployed in real world situations. The objective of this project was to develop a decision-making tool to guide traffic engineers and decision-makers who must decide whether or not a...

Advancing interconnect density for spiking neural network hardware implementations using traffic-aware adaptive network-on-chip routers.

PubMed

Carrillo, Snaider; Harkin, Jim; McDaid, Liam; Pande, Sandeep; Cawley, Seamus; McGinley, Brian; Morgan, Fearghal

2012-09-01

The brain is highly efficient in how it processes information and tolerates faults. Arguably, the basic processing units are neurons and synapses that are interconnected in a complex pattern. Computer scientists and engineers aim to harness this efficiency and build artificial neural systems that can emulate the key information processing principles of the brain. However, existing approaches cannot provide the dense interconnect for the billions of neurons and synapses that are required. Recently a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an efficient, robust computing platform. However, the use of the NoC as an interconnection fabric for large-scale SNNs demands a good trade-off between scalability, throughput, neuron/synapse ratio and power consumption. This paper presents a novel traffic-aware, adaptive NoC router, which forms part of a proposed embedded mixed-signal SNN architecture called EMBRACE (EMulating Biologically-inspiRed ArChitectures in hardwarE). The proposed adaptive NoC router provides the inter-neuron connectivity for EMBRACE, maintaining router communication and avoiding dropped router packets by adapting to router traffic congestion. Results are presented on throughput, power and area performance analysis of the adaptive router using a 90 nm CMOS technology which outperforms existing NoCs in this domain. The adaptive behaviour of the router is also verified on a Stratix II FPGA implementation of a 4 × 2 router array with real-time traffic congestion. The presented results demonstrate the feasibility of using the proposed adaptive NoC router within the EMBRACE architecture to realise large-scale SNNs on embedded hardware. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

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...

Congestion control for a fair packet delivery in WSN: from a complex system perspective.

PubMed

Aguirre-Guerrero, Daniela; Marcelín-Jiménez, Ricardo; Rodriguez-Colina, Enrique; Pascoe-Chalke, Michael

2014-01-01

In this work, we propose that packets travelling across a wireless sensor network (WSN) can be seen as the active agents that make up a complex system, just like a bird flock or a fish school, for instance. From this perspective, the tools and models that have been developed to study this kind of systems have been applied. This is in order to create a distributed congestion control based on a set of simple rules programmed at the nodes of the WSN. Our results show that it is possible to adapt the carried traffic to the network capacity, even under stressing conditions. Also, the network performance shows a smooth degradation when the traffic goes beyond a threshold which is settled by the proposed self-organized control. In contrast, without any control, the network collapses before this threshold. The use of the proposed solution provides an effective strategy to address some of the common problems found in WSN deployment by providing a fair packet delivery. In addition, the network congestion is mitigated using adaptive traffic mechanisms based on a satisfaction parameter assessed by each packet which has impact on the global satisfaction of the traffic carried by the WSN.

RHODES-ITMS Tempe field test project : implementation and field testing of RHODES, a real-time traffic adaptive control system

DOT National Transportation Integrated Search

2001-09-01

RHODES is a traffic-adaptive signal control system that optimally controls the traffic that is observed in real time. The RHODES-ITMS Program is the application of the RHODES strategy for the two intersections of a freeway-arterial diamond interchang...

Congestion-based emergency vehicle preemption.

DOT National Transportation Integrated Search

2010-08-01

This research analyzed and evaluated a new strategy for preemption of emergency vehicles along a corridor, which is : route-based and adaptive to real-time traffic conditions. The method uses dynamic offsets which are adjusted using : congestion-leve...

Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers.

PubMed

Oviedo-Trespalacios, Oscar; Haque, Md Mazharul; King, Mark; Washington, Simon

2017-04-01

The use of mobile phones while driving remains a major human factors issue in the transport system. A significant safety concern is that driving while distracted by a mobile phone potentially modifies the driving speed leading to conflicts with other road users and consequently increases crash risk. However, the lack of systematic knowledge of the mechanisms involved in speed adaptation of distracted drivers constrains the explanation and modelling of the extent of this phenomenon. The objective of this study was to investigate speed adaptation of distracted drivers under varying road infrastructure and traffic complexity conditions. The CARRS-Q Advanced Driving Simulator was used to test participants on a simulated road with different traffic conditions, such as free flow traffic along straight roads, driving in urbanized areas, and driving in heavy traffic along suburban roads. Thirty-two licensed young drivers drove the simulator under three phone conditions: baseline (no phone conversation), hands-free and handheld phone conversations. To understand the relationships between distraction, road infrastructure and traffic complexity, speed adaptation calculated as the deviation of driving speed from the posted speed limit was modelled using a decision tree. The identified groups of road infrastructure and traffic characteristics from the decision tree were then modelled with a Generalized Linear Mixed Model (GLMM) with repeated measures to develop inferences about speed adaptation behaviour of distracted drivers. The GLMM also included driver characteristics and secondary task demands as predictors of speed adaptation. Results indicated that complex road environments like urbanization, car-following situations along suburban roads, and curved road alignment significantly influenced speed adaptation behaviour. Distracted drivers selected a lower speed while driving along a curved road or during car-following situations, but speed adaptation was negligible in the presence of high visual cutter, indicating the prioritization of the driving task over the secondary task. Additionally, drivers who scored high on self-reported safe attitudes towards mobile phone usage, and who reported prior involvement in a road traffic crash, selected a lower driving speed in the distracted condition than in the baseline. The results aid in understanding how driving task demands influence speed adaptation of distracted drivers under various road infrastructure and traffic complexity conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficient hybrid monocular-stereo approach to on-board video-based traffic sign detection and tracking

NASA Astrophysics Data System (ADS)

Marinas, Javier; Salgado, Luis; Arróspide, Jon; Camplani, Massimo

2012-01-01

In this paper we propose an innovative method for the automatic detection and tracking of road traffic signs using an onboard stereo camera. It involves a combination of monocular and stereo analysis strategies to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. Firstly, an adaptive color and appearance based detection is applied at single camera level to generate a set of traffic sign hypotheses. In turn, stereo information allows for sparse 3D reconstruction of potential traffic signs through a SURF-based matching strategy. Namely, the plane that best fits the cloud of 3D points traced back from feature matches is estimated using a RANSAC based approach to improve robustness to outliers. Temporal consistency of the 3D information is ensured through a Kalman-based tracking stage. This also allows for the generation of a predicted 3D traffic sign model, which is in turn used to enhance the previously mentioned color-based detector through a feedback loop, thus improving detection accuracy. The proposed solution has been tested with real sequences under several illumination conditions and in both urban areas and highways, achieving very high detection rates in challenging environments, including rapid motion and significant perspective distortion.

Simulating and evaluating an adaptive and integrated traffic lights control system for smart city application

NASA Astrophysics Data System (ADS)

Djuana, E.; Rahardjo, K.; Gozali, F.; Tan, S.; Rambung, R.; Adrian, D.

2018-01-01

A city could be categorized as a smart city when the information technology has been developed to the point that the administration could sense, understand, and control every resource to serve its people and sustain the development of the city. One of the smart city aspects is transportation and traffic management. This paper presents a research project to design an adaptive traffic lights control system as a part of the smart system for optimizing road utilization and reducing congestion. Research problems presented include: (1) Congestion in one direction toward an intersection due to dynamic traffic condition from time to time during the day, while the timing cycles in traffic lights system are mostly static; (2) No timing synchronization among traffic lights in adjacent intersections that is causing unsteady flows; (3) Difficulties in traffic condition monitoring on the intersection and the lack of facility for remotely controlling traffic lights. In this research, a simulator has been built to model the adaptivity and integration among different traffic lights controllers in adjacent intersections, and a case study consisting of three sets of intersections along Jalan K. H. Hasyim Ashari has been simulated. It can be concluded that timing slots synchronization among traffic lights is crucial for maintaining a steady traffic flow.

Adaptive video-based vehicle classification technique for monitoring traffic.

DOT National Transportation Integrated Search

2015-08-01

This report presents a methodology for extracting two vehicle features, vehicle length and number of axles in order : to classify the vehicles from video, based on Federal Highway Administration (FHWA)s recommended vehicle : classification scheme....

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.

Towards a Cloud Based Smart Traffic Management Framework

NASA Astrophysics Data System (ADS)

Rahimi, M. M.; Hakimpour, F.

2017-09-01

Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM) real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

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 ...

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

DOE PAGES

Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

2015-01-31

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

PubMed Central

Fontaine, Michael D.

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. PMID:23766690

A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.

PubMed

Xia, Yingjie; Hu, Jia; Fontaine, Michael D

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

Distributed Traffic Complexity Management by Preserving Trajectory Flexibility

NASA Technical Reports Server (NTRS)

Idris, Husni; Vivona, Robert A.; Garcia-Chico, Jose-Luis; Wing, David J.

2007-01-01

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which groundbased service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. This paper presents preliminary research investigating a distributed trajectory-oriented approach to manage traffic complexity, based on preserving trajectory flexibility. The underlying hypotheses are that preserving trajectory flexibility autonomously by aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by collaboratively minimizing trajectory constraints without jeopardizing the intended air traffic management objectives. This paper presents an analytical framework in which flexibility is defined in terms of robustness and adaptability to disturbances and preliminary metrics are proposed that can be used to preserve trajectory flexibility. The hypothesized impacts are illustrated through analyzing a trajectory solution space in a simple scenario with only speed as a degree of freedom, and in constraint situations involving meeting multiple times of arrival and resolving conflicts.

Effective distance adaptation traffic dispatching in software defined IP over optical network

NASA Astrophysics Data System (ADS)

Duan, Zhiwei; Li, Hui; Liu, Yuze; Ji, Yuefeng; Li, Hongfa; Lin, Yi

2017-10-01

The rapid growth of IP traffic has contributed to the wide deployment of optical devices (ROADM/OXC, etc.). Meanwhile, with the emergence and application of high-performance network services such as ultra-high video transmission, people are increasingly becoming more and more particular about the quality of service (QoS) of network. However, the pass-band shape of WSSs which is utilized in the ROADM/OXC is not ideal, causing narrowing of spectrum. Spectral narrowing can lead to signal impairment. Therefore, guard-bands need to be inserted between adjacent paths. In order to minimize the bandwidth waste due to guard bands, we propose an effective distance-adaptation traffic dispatching algorithm in IP over optical network based on SDON architecture. We use virtualization technology to set up virtual resources direct links by extracting part of the resources on paths which meet certain specific constraints. We also assign different bandwidth to each IP request based on path length. There is no need for guard-bands between the adjacent paths on the virtual link, which can effectively reduce the number of guard-bands and save the spectrum.

Evaluation of New Jersey Route 18 OPAC/MIST traffic-control system

DOT National Transportation Integrated Search

1997-01-01

Conventional traffic-control strategies have limitations in handling unanticipated traffic demands. An adaptive traffic-signal control is expected to mitigate this problem and improve overall system performance. Furthermore, with the increasing needs...

Detection of network attacks based on adaptive resonance theory

NASA Astrophysics Data System (ADS)

Bukhanov, D. G.; Polyakov, V. M.

2018-05-01

The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.

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 ...

Design and implementation of priority and time-window based traffic scheduling and routing-spectrum allocation mechanism in elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan

2016-02-01

With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.

Advanced driver assistance system: Road sign identification using VIAPIX system and a correlation technique

NASA Astrophysics Data System (ADS)

Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.

2017-02-01

We present a three-step approach based on the commercial VIAPIX® module for road traffic sign recognition and identification. Firstly, detection in a scene of all objects having characteristics of traffic signs is performed. This is followed by a first-level recognition based on correlation which consists in making a comparison between each detected object with a set of reference images of a database. Finally, a second level of identification allows us to confirm or correct the previous identification. In this study, we perform a correlation-based analysis by combining and adapting the Vander Lugt correlator with the nonlinear joint transformation correlator (JTC). Of particular significance, this approach permits to make a reliable decision on road traffic sign identification. We further discuss a robust scheme allowing us to track a detected road traffic sign in a video sequence for the purpose of increasing the decision performance of our system. This approach can have broad practical applications in the maintenance and rehabilitation of transportation infrastructure, or for drive assistance.

Preliminary Investigation of Workload on Intrastate Bus Traffic Controllers

NASA Astrophysics Data System (ADS)

Yen Bin, Teo; Azlis-Sani, Jalil; Nur Annuar Mohd Yunos, Muhammad; Ismail, S. M. Sabri S. M.; Tajedi, Noor Aqilah Ahmad

2016-11-01

The daily routine of bus traffic controller which involves high mental processes would have a direct impact on the level of workload. To date, the level of workload on the bus traffic controllers in Malaysia is relatively unknown. Excessive workload on bus traffic controllers would affect the control and efficiency of the system. This paper served to study the workload on bus traffic controllers and justify the needs to conduct further detailed research on this field. The objectives of this research are to identify the level of workload on the intrastate bus traffic controllers. Based on the results, recommendations will be proposed for improvements and future studies. The level of workload for the bus traffic controllers is quantified using questionnaire adapted from NASA TLX. Interview sessions were conducted for validation of workload. Sixteen respondents were involved and it was found that the average level of workload based on NASA TLX was 6.91. It was found that workload is not affected by gender and marital status. This study also showed that the level of workload and working experience of bus traffic controllers has a strong positive linear relationship. This study would serve as a guidance and reference related to this field. Since this study is a preliminary investigation, further detailed studies could be conducted to obtain a better comprehension regarding the bus traffic controllers.

Adaptive automation of human-machine system information-processing functions.

PubMed

Kaber, David B; Wright, Melanie C; Prinzel, Lawrence J; Clamann, Michael P

2005-01-01

The goal of this research was to describe the ability of human operators to interact with adaptive automation (AA) applied to various stages of complex systems information processing, defined in a model of human-automation interaction. Forty participants operated a simulation of an air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making), and AA is superior to completely manual control. Potential applications of this research include the design of automation to support air traffic controller information processing.

A tracked robot with novel bio-inspired passive "legs".

PubMed

Sun, Bo; Jing, Xingjian

2017-01-01

For track-based robots, an important aspect is the suppression design, which determines the trafficability and comfort of the whole system. The trafficability limits the robot's working capability, and the riding comfort limits the robot's working effectiveness, especially with some sensitive instruments mounted on or operated. To these aims, a track-based robot equipped with a novel passive bio-inspired suspension is designed and studied systematically in this paper. Animal or insects have very special leg or limb structures which are good for motion control and adaptable to different environments. Inspired by this, a new track-based robot is designed with novel "legs" for connecting the loading wheels to the robot body. Each leg is designed with passive structures and can achieve very high loading capacity but low dynamic stiffness such that the robot can move on rough ground similar to a multi-leg animal or insect. Therefore, the trafficability and riding comfort can be significantly improved without losing loading capacity. The new track-based robot can be well applied to various engineering tasks for providing a stable moving platform of high mobility, better trafficability and excellent loading capacity.

InSync Adaptive Traffic Control System for the Veterans Memorial Hwy Corridor on Long Island, NY

DOT National Transportation Integrated Search

2012-08-01

This report documents Rhythm Engineerings adaptive traffic control system field installation performed : by New York State Department of Transportation (NYSDOT) along Veterans Memorial Hwy in Long : Island, NY. This report reviews the reason for t...

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

Wu, Song; Wang, Yihong; Luo, Wei

In virtualized data centers, virtual disk images (VDIs) serve as the containers in virtual environment, so their access performance is critical for the overall system performance. Some distributed VDI chunk storage systems have been proposed in order to alleviate the I/O bottleneck for VM management. As the system scales up to a large number of running VMs, however, the overall network traffic would become unbalanced with hot spots on some VMs inevitably, leading to I/O performance degradation when accessing the VMs. Here, we propose an adaptive and collaborative VDI storage system (ACStor) to resolve the above performance issue. In comparisonmore » with the existing research, our solution is able to dynamically balance the traffic workloads in accessing VDI chunks, based on the run-time network state. Specifically, compute nodes with lightly loaded traffic will be adaptively assigned more chunk access requests from remote VMs and vice versa, which can effectively eliminate the above problem and thus improves the I/O performance of VMs. We also implement a prototype based on our ACStor design, and evaluate it by various benchmarks on a real cluster with 32 nodes and a simulated platform with 256 nodes. Experiments show that under different network traffic patterns of data centers, our solution achieves up to 2-8 performance gain on VM booting time and VM’s I/O throughput, in comparison with the other state-of-the-art approaches.« less

The big and intricate dreams of little organelles: Embracing complexity in the study of membrane traffic.

PubMed

Liu, Allen P; Botelho, Roberto J; Antonescu, Costin N

2017-09-01

Compartmentalization of eukaryotic cells into dynamic organelles that exchange material through regulated membrane traffic governs virtually every aspect of cellular physiology including signal transduction, metabolism and transcription. Much has been revealed about the molecular mechanisms that control organelle dynamics and membrane traffic and how these processes are regulated by metabolic, physical and chemical cues. From this emerges the understanding of the integration of specific organellar phenomena within complex, multiscale and nonlinear regulatory networks. In this review, we discuss systematic approaches that revealed remarkable insight into the complexity of these phenomena, including the use of proximity-based proteomics, high-throughput imaging, transcriptomics and computational modeling. We discuss how these methods offer insights to further understand molecular versatility and organelle heterogeneity, phenomena that allow a single organelle population to serve a range of physiological functions. We also detail on how transcriptional circuits drive organelle adaptation, such that organelles may shift their function to better serve distinct differentiation and stress conditions. Thus, organelle dynamics and membrane traffic are functionally heterogeneous and adaptable processes that coordinate with higher-order system behavior to optimize cell function under a range of contexts. Obtaining a comprehensive understanding of organellar phenomena will increasingly require combined use of reductionist and system-based approaches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

Analysis and improvement measures of flight delay in China

NASA Astrophysics Data System (ADS)

Zang, Yuhang

2017-03-01

Firstly, this paper establishes the principal component regression model to analyze the data quantitatively, based on principal component analysis to get the three principal component factors of flight delays. Then the least square method is used to analyze the factors and obtained the regression equation expression by substitution, and then found that the main reason for flight delays is airlines, followed by weather and traffic. Aiming at the above problems, this paper improves the controllable aspects of traffic flow control. For reasons of traffic flow control, an adaptive genetic queuing model is established for the runway terminal area. This paper, establish optimization method that fifteen planes landed simultaneously on the three runway based on Beijing capital international airport, comparing the results with the existing FCFS algorithm, the superiority of the model is proved.

Value of Information for Optimal Adaptive Routing in Stochastic Time-Dependent Traffic Networks: Algorithms and Computational Tools

DOT National Transportation Integrated Search

2010-10-25

Real-time information is important for travelers' routing decisions in uncertain networks by enabling online adaptation to revealed traffic conditions. Usually there are spatial and/or temporal limitations in traveler information. In this research, a...

Substantiation of Structure of Adaptive Control Systems for Motor Units

NASA Astrophysics Data System (ADS)

Ovsyannikov, S. I.

2018-05-01

The article describes the development of new electronic control systems, in particular motor units, for small-sized agricultural equipment. Based on the analysis of traffic control systems, the main course of development of the conceptual designs of motor units has been defined. The systems aimed to control the course motion of the motor unit in automatic mode using the adaptive systems have been developed. The article presents structural models of the conceptual motor units based on electrically controlled systems by the operation of drive motors and adaptive systems that make the motor units completely automated.

Next-generation smart traffic signals : RHODES with Intellidrive, the self-taught traffic control system.

DOT National Transportation Integrated Search

2009-01-01

Can a self-calibrating signal control system lead to wider adoption of adaptive traffic control systems? The focus of Next Generation of Smart Traffic Signals, an Exploratory Advanced Research (EAR) Program project, is a system that-with lit...

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.

Evaluation of an adaptive traffic signal system : route 291 in Lee's Summit, Missouri.

DOT National Transportation Integrated Search

2010-03-01

An adaptive traffic signal system was installed on a 12-signal, 2.5-mi arterial in Lees Summit, Missouri in the Spring : of 2008. An evaluation of travel time, delay, number of stops, fuel consumption, and emissions was conducted, which : compared...

A travel time forecasting model based on change-point detection method

NASA Astrophysics Data System (ADS)

LI, Shupeng; GUANG, Xiaoping; QIAN, Yongsheng; ZENG, Junwei

2017-06-01

Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. A travel time forecasting model is proposed for urban road traffic sensors data based on the method of change-point detection in this paper. The first-order differential operation is used for preprocessing over the actual loop data; a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns; then a travel time forecasting model is established based on autoregressive integrated moving average (ARIMA) model. By computer simulation, different control parameters are chosen for adaptive change point search for travel time series, which is divided into several sections of similar state.Then linear weight function is used to fit travel time sequence and to forecast travel time. The results show that the model has high accuracy in travel time forecasting.

Traveling With Success, How Local Governments Use Intelligent Transportation Systems

DOT National Transportation Integrated Search

1995-01-01

ELECTRONIC TOLL COLLECTION AND TRAFFIC MANAGEMENT OR ETC/ETTM, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS, ADVANCED TRAVELER INFORMATION SYSTEMS OR ATIS, ELECTRONIC PAYMENTS SYSTEMS, TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, TRANSIT MANAGEM...

Self-Organized Transport System

DOT National Transportation Integrated Search

2009-09-28

This report presents the findings of the simulation model for a self-organized transport system where traffic lights communicate with neighboring traffic lights and make decisions locally to adapt to traffic conditions in real time. The model is insp...

Enhancing TSM&O strategies through life cycle benefit/cost analysis : life cycle benefit/cost analysis & life cycle assessment of adaptive traffic control systems and ramp metering systems.

DOT National Transportation Integrated Search

2015-05-01

The research team developed a comprehensive Benefit/Cost (B/C) analysis framework to evaluate existing and anticipated : intelligent transportation system (ITS) strategies, particularly, adaptive traffic control systems and ramp metering systems, : i...

Traffic-Adaptive, Flow-Specific Medium Access for Wireless Networks

DTIC Science & Technology

2009-09-01

hybrid, contention and non-contention schemes are shown to be special cases. This work also compares the energy efficiency of centralized and distributed...solutions and proposes an energy efficient version of traffic-adaptive CWS-MAC that includes an adaptive sleep cycle coordinated through the use of...preamble sampling. A preamble sampling probability parameter is introduced to manage the trade-off between energy efficiency and throughput and delay

ACStor: Optimizing Access Performance of Virtual Disk Images in Clouds

DOE PAGES

Wu, Song; Wang, Yihong; Luo, Wei; ...

2017-03-02

In virtualized data centers, virtual disk images (VDIs) serve as the containers in virtual environment, so their access performance is critical for the overall system performance. Some distributed VDI chunk storage systems have been proposed in order to alleviate the I/O bottleneck for VM management. As the system scales up to a large number of running VMs, however, the overall network traffic would become unbalanced with hot spots on some VMs inevitably, leading to I/O performance degradation when accessing the VMs. Here, we propose an adaptive and collaborative VDI storage system (ACStor) to resolve the above performance issue. In comparisonmore » with the existing research, our solution is able to dynamically balance the traffic workloads in accessing VDI chunks, based on the run-time network state. Specifically, compute nodes with lightly loaded traffic will be adaptively assigned more chunk access requests from remote VMs and vice versa, which can effectively eliminate the above problem and thus improves the I/O performance of VMs. We also implement a prototype based on our ACStor design, and evaluate it by various benchmarks on a real cluster with 32 nodes and a simulated platform with 256 nodes. Experiments show that under different network traffic patterns of data centers, our solution achieves up to 2-8 performance gain on VM booting time and VM’s I/O throughput, in comparison with the other state-of-the-art approaches.« less

Safety evaluation of the SCATS control system, final report.

DOT National Transportation Integrated Search

2010-09-01

Since 1992, traffic signals in Oakland County and a portion of Macomb and Wayne Counties of Michigan have been : converted to the Sydney Coordinated Adaptive Traffic System (SCATS). County traffic engineers have been : adjusting various SCATS paramet...

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.

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...

Test and evaluation of vehicle platooning proof-of-concept based on cooperative adaptive cruise control

DOT National Transportation Integrated Search

2017-04-01

This report presents a high-level test and evaluation framework for cooperative driving automation systems that have the potential to significantly improve mobility and enhance traffic flow stability with better safety. It focuses on the test and eva...

Extending the Capabilities of Internet-Based Research: Lessons from the Field.

ERIC Educational Resources Information Center

Tingling, Peter; Parent, Michael; Wade, Michael

2003-01-01

Summarizes the existing practices of Internet research and suggests extensions to them (e.g., consideration of new capabilities, such as adaptive questions and higher levels of flexibility and control) based on a large-scale, national Web survey. Lessons learned include the use of a modular design, management of Web traffic, and the higher level…

Profile negotiation - A concept for integrating airborne and ground-based automation for managing arrival traffic

NASA Technical Reports Server (NTRS)

Green, Steven M.; Den Braven, Wim; Williams, David H.

1991-01-01

The profile negotiation process (PNP) concept as applied to the management of arrival traffic within the extended terminal area is presented, focusing on functional issues from the ground-based perspective. The PNP is an interactive process between an aircraft and air traffic control (ATC) which combines airborne and ground-based automation capabilities to determine conflict-free trajectories that are as close to an aircraft's preference as possible. Preliminary results from a real-time simulation study show that the controller teams are able to consistently and effectively negotiate conflict-free vertical profiles with 4D-equipped aircraft. The ability of the airborne 4D flight management system to adapt to ATC specified 4D trajectory constraints is found to be a requirement for successful execution of the PNP. It is recommended that the conventional method of cost index iteration for obtaining the minimum fuel 4D trajectory be supplemented by a method which constrains the profile speeds to those desired by ATC.

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.

Adapting ISA system warnings to enhance user acceptance.

PubMed

Jiménez, Felipe; Liang, Yingzhen; Aparicio, Francisco

2012-09-01

Inappropriate speed is a major cause of traffic accidents. Different measures have been considered to control traffic speed, and intelligent speed adaptation (ISA) systems are one of the alternatives. These systems know the speed limits and try to improve compliance with them. This paper deals with an informative ISA system that provides the driver with an advance warning before reaching a road section with singular characteristics that require a lower safe speed than the current speed. In spite of the extensive tests performed using ISA systems, few works show how warnings can be adapted to the driver. This paper describes a method to adapt warning parameters (safe speed on curves, zone of influence of a singular stretch, deceleration process and reaction time) to normal driving behavior. The method is based on a set of tests with and without the ISA system. This adjustment, as well as the analysis of driver acceptance before and after the adaptation and changes in driver behavior (changes in speed and path) resulting from the tested ISA regarding a driver's normal driving style, is shown in this paper. The main conclusion is that acceptance by drivers increased significantly after redefining the warning parameters, but the effect of speed homogenization was not reduced. Copyright © 2010 Elsevier Ltd. All rights reserved.

Simulation-based decision-making tool for adaptive traffic signal control on Tarrytown Road in the City of White Plains.

DOT National Transportation Integrated Search

2013-01-01

Transportation corridors are vital for our region and even the nations economy and quality of life. A corridor is usually a complicated system that may span multi-jurisdictions, contains multiple modes, include both freeways and local arterials, a...

Continuum modeling of cooperative traffic flow dynamics

NASA Astrophysics Data System (ADS)

Ngoduy, D.; Hoogendoorn, S. P.; Liu, R.

2009-07-01

This paper presents a continuum approach to model the dynamics of cooperative traffic flow. The cooperation is defined in our model in a way that the equipped vehicle can issue and receive a warning massage when there is downstream congestion. Upon receiving the warning massage, the (up-stream) equipped vehicle will adapt the current desired speed to the speed at the congested area in order to avoid sharp deceleration when approaching the congestion. To model the dynamics of such cooperative systems, a multi-class gas-kinetic theory is extended to capture the adaptation of the desired speed of the equipped vehicle to the speed at the downstream congested traffic. Numerical simulations are carried out to show the influence of the penetration rate of the equipped vehicles on traffic flow stability and capacity in a freeway.

Emotional reactivity: Beware its involvement in traffic accidents.

PubMed

M'bailara, Katia; Atzeni, Thierry; Contrand, Benjamin; Derguy, Cyrielle; Bouvard, Manuel-Pierre; Lagarde, Emmanuel; Galéra, Cédric

2018-04-01

Reducing risk attributable to traffic accidents is a public health challenge. Research into risk factors in the area is now moving towards identification of the psychological factors involved, particularly emotional states. The aim of this study was to evaluate the link between emotional reactivity and responsibility in road traffic accidents. We hypothesized that the more one's emotional reactivity is disturbed, the greater the likelihood of being responsible for a traffic accident. This case-control study was based on a sample of 955 drivers injured in a motor vehicle crash. Responsibility levels were determined with a standardized method adapted from the quantitative Robertson and Drummer crash responsibility instrument. Emotional reactivity was assessed with the MATHYS. Hierarchical cluster analysis discriminated four distinctive driver's emotional reactivity profiles: basic emotional reactivity (54%), mild emotional hyper-reactivity (29%), emotional hyper-reactivity (11%) and emotional hypo-reactivity (6%). Drivers who demonstrated emotional hypo-reactivity had a 2.3-fold greater risk of being responsible for a traffic accident than those with basic emotional reactivity. Drivers' responsibility in traffic accidents depends on their emotional status. The latter can change the ability of drivers, modifying their behavior and thus increasing their propensity to exhibit risk behavior and to cause traffic accidents. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of the neighborhood environment walkability scale in Nigeria.

PubMed

Oyeyemi, Adewale L; Sallis, James F; Deforche, Benedicte; Oyeyemi, Adetoyeje Y; De Bourdeaudhuij, Ilse; Van Dyck, Delfien

2013-03-21

The development of reliable and culturally sensitive measures of attributes of the built and social environment is necessary for accurate analysis of environmental correlates of physical activity in low-income countries, that can inform international evidence-based policies and interventions in the worldwide prevention of physical inactivity epidemics. This study systematically adapted the Neighborhood Environment Walkability Scale (NEWS) for Nigeria and evaluated aspects of reliability and validity of the adapted version among Nigerian adults. The adaptation of the NEWS was conducted by African and international experts, and final items were selected for NEWS-Nigeria after a cross-validation of the confirmatory factor analysis structure of the original NEWS. Participants (N = 386; female = 47.2%) from two cities in Nigeria completed the adapted NEWS surveys regarding perceived residential density, land use mix - diversity, land use mix - access, street connectivity, infrastructure and safety for walking and cycling, aesthetics, traffic safety, and safety from crime. Self-reported activity for leisure, walking for different purposes, and overall physical activity were assessed with the validated International Physical Activity Questionnaire (long version). The adapted NEWS subscales had moderate to high test-retest reliability (ICC range 0.59 -0.91). Construct validity was good, with residents of high-walkable neighborhoods reporting significantly higher residential density, more land use mix diversity, higher street connectivity, more traffic safety and more safety from crime, but lower infrastructure and safety for walking/cycling and aesthetics than residents of low-walkable neighborhoods. Concurrent validity correlations were low to moderate (r = 0.10 -0.31) with residential density, land use mix diversity, and traffic safety significantly associated with most physical activity outcomes. The NEWS-Nigeria demonstrated acceptable measurement properties among Nigerian adults and may be useful for evaluation of the built environment in Nigeria. Further adaptation and evaluation in other African countries is needed to create a version that could be used throughout the African region.

An improved car-following model with two preceding cars' average speed

NASA Astrophysics Data System (ADS)

Yu, Shao-Wei; Shi, Zhong-Ke

2015-01-01

To better describe cooperative car-following behaviors under intelligent transportation circumstances and increase roadway traffic mobility, the data of three successive following cars at a signalized intersection of Jinan in China were obtained and employed to explore the linkage between two preceding cars' average speed and car-following behaviors. The results indicate that two preceding cars' average velocity has significant effects on the following car's motion. Then an improved car-following model considering two preceding cars' average velocity was proposed and calibrated based on full velocity difference model and some numerical simulations were carried out to study how two preceding cars' average speed affected the starting process and the traffic flow evolution process with an initial small disturbance, the results indicate that the improved car-following model can qualitatively describe the impacts of two preceding cars' average velocity on traffic flow and that taking two preceding cars' average velocity into account in designing the control strategy for the cooperative adaptive cruise control system can improve the stability of traffic flow, suppress the appearance of traffic jams and increase the capacity of signalized intersections.

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.

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.

Salient Feature Selection Using Feed-Forward Neural Networks and Signal-to-Noise Ratios with a Focus Toward Network Threat Detection and Classification

DTIC Science & Technology

2014-03-27

0.8.0. The virtual machine’s network adapter was set to internal network only to keep any outside traffic from interfering. A MySQL -based query...primary output of Fullstats is the ARFF file format, intended for use with the WEKA Java -based data mining software developed at the University of Waikato

A graph based algorithm for adaptable dynamic airspace configuration for NextGen

NASA Astrophysics Data System (ADS)

Savai, Mehernaz P.

The National Airspace System (NAS) is a complicated large-scale aviation network, consisting of many static sectors wherein each sector is controlled by one or more controllers. The main purpose of the NAS is to enable safe and prompt air travel in the U.S. However, such static configuration of sectors will not be able to handle the continued growth of air travel which is projected to be more than double the current traffic by 2025. Under the initiative of the Next Generation of Air Transportation system (NextGen), the main objective of Adaptable Dynamic Airspace Configuration (ADAC) is that the sectors should change to the changing traffic so as to reduce the controller workload variance with time while increasing the throughput. Change in the resectorization should be such that there is a minimal increase in exchange of air traffic among controllers. The benefit of a new design (improvement in workload balance, etc.) should sufficiently exceed the transition cost, in order to deserve a change. This leads to the analysis of the concept of transition workload which is the cost associated with a transition from one sectorization to another. Given two airspace configurations, a transition workload metric which considers the air traffic as well as the geometry of the airspace is proposed. A solution to reduce this transition workload is also discussed. The algorithm is specifically designed to be implemented for the Dynamic Airspace Configuration (DAC) Algorithm. A graph model which accurately represents the air route structure and air traffic in the NAS is used to formulate the airspace configuration problem. In addition, a multilevel graph partitioning algorithm is developed for Dynamic Airspace Configuration which partitions the graph model of airspace with given user defined constraints and hence provides the user more flexibility and control over various partitions. In terms of air traffic management, vertices represent airports and waypoints. Some of the major (busy) airports need to be given more importance and hence treated separately. Thus the algorithm takes into account the air route structure while finding a balance between sector workloads. The performance of the proposed algorithms and performance metrics is validated with the Enhanced Traffic Management System (ETMS) air traffic data.

IDMA-Based MAC Protocol for Satellite Networks with Consideration on Channel Quality

PubMed Central

2014-01-01

In order to overcome the shortcomings of existing medium access control (MAC) protocols based on TDMA or CDMA in satellite networks, interleave division multiple access (IDMA) technique is introduced into satellite communication networks. Therefore, a novel wide-band IDMA MAC protocol based on channel quality is proposed in this paper, consisting of a dynamic power allocation algorithm, a rate adaptation algorithm, and a call admission control (CAC) scheme. Firstly, the power allocation algorithm combining the technique of IDMA SINR-evolution and channel quality prediction is developed to guarantee high power efficiency even in terrible channel conditions. Secondly, the effective rate adaptation algorithm, based on accurate channel information per timeslot and by the means of rate degradation, can be realized. What is more, based on channel quality prediction, the CAC scheme, combining the new power allocation algorithm, rate scheduling, and buffering strategies together, is proposed for the emerging IDMA systems, which can support a variety of traffic types, and offering quality of service (QoS) requirements corresponding to different priority levels. Simulation results show that the new wide-band IDMA MAC protocol can make accurate estimation of available resource considering the effect of multiuser detection (MUD) and QoS requirements of multimedia traffic, leading to low outage probability as well as high overall system throughput. PMID:25126592

Neural-tree call admission controller for ATM networks

NASA Astrophysics Data System (ADS)

Rughooputh, Harry C. S.

1999-03-01

Asynchronous Transfer Mode (ATM) has been recommended by ITU-T as the transport method for broadband integrated services digital networks. In high-speed ATM networks different types of multimedia traffic streams with widely varying traffic characteristics and Quality of Service (QoS) are asynchronously multiplexed on transmission links and switched without window flow control as found in X.25. In such an environment, a traffic control scheme is required to manage the required QoS of each class individually. To meet the QoS requirements, Bandwidth Allocation and Call Admission Control (CAC) in ATM networks must be able to adapt gracefully to the dynamic behavior of traffic and the time-varying nature of the network condition. In this paper, a Neural Network approach for CAC is proposed. The call admission problem is addressed by designing controllers based on Neural Tree Networks. Simulations reveal that the proposed scheme is not only simple but it also offers faster response than conventional neural/neuro-fuzzy controllers.

Vehicle Detection with Occlusion Handling, Tracking, and OC-SVM Classification: A High Performance Vision-Based System

PubMed Central

Velazquez-Pupo, Roxana; Sierra-Romero, Alberto; Torres-Roman, Deni; Shkvarko, Yuriy V.; Romero-Delgado, Misael

2018-01-01

This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the background using the adaptive Gaussian Mixture Model (GMM). After that, several geometric features are extracted, such as vehicle area, height, width, centroid, and bounding box. As occlusion is present, an algorithm was implemented to reduce it. The tracking is performed with adaptive Kalman filter. Finally, the selected geometric features: estimated area, height, and width are used by different classifiers in order to sort vehicles into three classes: small, midsize, and large. Extensive experimental results in eight real traffic videos with more than 4000 ground truth vehicles have shown that the improved system can run in real time under an occlusion index of 0.312 and classify vehicles with a global detection rate or recall, precision, and F-measure of up to 98.190%, and an F-measure of up to 99.051% for midsize vehicles. PMID:29382078

Final report on the analyses of traffic accidents : Fast-Trac--phase 3, deliverable. Semi-annual reports on total accidents : trends, types and analysis of before and after studies

DOT National Transportation Integrated Search

1996-12-01

This report contains the results of an analysis of : traffic accidents in the City of Troy, Michigan, where : the Sydney Coordinated Adaptive Traffic System : (SCATS) was deployed as part of a federal demonstration : program. The analyses includes a ...

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.

All-optical OXC transition strategy from WDM optical network to elastic optical network.

PubMed

Chen, Xin; Li, Juhao; Guo, Bingli; Zhu, Paikun; Tang, Ruizhi; Chen, Zhangyuan; He, Yongqi

2016-02-22

Elastic optical network (EON) has been proposed recently as a spectrum-efficient optical layer to adapt to rapidly-increasing traffic demands instead of current deployed wavelength-division-multiplexing (WDM) optical network. In contrast with conventional WDM optical cross-connect (OXCs) based on wavelength selective switches (WSSs), the EON OXCs are based on spectrum selective switches (SSSs) which are much more expensive than WSSs, especially for large-scale switching architectures. So the transition cost from WDM OXCs to EON OXCs is a major obstacle to realizing EON. In this paper, we propose and experimentally demonstrate a transition OXC (TOXC) structure based on 2-stage cascading switching architectures, which make full use of available WSSs in current deployed WDM OXCs to reduce number and port count of required SSSs. Moreover, we propose a contention-aware spectrum allocation (CASA) scheme for EON built with the proposed TOXCs. We show by simulation that the TOXCs reduce the network capital expenditure transiting from WDM optical network to EON about 50%, with a minor traffic blocking performance degradation and about 10% accommodated traffic number detriment compared with all-SSS EON OXC architectures.

Citizen Science for Traffic Planning: A Practical Example

NASA Astrophysics Data System (ADS)

Rieke, Matthes; Stasch, Christoph; Autermann, Christian; de Wall, Arne; Remke, Albert; Wulffius, Herwig; Jirka, Simon

2017-04-01

Measures affecting traffic flows in urban areas, e.g. changing the configuration of traffic lights, are often causing emotional debates by citizens who are affected by these measures. Up to now, citizens are usually not involved in traffic planning and the evaluation of the decisions that were taken. The enviroCar project provides an open platform for collecting and analyzing car sensor data with GPS position data. On the hardware side, enviroCar relies on using Android smartphones and OBD-II Bluetooth adapters. A Web server component collects and aggregates the readings from the cars, anonymizes them and publishes the data as open data which scientists, public administrations or other third parties can utilize for further analysis. In this work, we provide a general overview on the enviroCar project and present a project in a mid-size city in Germany. The city's administration utilized the enviroCar platform with the help of a traffic system consultancy for including citizens in the evaluation process of different traffic light configurations along major traffic axes. Therefore, a public campaign was started including local workshops to engage the citizens. More than 150 citizens were actively collecting more about 9.500 tracks including about 2.5 million measurements. Dedicated evaluation results for the different traffic axes were computed based on the collected data set. Because the data is publicly available as open data, others may prove and reproduce the evaluation results contributing to an objective discussion of traffic planning measures. In summary, the project illustrates how Citizen Science methods and technologies improve traffic planning and related discussions.

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

Scheduling logic for Miles-In-Trail traffic management

NASA Technical Reports Server (NTRS)

Synnestvedt, Robert G.; Swenson, Harry; Erzberger, Heinz

1995-01-01

This paper presents an algorithm which can be used for scheduling arrival air traffic in an Air Route Traffic Control Center (ARTCC or Center) entering a Terminal Radar Approach Control (TRACON) Facility . The algorithm aids a Traffic Management Coordinator (TMC) in deciding how to restrict traffic while the traffic expected to arrive in the TRACON exceeds the TRACON capacity. The restrictions employed fall under the category of Miles-in-Trail, one of two principal traffic separation techniques used in scheduling arrival traffic . The algorithm calculates aircraft separations for each stream of aircraft destined to the TRACON. The calculations depend upon TRACON characteristics, TMC preferences, and other parameters adapted to the specific needs of scheduling traffic in a Center. Some preliminary results of traffic simulations scheduled by this algorithm are presented, and conclusions are drawn as to the effectiveness of using this algorithm in different traffic scenarios.

Simple cellular automaton model for traffic breakdown, highway capacity, and synchronized flow.

PubMed

Kerner, Boris S; Klenov, Sergey L; Schreckenberg, Michael

2011-10-01

We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules "acceleration," "deceleration," "randomization," and "motion" of the Nagel-Schreckenberg CA model as well as "overacceleration through lane changing to the faster lane," "comparison of vehicle gap with the synchronization gap," and "speed adaptation within the synchronization gap" of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.

Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

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

Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune

2011-07-12

This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet.more » The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks using feasibly-implementable rate adaptivity. • A buffer-management algorithm that is designed to reduce the size of router buffers, and hence energy consumed. • A packet-scheduling algorithm designed to minimize packet-processing energy requirements. Additional research is recommended in at least two areas: further exploration of rate-adaptation in network switching equipment, including incorporation of rate-adaptation in actual hardware, allowing experimentation in operational networks; and development of control protocols that allow parts of networks to be shut down while minimizing disruption to traffic flow in the network. The research is an integral part of a large effort within Bell Laboratories, Alcatel-Lucent, aimed at dramatic improvements in the energy efficiency of telecommunication networks. This Study did not explicitly consider any commercialization opportunities.« less

Improving the energy efficiency of telecommunication networks

NASA Astrophysics Data System (ADS)

Lange, Christoph; Gladisch, Andreas

2011-05-01

The energy consumption of telecommunication networks has gained increasing interest throughout the recent past: Besides its environmental implications it has been identified to be a major contributor to operational expenditures of network operators. Targeting at sustainable telecommunication networks, thus, it is important to find appropriate strategies for improving their energy efficiency before the background of rapidly increasing traffic volumes. Besides the obvious benefits of increasing energy efficiency of network elements by leveraging technology progress, load-adaptive network operation is a very promising option, i.e. using network resources only to an extent and for the time they are actually needed. In contrast, current network operation takes almost no advantage of the strongly time-variant behaviour of the network traffic load. Mechanisms for energy-aware load-adaptive network operation can be subdivided in techniques based on local autonomous or per-link decisions and in techniques relying on coordinated decisions incorporating information from several links. For the transformation from current network structures and operation paradigms towards energy-efficient and sustainable networks it will be essential to use energy-optimized network elements as well as including the overall energy consumption in network design and planning phases together with the energy-aware load-adaptive operation. In load-adaptive operation it will be important to establish the optimum balance between local and overarching power management concepts in telecommunication networks.

A real-time traffic control method for the intersection with pre-signals under the phase swap sorting strategy

PubMed Central

Bie, Yiming; Wang, Yinhai

2017-01-01

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios. PMID:28531198

A real-time traffic control method for the intersection with pre-signals under the phase swap sorting strategy.

PubMed

Bie, Yiming; Liu, Zhiyuan; Wang, Yinhai

2017-01-01

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios.

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah

PubMed Central

Tian, Le; Latré, Steven

2017-01-01

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

PubMed

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.

Towards Internet QoS provisioning based on generic distributed QoS adaptive routing engine.

PubMed

Haikal, Amira Y; Badawy, M; Ali, Hesham A

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature.

Towards Internet QoS Provisioning Based on Generic Distributed QoS Adaptive Routing Engine

PubMed Central

Haikal, Amira Y.; Badawy, M.; Ali, Hesham A.

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature. PMID:25309955

An RFID-based intelligent vehicle speed controller using active traffic signals.

PubMed

Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C; de Pedro, Teresa

2010-01-01

These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver's attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results.

An RFID-Based Intelligent Vehicle Speed Controller Using Active Traffic Signals

PubMed Central

Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C.; de Pedro, Teresa

2010-01-01

These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver’s attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results. PMID:22219692

Multigranular integrated services optical network

NASA Astrophysics Data System (ADS)

Yu, Oliver; Yin, Leping; Xu, Huan; Liao, Ming

2006-12-01

Based on all-optical switches without requiring fiber delay lines and optical-electrical-optical interfaces, the multigranular optical switching (MGOS) network integrates three transport services via unified core control to efficiently support bursty and stream traffic of subwavelength to multiwavelength bandwidth. Adaptive robust optical burst switching (AR-OBS) aggregates subwavelength burst traffic into asynchronous light-rate bursts, transported via slotted-time light paths established by fast two-way reservation with robust blocking recovery control. Multiwavelength optical switching (MW-OS) decomposes multiwavelength stream traffic into a group of timing-related light-rate streams, transported via a light-path group to meet end-to-end delay-variation requirements. Optical circuit switching (OCS) simply converts wavelength stream traffic from an electrical-rate into a light-rate stream. The MGOS network employs decoupled routing, wavelength, and time-slot assignment (RWTA) and novel group routing and wavelength assignment (GRWA) to select slotted-time light paths and light-path groups, respectively. The selected resources are reserved by the unified multigranular robust fast optical reservation protocol (MG-RFORP). Simulation results show that elastic traffic is efficiently supported via AR-OBS in terms of loss rate and wavelength utilization, while connection-oriented wavelength traffic is efficiently supported via wavelength-routed OCS in terms of connection blocking and wavelength utilization. The GRWA-tuning result for MW-OS is also shown.

Traffic off-balancing algorithm for energy efficient networks

NASA Astrophysics Data System (ADS)

Kim, Junhyuk; Lee, Chankyun; Rhee, June-Koo Kevin

2011-12-01

Physical layer of high-end network system uses multiple interface arrays. Under the load-balancing perspective, light load can be distributed to multiple interfaces. However, it can cause energy inefficiency in terms of the number of poor utilization interfaces. To tackle this energy inefficiency, traffic off-balancing algorithm for traffic adaptive interface sleep/awake is investigated. As a reference model, 40G/100G Ethernet is investigated. We report that suggested algorithm can achieve energy efficiency while satisfying traffic transmission requirement.

Improving traffic flow at a 2-to-1 lane reduction with wirelessly connected, adaptive cruise control vehicles

NASA Astrophysics Data System (ADS)

Davis, L. C.

2016-06-01

Wirelessly connected vehicles that exchange information about traffic conditions can reduce delays caused by congestion. At a 2-to-1 lane reduction, the improvement in flow past a bottleneck due to traffic with a random mixture of 40% connected vehicles is found to be 52%. Control is based on connected-vehicle-reported velocities near the bottleneck. In response to indications of congestion the connected vehicles, which are also adaptive cruise control vehicles, reduce their speed in slowdown regions. Early lane changes of manually driven vehicles from the terminated lane to the continuous lane are induced by the slowing connected vehicles. Self-organized congestion at the bottleneck is thus delayed or eliminated, depending upon the incoming flow magnitude. For the large majority of vehicles, travel times past the bottleneck are substantially reduced. Control is responsible for delaying the onset of congestion as the incoming flow increases. Adaptive cruise control increases the flow out of the congested state at the bottleneck. The nature of the congested state, when it occurs, appears to be similar under a variety of conditions. Typically 80-100 vehicles are approximately equally distributed between the lanes in the 500 m region prior to the end of the terminated lane. Without the adaptive cruise control capability, connected vehicles can delay the onset of congestion but do not increase the asymptotic flow past the bottleneck. Calculations are done using the Kerner-Klenov three-phase theory, stochastic discrete-time model for manual vehicles. The dynamics of the connected vehicles is given by a conventional adaptive cruise control algorithm plus commanded deceleration. Because time in the model for manual vehicles is discrete (one-second intervals), it is assumed that the acceleration of any vehicle immediately in front of a connected vehicle is constant during the time interval, thereby preserving the computational simplicity and speed of a discrete-time model.

RHODES-ITMS-MILOS : ramp metering system test

DOT National Transportation Integrated Search

2002-04-01

The RHODES-Integrated Traffic Management System Program addresses the design and development of a real-time traffic adaptive control system for an integrated system of freeways and arterial roads. The goals of this project were to test coordinated, a...

Estimate benefits of crowdsourced data from social media.

DOT National Transportation Integrated Search

2014-12-01

Traffic Management Centers (TMCs) acquire, process, and integrate data in a variety of ways to support real-time operations. Crowdsourcing has been identified as one of the top trends and technologies that traffic management agencies can adapt and ta...

A self-adaptive toll rate algorithm for high occupancy toll (HOT) lane operations.

DOT National Transportation Integrated Search

2009-12-01

Dramatically increasing travel demands and insufficient traffic facility supplies have resulted in severe : traffic congestion. High Occupancy Toll (HOT) lane operations have been proposed as one of the most : applicable and cost-effective countermea...

Local evaluation report for ATLAS-ITS phase II : integration of real-time traffic information for adaptive signal control, traveler information and management of transit and emergency services

DOT National Transportation Integrated Search

2005-12-01

Major roads and arterials in the City of Tucson and Pima County are already significantly detectorized with inductive loop detectors and, at places, with video-based detectors. These detectors are used for semi-actuated signal control and for limited...

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

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

PubMed

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

Statewide Intelligent Transportation Systems As-Is Agency Reports For Minnesota, Volume 6, City Of St. Paul

DOT National Transportation Integrated Search

1996-08-01

KEYWORDS: : TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS : THIS DOCUMENT PRESENTS THE METHODS, ASSUMPTIONS AND PROCEDURES USED TO COLLECT THE BASELINE INFORMATION. THE DOCUMENTATION OF SYSTEMS ...

Active transportation to support diabetes prevention: Expanding school health promotion programming in an Indigenous community.

PubMed

Macridis, Soultana; Garcia Bengoechea, Enrique; McComber, Alex M; Jacobs, Judi; Macaulay, Ann C

2016-06-01

School-based physical activity (PA) interventions, including school active transportation (AT), provide opportunities to increase daily PA levels, improves fitness, and reduces risk of diseases, such as type 2 diabetes. Based on a community-identified need, the Kahnawake Schools Diabetes Prevention Project, within an Indigenous community, undertook school travel planning to contribute to PA programming for two elementary schools. Using community-based participatory research, the Active & Safe Routes to School's School Travel Planning (STP) process was undertaken in two schools with an STP-Committee comprised of community stakeholders and researchers. STP activities were adapted for local context including: school profile form, family survey, in-class travel survey, pedestrian-traffic observations, walkability checklist, and student mapping. STP data were jointly collected, analyzed and interpreted by researchers and community. Traffic-pedestrian observations, walkability and parent surveys identified key pedestrian-traffic locations, helped develop safe/direct routes, and traffic calming strategies. In-class travel and mapping surveys identified a need and student desire to increase school AT. The STP-Committee translated findings into STP-action plans for two schools, which were implemented in 2014-2015 school year. Combining CBPR with STP merges community and researcher expertise. This project offered evidence-informed practice for active living promotions. Experience and findings could benefit Indigenous and non-Indigenous communities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simple cellular automaton model for traffic breakdown, highway capacity, and synchronized flow

NASA Astrophysics Data System (ADS)

Kerner, Boris S.; Klenov, Sergey L.; Schreckenberg, Michael

2011-10-01

We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules “acceleration,” “deceleration,” “randomization,” and “motion” of the Nagel-Schreckenberg CA model as well as “overacceleration through lane changing to the faster lane,” “comparison of vehicle gap with the synchronization gap,” and “speed adaptation within the synchronization gap” of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.

Analytical studies on the instabilities of heterogeneous intelligent traffic flow

NASA Astrophysics Data System (ADS)

Ngoduy, D.

2013-10-01

It has been widely reported in literature that a small perturbation in traffic flow such as a sudden deceleration of a vehicle could lead to the formation of traffic jams without a clear bottleneck. These traffic jams are usually related to instabilities in traffic flow. The applications of intelligent traffic systems are a potential solution to reduce the amplitude or to eliminate the formation of such traffic instabilities. A lot of research has been conducted to theoretically study the effect of intelligent vehicles, for example adaptive cruise control vehicles, using either computer simulation or analytical method. However, most current analytical research has only applied to single class traffic flow. To this end, the main topic of this paper is to perform a linear stability analysis to find the stability threshold of heterogeneous traffic flow using microscopic models, particularly the effect of intelligent vehicles on heterogeneous (or multi-class) traffic flow instabilities. The analytical results will show how intelligent vehicle percentages affect the stability of multi-class traffic flow.

The effects of velocity difference changes with memory on the dynamics characteristics and fuel economy of traffic flow

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Zhao, Xiangmo; Xu, Zhigang; Zhang, Licheng

2016-11-01

To evaluate the effects of velocity difference changes with memory in the intelligent transportation environment on the dynamics and fuel consumptions of traffic flow, we first investigate the linkage between velocity difference changes with memory and car-following behaviors with the measured data in cities, and then propose an improved cooperative car-following model considering multiple velocity difference changes with memory in the cooperative adaptive cruise control strategy, finally carry out several numerical simulations under the periodic boundary condition and at signalized intersections to explore how velocity difference changes with memory affect car's velocity, velocity fluctuation, acceleration and fuel consumptions in the intelligent transportation environment. The results show that velocity difference changes with memory have obvious effects on car-following behaviors, that the improved cooperative car-following model can describe the phase transition of traffic flow and estimate the evolution of traffic congestion, that the stability and fuel economy of traffic flow simulated by the improved car-following model with velocity difference changes with memory is obviously superior to those without velocity difference changes, and that taking velocity difference changes with memory into account in designing the advanced adaptive cruise control strategy can significantly improve the stability and fuel economy of traffic flow.

Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections.

PubMed

Mignan, A; Broccardo, M; Wiemer, S; Giardini, D

2017-10-19

The rise in the frequency of anthropogenic earthquakes due to deep fluid injections is posing serious economic, societal, and legal challenges to many geo-energy and waste-disposal projects. Existing tools to assess such problems are still inherently heuristic and mostly based on expert elicitation (so-called clinical judgment). We propose, as a complementary approach, an adaptive traffic light system (ATLS) that is function of a statistical model of induced seismicity. It offers an actuarial judgement of the risk, which is based on a mapping between earthquake magnitude and risk. Using data from six underground reservoir stimulation experiments, mostly from Enhanced Geothermal Systems, we illustrate how such a data-driven adaptive forecasting system could guarantee a risk-based safety target. The proposed model, which includes a linear relationship between seismicity rate and flow rate, as well as a normal diffusion process for post-injection, is first confirmed to be representative of the data. Being integrable, the model yields a closed-form ATLS solution that is both transparent and robust. Although simulations verify that the safety target is consistently ensured when the ATLS is applied, the model from which simulations are generated is validated on a limited dataset, hence still requiring further tests in additional fluid injection environments.

Effects of inter-packet spacing on the delivery of multimedia content

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

Kapadia, A. C.; Feng, A. C.; Feng, W. C.

2001-01-01

Streaming multimedia content with UDP has become increasingly popular over distributed systems such as the Internet. However, because UDP does not possess any congestion-control mechanism and most best-effort trafic is served by the congestion-controlled TCP, UDP flows steal bandwidth from TCP to the point that TCP flows can starve for network resources. Furthermore, such applications may cause the Internet infrastructure to eventually suffer from congestion collapse because UDP trafic does not self-regulate itself. To address this problem, next-generation Internet routers will implement active queue-management schemes to punish malicious traffic, e.g., non-adaptive UDP flows, and to the improve the performance ofmore » congestion-controlled traffic, e.g., TCP flows. The arrival of such routers will cripple the performance of today's UDP-based multimedia applications. So, in this paper, we introduce the notion of inter-packet spacing with control feedback to enable these UDP-based applications to perform well in the next-generation Internet while being adaptive and self-regulating. When compared with traditional UDP-based multimedia streaming, we illustrate that our counterintuitive, interpacket-spacing scheme with control feedback can reduce packet loss by 90% without adversely affecting delivered throughput. Keywords: network protocol, multimedia, packet spacing, rate-adjusting congestion control.« less

Evaluation of the Virginia Department of Transportation adaptive signal control technology pilot project.

DOT National Transportation Integrated Search

2015-06-01

Currently, most traffic signals operated by the Virginia Department of Transportation (VDOT) use actuated plans that vary : by time of day (TOD) and day of the week. These timing plans are typically developed off-line using traffic count information ...

Multi Car Elevator Control by using Learning Automaton

NASA Astrophysics Data System (ADS)

Shiraishi, Kazuaki; Hamagami, Tomoki; Hirata, Hironori

We study an adaptive control technique for multi car elevators (MCEs) by adopting learning automatons (LAs.) The MCE is a high performance and a near-future elevator system with multi shafts and multi cars. A strong point of the system is that realizing a large carrying capacity in small shaft area. However, since the operation is too complicated, realizing an efficient MCE control is difficult for top-down approaches. For example, “bunching up together" is one of the typical phenomenon in a simple traffic environment like the MCE. Furthermore, an adapting to varying environment in configuration requirement is a serious issue in a real elevator service. In order to resolve these issues, having an autonomous behavior is required to the control system of each car in MCE system, so that the learning automaton, as the solutions for this requirement, is supposed to be appropriate for the simple traffic control. First, we assign a stochastic automaton (SA) to each car control system. Then, each SA varies its stochastic behavior distributions for adapting to environment in which its policy is evaluated with each passenger waiting times. That is LA which learns the environment autonomously. Using the LA based control technique, the MCE operation efficiency is evaluated through simulation experiments. Results show the technique enables reducing waiting times efficiently, and we confirm the system can adapt to the dynamic environment.

Stability and Responsiveness in a Self-Organized Living Architecture

PubMed Central

Garnier, Simon; Murphy, Tucker; Lutz, Matthew; Hurme, Edward; Leblanc, Simon; Couzin, Iain D.

2013-01-01

Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies. PMID:23555219

TRACC_PB SOSS Integrated Traffic Simulation for CLT Ramp Operation

NASA Technical Reports Server (NTRS)

Okuniek, Nikolai; Zhu, Zhifan

2017-01-01

This presentation provides the current task under the NASA-DLR research collaboration for airport surface. It presents the effort done to adapt TRACC and SOSS software components to simulate airport (CLT) ramp area traffic management using TRACC's conflict free taxi trajectory optimization and SOSS's fast time simulation platform.

Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

PubMed

Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

2016-01-01

This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

Adaptive Signal Timing Comparison Between the InSync and QuicTrac Adaptive Signal Systems Installed in Colorado

DOT National Transportation Integrated Search

2012-07-01

The FHWAs Every Day Counts (EDC) initiative identifies adaptive signal control as a tool for local agencies to deploy : innovation. In an effort to achieve the goals of the EDC initiative, the traffic sections of the Colorado Department of : Trans...

A Cooperative Human-Adaptive Traffic Simulation (CHATS)

NASA Technical Reports Server (NTRS)

Phillips, Charles T.; Ballin, Mark G.

1999-01-01

NASA is considering the development of a Cooperative Human-Adaptive Traffic Simulation (CHATS), to examine and evaluate performance of the National Airspace System (NAS) as the aviation community moves toward free flight. CHATS will be specifically oriented toward simulating strategic decision-making by airspace users and by the service provider s traffic management personnel, within the context of different airspace and rules assumptions. It will use human teams to represent these interests and make decisions, and will rely on computer modeling and simulation to calculate the impacts of these decisions. The simulation objectives will be to examine: 1. evolution of airspace users and the service provider s strategies, through adaptation to new operational environments; 2. air carriers competitive and cooperative behavior; 3. expected benefits to airspace users and the service provider as compared to the current NAS; 4. operational limitations of free flight concepts due to congestion and safety concerns. This paper describes an operational concept for CHATS, and presents a high-level functional design which would utilize a combination of existing and new models and simulation capabilities.

Extended time-to-collision measures for road traffic safety assessment.

PubMed

Minderhoud, M M; Bovy, P H

2001-01-01

This article describes two new safety indicators based on the time-to-collision notion suitable for comparative road traffic safety analyses. Such safety indicators can be applied in the comparison of a do-nothing case with an adapted situation, e.g. the introduction of intelligent driver support systems. In contrast to the classical time-to-collision value, measured at a cross section, the improved safety indicators use vehicle trajectories collected over a specific time horizon for a certain roadway segment to calculate the overall safety indicator value. Vehicle-specific indicator values as well as safety-critical probabilities can easily be determined from the developed safety measures. Application of the derived safety indicators is demonstrated for the assessment of the potential safety impacts of driver support systems from which it appears that some Autonomous Intelligent Cruise Control (AICC) designs are more safety-critical than the reference case without these systems. It is suggested that the indicator threshold value to be applied in the safety assessment has to be adapted when advanced AICC-systems with safe characteristics are introduced.

Assessment of the contribution of traffic emissions to the mobile vehicle measured PM2.5 concentration by means of WRF-CMAQ simulations.

DOT National Transportation Integrated Search

2012-03-01

The Alaska adapted version of the Weather Research and Forecasting and the Community Modeling and Analysis Quality (WRF-CMAQ) modeling : systems was used to assess the contribution of traffic to the PM2.5-concentration in the Fairbanks nonattainment ...

Project no. B371 : acoustic emission and strain gage monitoring of WIDOT structure B-5-158, Tower Drive Tied Arch, Green Bay, Wisconsin

DOT National Transportation Integrated Search

1993-06-16

The City of South Lyon converted the traffic signals on the street network from fixed time control to the Sydney Coordinated Adaptive Traffic System (SCATS). The objectives of this research study were to analyze the differences in certain delay param...

Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity.

PubMed

Kesting, Arne; Treiber, Martin; Helbing, Dirk

2010-10-13

With an increasing number of vehicles equipped with adaptive cruise control (ACC), the impact of such vehicles on the collective dynamics of traffic flow becomes relevant. By means of simulation, we investigate the influence of variable percentages of ACC vehicles on traffic flow characteristics. For simulating the ACC vehicles, we propose a new car-following model that also serves as the basis of an ACC implementation in real cars. The model is based on the intelligent driver model (IDM) and inherits its intuitive behavioural parameters: desired velocity, acceleration, comfortable deceleration and desired minimum time headway. It eliminates, however, the sometimes unrealistic behaviour of the IDM in cut-in situations with ensuing small gaps that regularly are caused by lane changes of other vehicles in dense or congested traffic. We simulate the influence of different ACC strategies on the maximum capacity before breakdown and the (dynamic) bottleneck capacity after breakdown. With a suitable strategy, we find sensitivities of the order of 0.3, i.e. 1 per cent more ACC vehicles will lead to an increase in the capacities by about 0.3 per cent. This sensitivity multiplies when considering travel times at actual breakdowns.

Designing area optimized application-specific network-on-chip architectures while providing hard QoS guarantees.

PubMed

Khawaja, Sajid Gul; Mushtaq, Mian Hamza; Khan, Shoab A; Akram, M Usman; Jamal, Habib Ullah

2015-01-01

With the increase of transistors' density, popularity of System on Chip (SoC) has increased exponentially. As a communication module for SoC, Network on Chip (NoC) framework has been adapted as its backbone. In this paper, we propose a methodology for designing area-optimized application specific NoC while providing hard Quality of Service (QoS) guarantees for real time flows. The novelty of the proposed system lies in derivation of a Mixed Integer Linear Programming model which is then used to generate a resource optimal Network on Chip (NoC) topology and architecture while considering traffic and QoS requirements. We also present the micro-architectural design features used for enabling traffic and latency guarantees and discuss how the solution adapts for dynamic variations in the application traffic. The paper highlights the effectiveness of proposed method by generating resource efficient NoC solutions for both industrial and benchmark applications. The area-optimized results are generated in few seconds by proposed technique, without resorting to heuristics, even for an application with 48 traffic flows.

Designing Area Optimized Application-Specific Network-On-Chip Architectures while Providing Hard QoS Guarantees

PubMed Central

Khawaja, Sajid Gul; Mushtaq, Mian Hamza; Khan, Shoab A.; Akram, M. Usman; Jamal, Habib ullah

2015-01-01

With the increase of transistors' density, popularity of System on Chip (SoC) has increased exponentially. As a communication module for SoC, Network on Chip (NoC) framework has been adapted as its backbone. In this paper, we propose a methodology for designing area-optimized application specific NoC while providing hard Quality of Service (QoS) guarantees for real time flows. The novelty of the proposed system lies in derivation of a Mixed Integer Linear Programming model which is then used to generate a resource optimal Network on Chip (NoC) topology and architecture while considering traffic and QoS requirements. We also present the micro-architectural design features used for enabling traffic and latency guarantees and discuss how the solution adapts for dynamic variations in the application traffic. The paper highlights the effectiveness of proposed method by generating resource efficient NoC solutions for both industrial and benchmark applications. The area-optimized results are generated in few seconds by proposed technique, without resorting to heuristics, even for an application with 48 traffic flows. PMID:25898016

Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS) Networks with Ensuring the Fairness for Other Traffics.

PubMed

Al-Shargabi, Mohammed A; Shaikh, Asadullah; Ismail, Abdulsamad S

2016-01-01

Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS' QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50-60%, 30-40%, and 10-20% for high, normal, and low traffic loads respectively.

Google-Earth Based Visualizations for Environmental Flows and Pollutant Dispersion in Urban Areas

PubMed Central

Liu, Daoming; Kenjeres, Sasa

2017-01-01

In the present study, we address the development and application of an efficient tool for conversion of results obtained by an integrated computational fluid dynamics (CFD) and computational reaction dynamics (CRD) approach and their visualization in the Google Earth. We focus on results typical for environmental fluid mechanics studies at a city scale that include characteristic wind flow patterns and dispersion of reactive scalars. This is achieved by developing a code based on the Java language, which converts the typical four-dimensional structure (spatial and temporal dependency) of data results in the Keyhole Markup Language (KML) format. The visualization techniques most often used are revisited and implemented into the conversion tool. The potential of the tool is demonstrated in a case study of smog formation due to an intense traffic emission in Rotterdam (The Netherlands). It is shown that the Google Earth can provide a computationally efficient and user-friendly means of data representation. This feature can be very useful for visualization of pollution at street levels, which is of great importance for the city residents. Various meteorological and traffic emissions can be easily visualized and analyzed, providing a powerful, user-friendly tool for traffic regulations and urban climate adaptations. PMID:28257078

Optimize pollutant emissions through adaptive highway management.

DOT National Transportation Integrated Search

2011-09-01

In this project, we investigated the possibility to reduce green house emission : (mainly CO2) from urban highways by adaptive ramp meter control. QUADSTONE : PARAMICS software was used to build a microscopic traffic model for a 4-lane highway : sect...

A Distributed Trajectory-Oriented Approach to Managing Traffic Complexity

NASA Technical Reports Server (NTRS)

Idris, Husni; Wing, David J.; Vivona, Robert; Garcia-Chico, Jose-Luis

2007-01-01

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which ground-based service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. While its architecture becomes more distributed, the goal of the Air Traffic Management (ATM) system remains to achieve objectives such as maintaining safety and efficiency. It is, therefore, critical to design appropriate control elements to ensure that aircraft and groundbased actions result in achieving these objectives without unduly restricting user-preferred trajectories. This paper presents a trajectory-oriented approach containing two such elements. One is a trajectory flexibility preservation function, by which aircraft plan their trajectories to preserve flexibility to accommodate unforeseen events. And the other is a trajectory constraint minimization function by which ground-based agents, in collaboration with air-based agents, impose just-enough restrictions on trajectories to achieve ATM objectives, such as separation assurance and flow management. The underlying hypothesis is that preserving trajectory flexibility of each individual aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by minimizing constraints without jeopardizing the intended ATM objectives. The paper presents conceptually how the two functions operate in a distributed control architecture that includes self separation. The paper illustrates the concept through hypothetical scenarios involving conflict resolution and flow management. It presents a functional analysis of the interaction and information flow between the functions. It also presents an analytical framework for defining metrics and developing methods to preserve trajectory flexibility and minimize its constraints. In this framework flexibility is defined in terms of robustness and adaptability to disturbances and the impact of constraints is illustrated through analysis of a trajectory solution space with limited degrees of freedom and in simple constraint situations involving meeting multiple times of arrival and resolving a conflict.

Memory effects in microscopic traffic models and wide scattering in flow-density data

NASA Astrophysics Data System (ADS)

Treiber, Martin; Helbing, Dirk

2003-10-01

By means of microscopic simulations we show that noninstantaneous adaptation of the driving behavior to the traffic situation together with the conventional method to measure flow-density data provides a possible explanation for the observed inverse-λ shape and the wide scattering of flow-density data in “synchronized” congested traffic. We model a memory effect in the response of drivers to the traffic situation for a wide class of car-following models by introducing an additional dynamical variable (the “subjective level of service”) describing the adaptation of drivers to the surrounding traffic situation during the past few minutes and couple this internal state to parameters of the underlying model that are related to the driving style. For illustration, we use the intelligent-driver model (IDM) as the underlying model, characterize the level of service solely by the velocity, and couple the internal variable to the IDM parameter “time gap” to model an increase of the time gap in congested traffic (“frustration effect”), which is supported by single-vehicle data. We simulate open systems with a bottleneck and obtain flow-density data by implementing “virtual detectors.” The shape, relative size, and apparent “stochasticity” of the region of the scattered data points agree nearly quantitatively with empirical data. Wide scattering is even observed for identical vehicles, although the proposed model is a time-continuous, deterministic, single-lane car-following model with a unique fundamental diagram.

An adaptive two-stage energy-efficiency mechanism for the doze mode in EPON

NASA Astrophysics Data System (ADS)

Nikoukar, AliAkbar; Hwang, I.-Shyan; Su, Yu-Min; Liem, Andrew Tanny

2016-07-01

Sleep and doze power-saving modes are the common ways to reduce power consumption of optical network units (ONUs) in Ethernet passive optical network (EPON). The doze mode turns off the ONU transmitter when there is no traffic in the upstream direction while the sleep mode turns off the ONU transmitter and receiver. As the result, the sleep mode is more efficient compared to the doze mode, but it introduces additional complexity of scheduling and signaling, losses the clock synchronization and requires long clock recovery time; furthermore, it requires the cooperation of the optical line terminal (OLT) in the downstream direction to queue frames. To improve the energy-saving in the doze mode, a new two-stage mechanism is introduced that the doze sleep duration is extended for longer time with acceptable quality-of-services (QoS) metrics when ONU is idle in the current cycle. By this way the ONU enters the doze mode even in the high load traffic; moreover, the green dynamic bandwidth allocation (GBA) is proposed to calculate the doze sleep duration based on the ONU queue state and incoming traffic ratio. Simulation results show that the proposed mechanism significantly improves the energy-saving 74% and 54% when traffic load is from the light load to the high load in different traffic situations, and also promises the QoS performance.

Modeling connected and autonomous vehicles in heterogeneous traffic flow

NASA Astrophysics Data System (ADS)

Ye, Lanhang; Yamamoto, Toshiyuki

2018-01-01

The objective of this study was to develop a heterogeneous traffic-flow model to study the possible impact of connected and autonomous vehicles (CAVs) on the traffic flow. Based on a recently proposed two-state safe-speed model (TSM), a two-lane cellular automaton (CA) model was developed, wherein both the CAVs and conventional vehicles were incorporated in the heterogeneous traffic flow. In particular, operation rules for CAVs are established considering the new characteristics of this emerging technology, including autonomous driving through the adaptive cruise control and inter-vehicle connection via short-range communication. Simulations were conducted under various CAV-penetration rates in the heterogeneous flow. The impact of CAVs on the road capacity was numerically investigated. The simulation results indicate that the road capacity increases with an increase in the CAV-penetration rate within the heterogeneous flow. Up to a CAV-penetration rate of 30%, the road capacity increases gradually; the effect of the difference in the CAV capability on the growth rate is insignificant. When the CAV-penetration rate exceeds 30%, the growth rate is largely decided by the capability of the CAV. The greater the capability, the higher the road-capacity growth rate. The relationship between the CAV-penetration rate and the road capacity is numerically analyzed, providing some insights into the possible impact of the CAVs on traffic systems.

Military Curricula for Vocational and Technical Education. Traffic Management and Accident Investigation, 17-8.

ERIC Educational Resources Information Center

Air Force, Washington, DC.

This teaching guide and student workbook for a postsecondary level course in traffic management and accident investigation is one of a number of military-developed curriculum packages selected for adaptation to vocational instruction and curriculum development in a civilian setting. Purpose stated for the 132-hour course is to expose students to…

Non-Uniform Per-Packet Priority Marker for Use with Adaptive Protocols

DTIC Science & Technology

2014-01-07

through con­ gestion points that would totally stop traffic from a customer using the SLA shown in FIG. 5, though only some fraction of his traffic...assigning priori­ ties to TCP flows. PDQoS has potential to fill the need for a quality of service mechanism that is simple to configure and to

Traffic dynamics of carnival processions

NASA Astrophysics Data System (ADS)

Polichronidis, Petros; Wegerle, Dominik; Dieper, Alexander; Schreckenberg, Michael

2018-03-01

The traffic dynamics of processions are described in this study. GPS data from participating groups in the Cologne Rose Monday processions 2014–2017 are used to analyze the kinematic characteristics. The preparation of the measured data requires an adjustment by a specially adapted algorithm for the map matching method. A higher average velocity is observed for the last participant, the Carnival Prince, than for the leading participant of the parade. Based on the results of the data analysis, for the first time a model can be established for defilading parade groups as a modified Nagel-Schreckenberg model. This model can reproduce the observed characteristics in simulations. They can be explained partly by the constantly moving vehicle driving ahead of the parade leaving the pathway and partly due to a spatial contraction of the parade during the procession.

Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS) Networks with Ensuring the Fairness for Other Traffics

PubMed Central

Al-Shargabi, Mohammed A.; Ismail, Abdulsamad S.

2016-01-01

Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS’ QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50–60%, 30–40%, and 10–20% for high, normal, and low traffic loads respectively. PMID:27583557

Evaluating the safety impact of adaptive cruise control in traffic oscillations on freeways.

PubMed

Li, Ye; Li, Zhibin; Wang, Hao; Wang, Wei; Xing, Lu

2017-07-01

Adaptive cruise control (ACC) has been considered one of the critical components of automated driving. ACC adjusts vehicle speeds automatically by measuring the status of the ego-vehicle and leading vehicle. Current commercial ACCs are designed to be comfortable and convenient driving systems. Little attention is paid to the safety impacts of ACC, especially in traffic oscillations when crash risks are the highest. The primary objective of this study was to evaluate the impacts of ACC parameter settings on rear-end collisions on freeways. First, the occurrence of a rear-end collision in a stop-and-go wave was analyzed. A car-following model in an integrated ACC was developed for a simulation analysis. The time-to-collision based factors were calculated as surrogate safety measures of the collision risk. We also evaluated different market penetration rates considering that the application of ACC will be a gradual process. The results showed that the safety impacts of ACC were largely affected by the parameters. Smaller time delays and larger time gaps improved safety performance, but inappropriate parameter settings increased the collision risks and caused traffic disturbances. A higher reduction of the collision risk was achieved as the ACC vehicle penetration rate increased, especially in the initial stage with penetration rates of less than 30%. This study also showed that in the initial stage, the combination of ACC and a variable speed limit achieved better safety improvements on congested freeways than each single technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

CATS-based Air Traffic Controller Agents

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.

Adaptive mechanism-based congestion control for networked systems

NASA Astrophysics Data System (ADS)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

Spatial correlation analysis of urban traffic state under a perspective of community detection

NASA Astrophysics Data System (ADS)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Grazing Soybean to Increase Voluntary Cow Traffic in a Pasture-based Automatic Milking System

PubMed Central

Clark, C. E. F.; Horadagoda, A.; Kerrisk, K. L.; Scott, V.; Islam, M. R.; Kaur, R.; Garcia, S. C.

2014-01-01

Pasture-based automatic milking systems (AMS) require cow traffic to enable cows to be milked. The interval between milkings can be manipulated by strategically allocating pasture. The current experiment investigated the effect of replacing an allocation of grazed pasture with grazed soybean (Glycine max) with the hypothesis that incorporating soybean would increase voluntary cow traffic and milk production. One hundred and eighty mixed age, primiparous and multiparous Holstein-Friesian/Illawarra cows were randomly assigned to two treatment groups (n = 90/group) with a 2×2 Latin square design. Each group was either offered treatments of kikuyu grass (Pennisetum clandestinum Hoach ex Chiov.) pasture (pasture) or soybean from 0900 h to 1500 h during the experimental period which consisted of 2 periods of 3 days following 5 days of training and adaptation in each period with groups crossing over treatments after the first period. The number of cows trafficking to each treatment was similar together with milk yield (mean ≈18 L/cow/d) in this experiment. For the cows that arrived at soybean or pasture there were significant differences in their behaviour and consequently the number of cows exiting each treatment paddock. There was greater cow traffic (more cows and sooner) exiting pasture allocations. Cows that arrived at soybean stayed on the allocation for 25% more time and ate more forage (8.5 kg/cow/d/allocation) relative to pasture (4.7 kg/cow/d/allocation). Pasture cows predominantly replaced eating time with rumination. These findings suggest that replacing pasture with alternative grazeable forages provides no additional incentive to increase voluntary cow traffic to an allocation of feed in AMS. This work highlights the opportunity to increase forage intakes in AMS through the incorporation of alternative forages. PMID:25049970

Gateway: An earth orbiting transportation node

NASA Technical Reports Server (NTRS)

1988-01-01

University of Texas Mission Design (UTMD) has outlined the components that a space based transportation facility must include in order to support the first decade of Lunar base buildup. After studying anticipated traffic flow to and from the hub, and taking into account crew manhour considerations, propellant storage, orbital transfer vehicle maintenance requirements, and orbital mechanics, UTMD arrived at a design for the facility. The amount of activity directly related to supporting Lunar base traffic is too high to allow the transportation hub to be part of the NASA Space Station. Instead, a separate structure should be constructed and dedicated to handling all transportation-related duties. UTMD found that the structure (named Gateway) would need a permanent crew of four to perform maintenance tasks on the orbital transfer and orbital maneuvering vehicles and to transfer payload from launch vehicles to the orbital transfer vehicles. In addition, quarters for 4 more persons should be allocated for temporary accommodation of Lunar base crew passing through Gateway. UTMD was careful to recommend an expendable structure that can adapt to meet the growing needs of the American space program.

A Learning System for Discriminating Variants of Malicious Network Traffic

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

Beaver, Justin M; Symons, Christopher T; Gillen, Rob

Modern computer network defense systems rely primarily on signature-based intrusion detection tools, which generate alerts when patterns that are pre-determined to be malicious are encountered in network data streams. Signatures are created reactively, and only after in-depth manual analysis of a network intrusion. There is little ability for signature-based detectors to identify intrusions that are new or even variants of an existing attack, and little ability to adapt the detectors to the patterns unique to a network environment. Due to these limitations, the need exists for network intrusion detection techniques that can more comprehensively address both known unknown networkbased attacksmore » and can be optimized for the target environment. This work describes a system that leverages machine learning to provide a network intrusion detection capability that analyzes behaviors in channels of communication between individual computers. Using examples of malicious and non-malicious traffic in the target environment, the system can be trained to discriminate between traffic types. The machine learning provides insight that would be difficult for a human to explicitly code as a signature because it evaluates many interdependent metrics simultaneously. With this approach, zero day detection is possible by focusing on similarity to known traffic types rather than mining for specific bit patterns or conditions. This also reduces the burden on organizations to account for all possible attack variant combinations through signatures. The approach is presented along with results from a third-party evaluation of its performance.« less

The impact of medicinal drugs on traffic safety: a systematic review of epidemiological studies.

PubMed

Orriols, Ludivine; Salmi, Louis-Rachid; Philip, Pierre; Moore, Nicholas; Delorme, Bernard; Castot, Anne; Lagarde, Emmanuel

2009-08-01

To evaluate the quality of epidemiological research into effects of medicinal drugs on traffic safety and the current knowledge in this area. The bibliographic search was done in Medline electronic database using the keywords: ((accident* or crash*) and traffic and drug*) leading to 1141 references. Additional references were retrieved from the Safetylit website and the reference lists of selected studies. Original articles published in English or French, between 1 April 1979 and 31 July 2008, were considered for inclusion. We excluded descriptive studies, studies limited to alcohol or illicit drug involvement and investigations of injuries other than from traffic crashes. Studies based on laboratory tests, driving simulators or on-the-road driving tests were also excluded. Eligible studies had to evaluate the causal relationship between the use of medicinal drugs and the risk of traffic crashes. Study quality was assessed by two independent experts, according to a grid adapted from the strengthening the reporting of observational studies in epidemiology (STROBE) statement. Twenty two studies of variable methodological quality were included. Definition of drug exposure varied across studies and depended on the data sources. Potential confounding due to the interaction between the effects of the medicinal drug and disease-related symptoms was often not controlled. The risk of motor-vehicle crashes related to benzodiazepines has been amply studied and demonstrated. Results for other medicinal drugs remain controversial. There is a need for large studies, investigating the role of individual substances in the risk of road traffic crashes. Copyright 2009 John Wiley & Sons, Ltd.

[Fitness for automobile driving of physically handicapped patients].

PubMed

Ekkernkamp, A; Gerlach, D

1987-05-01

Some 30.5 million Germans hold a driving license. For the person with a physical handicap, too, active traffic participation is of special importance, in that it constitutes an essential link in his rehabilitation. Road traffic authorities, in view of traffic safety, are held to consider both, the handicapped individual's interest in obtaining a license and society's claim to safety. Numerous studies have established the fact that disabled drivers, in particular those with impairment of the limbs, are neither more accident-prone nor otherwise more conspicious in road traffic than the non-disabled. The view that the driver with a physical disability poses particular risks, has been invalidated by extensive factual data and thorough literature review. Diseases of major relevance for driving ability are touched on, the range of adaptive equipment is exemplified. Physicians in accident surgery primarily have to deal with trauma to the spinal cord and limbs. The majority of these conditions permit good compensation by technical devices, enabling safe driving of a private car. Awareness of legal/administrative aspects of licensing, as well as of the adaptive potential of technical aids are of great importance to both physician and client.

Adaptive Traffic Route Control in QoS Provisioning for Cognitive Radio Technology with Heterogeneous Wireless Systems

NASA Astrophysics Data System (ADS)

Yamamoto, Toshiaki; Ueda, Tetsuro; Obana, Sadao

As one of the dynamic spectrum access technologies, “cognitive radio technology,” which aims to improve the spectrum efficiency, has been studied. In cognitive radio networks, each node recognizes radio conditions, and according to them, optimizes its wireless communication routes. Cognitive radio systems integrate the heterogeneous wireless systems not only by switching over them but also aggregating and utilizing them simultaneously. The adaptive control of switchover use and concurrent use of various wireless systems will offer a stable and flexible wireless communication. In this paper, we propose the adaptive traffic route control scheme that provides high quality of service (QoS) for cognitive radio technology, and examine the performance of the proposed scheme through the field trials and computer simulations. The results of field trials show that the adaptive route control according to the radio conditions improves the user IP throughput by more than 20% and reduce the one-way delay to less than 1/6 with the concurrent use of IEEE802.16 and IEEE802.11 wireless media. Moreover, the simulation results assuming hundreds of mobile terminals reveal that the number of users receiving the required QoS of voice over IP (VoIP) service and the total network throughput of FTP users increase by more than twice at the same time with the proposed algorithm. The proposed adaptive traffic route control scheme can enhance the performances of the cognitive radio technologies by providing the appropriate communication routes for various applications to satisfy their required QoS.

Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

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

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

Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better atmore » higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO 2, NO x, VOC, PM 10) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.« less

Impacts analysis of car following models considering variable vehicular gap policies

NASA Astrophysics Data System (ADS)

Xin, Qi; Yang, Nan; Fu, Rui; Yu, Shaowei; Shi, Zhongke

2018-07-01

Due to the important roles playing in the vehicles' adaptive cruise control system, variable vehicular gap polices were employed to full velocity difference model (FVDM) to investigate the traffic flow properties. In this paper, two new car following models were put forward by taking constant time headway(CTH) policy and variable time headway(VTH) policy into optimal velocity function, separately. By steady state analysis of the new models, an equivalent optimal velocity function was defined. To determine the linear stable conditions of the new models, we introduce equivalent expressions of safe vehicular gap, and then apply small amplitude perturbation analysis and long terms of wave expansion techniques to obtain the new models' linear stable conditions. Additionally, the first order approximate solutions of the new models were drawn at the stable region, by transforming the models into typical Burger's partial differential equations with reductive perturbation method. The FVDM based numerical simulations indicate that the variable vehicular gap polices with proper parameters directly contribute to the improvement of the traffic flows' stability and the avoidance of the unstable traffic phenomena.

Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach

NASA Astrophysics Data System (ADS)

Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei

2018-07-01

A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.

Distributed learning and multi-objectivity in traffic light control

NASA Astrophysics Data System (ADS)

Brys, Tim; Pham, Tong T.; Taylor, Matthew E.

2014-01-01

Traffic jams and suboptimal traffic flows are ubiquitous in modern societies, and they create enormous economic losses each year. Delays at traffic lights alone account for roughly 10% of all delays in US traffic. As most traffic light scheduling systems currently in use are static, set up by human experts rather than being adaptive, the interest in machine learning approaches to this problem has increased in recent years. Reinforcement learning (RL) approaches are often used in these studies, as they require little pre-existing knowledge about traffic flows. Distributed constraint optimisation approaches (DCOP) have also been shown to be successful, but are limited to cases where the traffic flows are known. The distributed coordination of exploration and exploitation (DCEE) framework was recently proposed to introduce learning in the DCOP framework. In this paper, we present a study of DCEE and RL techniques in a complex simulator, illustrating the particular advantages of each, comparing them against standard isolated traffic actuated signals. We analyse how learning and coordination behave under different traffic conditions, and discuss the multi-objective nature of the problem. Finally we evaluate several alternative reward signals in the best performing approach, some of these taking advantage of the correlation between the problem-inherent objectives to improve performance.

Integrated Demand Management: Minimizing Unanticipated Excessive Departure Delay while Ensuring Fairness from a Traffic Management Initiative

NASA Technical Reports Server (NTRS)

Yoo, Hyo-Sang; Brasil, Connie; Buckley, Nathan; Mohlenbrink, Christoph; Speridakos, Constantine; Parke, Bonny; Hodell, Gita; Lee, Paul U.; Smith, Nancy M.

2017-01-01

This paper introduces NASA's Integrated Demand Management (IDM) concept and presents the results from an early proof-of-concept evaluation and an exploratory experiment. An initial development of the concept was focused on integrating two systems - i.e. the FAA's newly deployed Traffic Flow Management System (TFMS) tool called the Collaborative Trajectory Options Program (CTOP) and the Time-Based Flow Management (TBFM) system with Extended Metering (XM) capabilities to manage projected heavy traffic demand into a capacity-constrained airport. A human-in-the-loop (HITL) simulation experiment was conducted to demonstrate the feasibility of the initial development of the concept by adapting it to an arrival traffic problem at Newark Liberty International Airport (EWR) during clear weather conditions. In this study, the CTOP was utilized to strategically plan the arrival traffic demand by controlling take-off times of both short- and long-haul flights (long-hauls specify aircraft outside TBFM regions and short-hauls specify aircraft within TBFM regions) in a way that results in equitable delays among the groups. Such strategic planning allows less airborne delay to occur within TBFM by feeding manageable long-haul traffic demand while reserving sufficient slots in the overhead streams for the short-haul departures. The manageable traffic demand indicates the TBFM scheduler assigns no more airborne delay than its assigned airspace is capable of absorbing. TBFM then uses its time-based metering capabilities to deliver the desirable throughput by tactically rescheduling the TBFM entered long-haul flights and short-haul departures. Additional research was also performed to explore use of Required Time of Arrival (RTA) capabilities as a potential control mechanism for the airborne flights to improve arrival traffic delivery accuracy of scheduled long-haul traffic demand. The study results show that both short- and long-haul flights received similar ground delays. In addition, there was a noticeable reduction in the total amount of excessive unanticipated last-minute ground delays, i.e. delays that are frequently imposed on the short-haul flight in current day operations due to saturation in the overhead stream, commonly referred to as 'double penalty'. Furthermore, the concept achieved the target throughput while minimizing the expected cost associated with overall delays in arrival traffic. Assessment of the RTA capabilities showed that there was indeed improvement of the scheduled entry times into TBFM regions by using RTA capabilities. However, with respect to reduction in delays incurred within TBFM, there was no observable benefit of improving the precision of long-haul flights entry times.

Adaptation of time line analysis program to single pilot instrument flight research

NASA Technical Reports Server (NTRS)

Hinton, D. A.; Shaughnessy, J. D.

1978-01-01

A data base was developed for SPIFR operation and the program was run. The outputs indicated that further work was necessary on the workload models. In particular, the workload model for the cognitive channel should be modified as the output workload appears to be too small. Included in the needed refinements are models to show the workload when in turbulence, when overshooting a radial or glideslope, and when copying air traffic control clearances.

The relationship of dangerous driving with traffic offenses: A study on an adapted measure of dangerous driving.

PubMed

Iliescu, Dragoş; Sârbescu, Paul

2013-03-01

Using data from three different samples and more than 1000 participants, the current study examines differences in dangerous driving in terms of age, gender, professional driving, as well as the relationship of dangerous driving with behavioral indicators (mileage) and criteria (traffic offenses). The study uses an adapted (Romanian) version of the Dula Dangerous Driving Index (DDDI, Dula and Ballard, 2003) and also reports data on the psychometric characteristics of this measure. Findings suggest that the Romanian version of the DDDI has sound psychometric properties. Dangerous driving is higher in males and occasional drivers, is not correlated with mileage and is significantly related with speeding as a traffic offense, both self-reported and objectively measured. The utility of predictive models including dangerous driving is not very large: logistic regression models have a significant fit to the data, but their misclassification rate (especially in terms of sensitivity) is unacceptable high. Copyright © 2012 Elsevier Ltd. All rights reserved.

Online boosting for vehicle detection.

PubMed

Chang, Wen-Chung; Cho, Chih-Wei

2010-06-01

This paper presents a real-time vision-based vehicle detection system employing an online boosting algorithm. It is an online AdaBoost approach for a cascade of strong classifiers instead of a single strong classifier. Most existing cascades of classifiers must be trained offline and cannot effectively be updated when online tuning is required. The idea is to develop a cascade of strong classifiers for vehicle detection that is capable of being online trained in response to changing traffic environments. To make the online algorithm tractable, the proposed system must efficiently tune parameters based on incoming images and up-to-date performance of each weak classifier. The proposed online boosting method can improve system adaptability and accuracy to deal with novel types of vehicles and unfamiliar environments, whereas existing offline methods rely much more on extensive training processes to reach comparable results and cannot further be updated online. Our approach has been successfully validated in real traffic environments by performing experiments with an onboard charge-coupled-device camera in a roadway vehicle.

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.

[The history of optical signals for traffic regulation].

PubMed

Draeger, J; Harsch, V

2008-04-01

For signal transmission in traffic today, different optical, acoustic, or other physical or technical means are used for information. The different kinds of traffic (water navigation, road and rail, and, later air transport) made traffic regulation necessary early on. This regulation, from its very beginning in ancient times, began by means of optical signals; nowadays, this remains the most important method. From the very start, minimum requirements for the navigator's vision, color discrimination, dark adaptation, and even visual field were needed. For historical reasons, it was in seafaring medicine that these first developed. Besides the development of the different signals, methods for checking the requirements were soon developed. National and international requirements have been very different. Only within the last 50 years has international cooperation led to the acceptance of general standards for the different traffic modes. This article discusses the technical development of optical signals for the different kinds of traffic, from ancient times to the present, and explains the development of minimum requirements for the different visual functions.

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics

PubMed Central

2017-01-01

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.

PubMed

Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier

2017-10-21

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.

The Development of the Multi-Center Traffic Management Advisor (MCTMA): Traffic Flow Management Research in a Multi-Facility Environment

NASA Technical Reports Server (NTRS)

Lee, Katharine K.; Davis, Thomas J.; Levin, Kerry M.; Rowe, Dennis W.

2001-01-01

The Traffic Management Advisor (TMA) is a decision-support tool for traffic managers and air traffic controllers that provides traffic flow visualization and other flow management tools. TMA creates an efficiently sequenced and safely spaced schedule for arrival traffic that meets but does not exceed specified airspace system constraints. TMA is being deployed at selected facilities throughout the National Airspace System in the US as part of the FAA's Free Flight Phase 1 program. TMA development and testing, and its current deployment, focuses on managing the arrival capacity for single major airports within single terminal areas and single en route centers. The next phase of development for this technology is the expansion of the TMA capability to complex facilities in which a terminal area or airport is fed by multiple en route centers, thus creating a multicenter TMA functionality. The focus of the multi-center TMA (McTMA) development is on the busy facilities in the Northeast comdor of the US. This paper describes the planning and development of McTMA and the challenges associated with adapting a successful traffic flow management tool for a very complex airspace.

Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment.

PubMed

Aricò, Pietro; Borghini, Gianluca; Di Flumeri, Gianluca; Colosimo, Alfredo; Bonelli, Stefano; Golfetti, Alessia; Pozzi, Simone; Imbert, Jean-Paul; Granger, Géraud; Benhacene, Raïlane; Babiloni, Fabio

2016-01-01

Adaptive Automation (AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both the under - and over-load conditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the AA solutions without affecting the operative task. In this regard, passive Brain-Computer Interface (pBCI) systems are a good candidate to activate automation, since they are able to gather information about the covert behavior (e.g., mental workload) of a subject by analyzing its neurophysiological signals (i.e., brain activity), and without interfering with the ongoing operational activity. We proposed a pBCI system able to trigger AA solutions integrated in a realistic Air Traffic Management (ATM) research simulator developed and hosted at ENAC (É cole Nationale de l'Aviation Civile of Toulouse, France). Twelve Air Traffic Controller (ATCO) students have been involved in the experiment and they have been asked to perform ATM scenarios with and without the support of the AA solutions. Results demonstrated the effectiveness of the proposed pBCI system, since it enabled the AA mostly during the high-demanding conditions (i.e., overload situations) inducing a reduction of the mental workload under which the ATCOs were operating. On the contrary, as desired, the AA was not activated when workload level was under the threshold, to prevent too low demanding conditions that could bring the operator's workload level toward potentially dangerous conditions of underload.

Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment

PubMed Central

Aricò, Pietro; Borghini, Gianluca; Di Flumeri, Gianluca; Colosimo, Alfredo; Bonelli, Stefano; Golfetti, Alessia; Pozzi, Simone; Imbert, Jean-Paul; Granger, Géraud; Benhacene, Raïlane; Babiloni, Fabio

2016-01-01

Adaptive Automation (AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both the under- and over-load conditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the AA solutions without affecting the operative task. In this regard, passive Brain-Computer Interface (pBCI) systems are a good candidate to activate automation, since they are able to gather information about the covert behavior (e.g., mental workload) of a subject by analyzing its neurophysiological signals (i.e., brain activity), and without interfering with the ongoing operational activity. We proposed a pBCI system able to trigger AA solutions integrated in a realistic Air Traffic Management (ATM) research simulator developed and hosted at ENAC (École Nationale de l'Aviation Civile of Toulouse, France). Twelve Air Traffic Controller (ATCO) students have been involved in the experiment and they have been asked to perform ATM scenarios with and without the support of the AA solutions. Results demonstrated the effectiveness of the proposed pBCI system, since it enabled the AA mostly during the high-demanding conditions (i.e., overload situations) inducing a reduction of the mental workload under which the ATCOs were operating. On the contrary, as desired, the AA was not activated when workload level was under the threshold, to prevent too low demanding conditions that could bring the operator's workload level toward potentially dangerous conditions of underload. PMID:27833542

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems.

PubMed

Munera, Eduardo; Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Noguera, Juan Fco Blanes

2015-07-24

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client's requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client's requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

Integrated driver modelling considering state transition feature for individual adaptation of driver assistance systems

NASA Astrophysics Data System (ADS)

Raksincharoensak, Pongsathorn; Khaisongkram, Wathanyoo; Nagai, Masao; Shimosaka, Masamichi; Mori, Taketoshi; Sato, Tomomasa

2010-12-01

This paper describes the modelling of naturalistic driving behaviour in real-world traffic scenarios, based on driving data collected via an experimental automobile equipped with a continuous sensing drive recorder. This paper focuses on the longitudinal driving situations which are classified into five categories - car following, braking, free following, decelerating and stopping - and are referred to as driving states. Here, the model is assumed to be represented by a state flow diagram. Statistical machine learning of driver-vehicle-environment system model based on driving database is conducted by a discriminative modelling approach called boosting sequential labelling method.

Fully programmable and scalable optical switching fabric for petabyte data center.

PubMed

Zhu, Zhonghua; Zhong, Shan; Chen, Li; Chen, Kai

2015-02-09

We present a converged EPS and OCS switching fabric for data center networks (DCNs) based on a distributed optical switching architecture leveraging both WDM & SDM technologies. The architecture is topology adaptive, well suited to dynamic and diverse *-cast traffic patterns. Compared to a typical folded-Clos network, the new architecture is more readily scalable to future multi-Petabyte data centers with 1000 + racks while providing a higher link bandwidth, reducing transceiver count by 50%, and improving cabling efficiency by more than 90%.

Low-cost Cognitive Electronics Technology for Enhanced Communications and Situational Awareness for Networks of Small Unmanned Aerial Vehicles (UAV)

DTIC Science & Technology

2013-03-01

series of checkpoints in a complex route network,” while observing standard traffic etiquette and regulations [17]. The rules for the 2012 RoboCup...structure or protocols above the PHY. To support AVEP operation, we developed a packet structure based on the transmission control protocol (TCP...Control Protocol .” 1981. [37] F. Ge, Q. Chen, Y. Wang, C. W. Bostian, T. W. Rondeau, and B. Le, “Cognitive radio: from spectrum sharing to adaptive

Guidelines for Assessing the Need for Adaptive Devices for Visually Impaired Pedestrians at Signalized Intersections.

ERIC Educational Resources Information Center

Gallagher, Brian R.; de Oca, Patricia Montes

1998-01-01

Presents guidelines for orientation and mobility instructors and traffic engineers to assess the need for adaptive devices to make crosswalks at signalized intersections accessible to pedestrians with visual impairments. The discussions of audible and tactile pedestrian devices, along with case examples, distinguish when each device should be…

Ramp - Metering Algorithms Evaluated within Simplified Conditions

NASA Astrophysics Data System (ADS)

Janota, Aleš; Holečko, Peter; Gregor, Michal; Hruboš, Marián

2017-12-01

Freeway networks reach their limits, since it is usually impossible to increase traffic volumes by indefinitely extending transport infrastructure through adding new traffic lanes. One of the possible solutions is to use advanced intelligent transport systems, particularly ramp metering systems. The paper shows how two particular algorithms of local and traffic-responsive control (Zone, ALINEA) can be adapted to simplified conditions corresponding to Slovak freeways. Both control strategies are modelled and simulated using PTV Vissim software, including the module VisVAP. Presented results demonstrate the properties of both control strategies, which are compared mutually as well as with the initial situation in which no control strategy is applied

Street Viewer: An Autonomous Vision Based Traffic Tracking System.

PubMed

Bottino, Andrea; Garbo, Alessandro; Loiacono, Carmelo; Quer, Stefano

2016-06-03

The development of intelligent transportation systems requires the availability of both accurate traffic information in real time and a cost-effective solution. In this paper, we describe Street Viewer, a system capable of analyzing the traffic behavior in different scenarios from images taken with an off-the-shelf optical camera. Street Viewer operates in real time on embedded hardware architectures with limited computational resources. The system features a pipelined architecture that, on one side, allows one to exploit multi-threading intensively and, on the other side, allows one to improve the overall accuracy and robustness of the system, since each layer is aimed at refining for the following layers the information it receives as input. Another relevant feature of our approach is that it is self-adaptive. During an initial setup, the application runs in learning mode to build a model of the flow patterns in the observed area. Once the model is stable, the system switches to the on-line mode where the flow model is used to count vehicles traveling on each lane and to produce a traffic information summary. If changes in the flow model are detected, the system switches back autonomously to the learning mode. The accuracy and the robustness of the system are analyzed in the paper through experimental results obtained on several different scenarios and running the system for long periods of time.

Informing road traffic intervention choices in South Africa: the role of economic evaluations

PubMed Central

Wesson, Hadley K.H.; Boikhutso, Nkuli; Hyder, Adnan A.; Bertram, Melanie; Hofman, Karen J.

2016-01-01

Introduction Given the burden of road traffic injuries (RTIs) in South Africa, economic evaluations of prevention interventions are necessary for informing and prioritising public health planning and policy with regard to road safety. Methods In view of the dearth of RTI cost analysis, and in order to understand the extent to which RTI-related costs in South Africa compare with those in other low- and middle-income countries (LMICs), we reviewed published economic evaluations of RTI-related prevention in LMICs. Results Thirteen articles were identified, including cost-of-illness and cost-effectiveness studies. Although RTI-related risk factors in South Africa are well described, costing studies are limited. There is minimal information, most of which is not recent, with nothing at all on societal costs. Cost-effective interventions for RTIs in LMICs include bicycle and motorcycle helmet enforcement, traffic enforcement, and the construction of speed bumps. Discussion Policy recommendations from studies conducted in LMICs suggest a number of cost-effective interventions for consideration in South Africa. They include speed bumps for pedestrian safety, strategically positioned speed cameras, traffic enforcement such as the monitoring of seatbelt use, and breathalyzer interventions. However, interventions introduced in South Africa will need to be based either on South African cost-effectiveness data or on findings adapted from similar middle-income country settings. PMID:27396485

Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

PubMed Central

Murata, Masayuki

2013-01-01

The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account. PMID:24319375

An improved car-following model considering headway changes with memory

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Shi, Zhongke

2015-03-01

To describe car-following behaviors in complex situations better, increase roadway traffic mobility and minimize cars' fuel consumptions, the linkage between headway changes with memory and car-following behaviors was explored with the field car-following data by using the gray correlation analysis method, and then an improved car-following model considering headway changes with memory on a single lane was proposed based on the full velocity difference model. Some numerical simulations were carried out by employing the improved car-following model to explore how headway changes with memory affected each car's velocity, acceleration, headway and fuel consumptions. The research results show that headway changes with memory have significant effects on car-following behaviors and fuel consumptions and that considering headway changes with memory in designing the adaptive cruise control strategy can improve the traffic flow stability and minimize cars' fuel consumptions.

Traffic Adaptive Energy Efficient and Low Latency Medium Access Control for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Yadav, Rajesh; Varma, Shirshu; Malaviya, N.

2008-05-01

Medium access control for wireless sensor networks has been a very active research area in the recent years. The traditional wireless medium access control protocol such as IEEE 802.11 is not suitable for the sensor network application because these are battery powered. The recharging of these sensor nodes is expensive and also not possible. The most of the literature in the medium access for the sensor network focuses on the energy efficiency. The proposed MAC protocol solves the energy inefficiency caused by idle listening, control packet overhead and overhearing taking nodes latency into consideration based on the network traffic. Simulation experiments have been performed to demonstrate the effectiveness of the proposed approach. The validation of the simulation results of the proposed MAC has been done by comparing it with the analytical model. This protocol has been simulated in Network Simulator ns-2.

Environmental Assessment Addressing the Emerald Breeze Resort, Santa Rosa Island, Fort Walton Beach, Florida

DTIC Science & Technology

2009-09-11

conditions in their upper part. Anaerobic soil conditions are conducive to the establishment of vegetation that is adapted for growth under oxygen...sufficient to support, and that under normal circumstances do support, a prevalence of vegetation typically adapted to life in saturated soil...species adapted to dense commercial development and heavy vehicular traffic would be expected to move back into the area after development of the

Understanding widely scattered traffic flows, the capacity drop, and platoons as effects of variance-driven time gaps

NASA Astrophysics Data System (ADS)

Treiber, Martin; Kesting, Arne; Helbing, Dirk

2006-07-01

We investigate the adaptation of the time headways in car-following models as a function of the local velocity variance, which is a measure of the inhomogeneity of traffic flow. We apply this mechanism to several car-following models and simulate traffic breakdowns in open systems with an on-ramp as bottleneck and in a closed ring road. Single-vehicle data and one-minute aggregated data generated by several virtual detectors show a semiquantitative agreement with microscopic and flow-density data from the Dutch freeway A9. This includes the observed distributions of the net time headways for free and congested traffic, the velocity variance as a function of density, and the fundamental diagram. The modal value of the time headway distribution is shifted by a factor of about 2 under congested conditions. Macroscopically, this corresponds to the capacity drop at the transition from free to congested traffic. The simulated fundamental diagram shows free, synchronized, and jammed traffic, and a wide scattering in the congested traffic regime. We explain this by a self-organized variance-driven process that leads to the spontaneous formation and decay of long-lived platoons even for a deterministic dynamics on a single lane.

Expanding the Use of Time-Based Metering: Multi-Center Traffic Management Advisor

NASA Technical Reports Server (NTRS)

Landry, Steven J.; Farley, Todd; Hoang, Ty

2005-01-01

Time-based metering is an efficient air traffic management alternative to the more common practice of distance-based metering (or "miles-in-trail spacing"). Despite having demonstrated significant operational benefit to airspace users and service providers, time-based metering is used in the United States for arrivals to just nine airports and is not used at all for non-arrival traffic flows. The Multi-Center Traffic Management Advisor promises to bring time-based metering into the mainstream of air traffic management techniques. Not constrained to operate solely on arrival traffic, Multi-Center Traffic Management Advisor is flexible enough to work in highly congested or heavily partitioned airspace for any and all traffic flows in a region. This broader and more general application of time-based metering is expected to bring the operational benefits of time-based metering to a much wider pool of beneficiaries than is possible with existing technology. It also promises to facilitate more collaborative traffic management on a regional basis. This paper focuses on the operational concept of the Multi-Center Traffic Management Advisor, touching also on its system architecture, field test results, and prospects for near-term deployment to the United States National Airspace System.

Air travel and vector-borne disease movement.

PubMed

Tatem, A J; Huang, Z; Das, A; Qi, Q; Roth, J; Qiu, Y

2012-12-01

Recent decades have seen substantial expansions in the global air travel network and rapid increases in traffic volumes. The effects of this are well studied in terms of the spread of directly transmitted infections, but the role of air travel in the movement of vector-borne diseases is less well understood. Increasingly however, wider reaching surveillance for vector-borne diseases and our improving abilities to map the distributions of vectors and the diseases they carry, are providing opportunities to better our understanding of the impact of increasing air travel. Here we examine global trends in the continued expansion of air transport and its impact upon epidemiology. Novel malaria and chikungunya examples are presented, detailing how geospatial data in combination with information on air traffic can be used to predict the risks of vector-borne disease importation and establishment. Finally, we describe the development of an online tool, the Vector-Borne Disease Airline Importation Risk (VBD-Air) tool, which brings together spatial data on air traffic and vector-borne disease distributions to quantify the seasonally changing risks for importation to non-endemic regions. Such a framework provides the first steps towards an ultimate goal of adaptive management based on near real time flight data and vector-borne disease surveillance.

HPNAIDM: The High-Performance Network Anomaly/Intrusion Detection and Mitigation System

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

Chen, Yan

Identifying traffic anomalies and attacks rapidly and accurately is critical for large network operators. With the rapid growth of network bandwidth, such as the next generation DOE UltraScience Network, and fast emergence of new attacks/virus/worms, existing network intrusion detection systems (IDS) are insufficient because they: • Are mostly host-based and not scalable to high-performance networks; • Are mostly signature-based and unable to adaptively recognize flow-level unknown attacks; • Cannot differentiate malicious events from the unintentional anomalies. To address these challenges, we proposed and developed a new paradigm called high-performance network anomaly/intrustion detection and mitigation (HPNAIDM) system. The new paradigm ismore » significantly different from existing IDSes with the following features (research thrusts). • Online traffic recording and analysis on high-speed networks; • Online adaptive flow-level anomaly/intrusion detection and mitigation; • Integrated approach for false positive reduction. Our research prototype and evaluation demonstrate that the HPNAIDM system is highly effective and economically feasible. Beyond satisfying the pre-set goals, we even exceed that significantly (see more details in the next section). Overall, our project harvested 23 publications (2 book chapters, 6 journal papers and 15 peer-reviewed conference/workshop papers). Besides, we built a website for technique dissemination, which hosts two system prototype release to the research community. We also filed a patent application and developed strong international and domestic collaborations which span both academia and industry.« less

Cost savings associated with 10 years of road safety policies in Catalonia, Spain

PubMed Central

Suelves, Josep M; Barbería, Eneko

2013-01-01

Abstract Objective To determine whether the road safety policies introduced between 2000 and 2010 in Catalonia, Spain, which aimed primarily to reduce deaths from road traffic collisions by 50% by 2010, were associated with economic benefits to society. Methods A cost analysis was performed from a societal perspective with a 10-year time horizon. It considered the costs of: hospital admissions; ambulance transport; autopsies; specialized health care; police, firefighter and roadside assistance; adapting to disability; and productivity lost due to institutionalization, death or sick leave of the injured or their caregivers; as well as material and administrative costs. Data were obtained from a Catalan hospital registry, the Catalan Traffic Service information system, insurance companies and other sources. All costs were calculated in euros (€) at 2011 values. Findings A substantial reduction in deaths from road traffic collisions was observed between 2000 and 2010. Between 2001 and 2010, with the implementation of new road safety policies, there were 26 063 fewer road traffic collisions with victims than expected, 2909 fewer deaths (57%) and 25 444 fewer hospitalizations. The estimated total cost savings were around €18 000 million. Of these, around 97% resulted from reductions in lost productivity. Of the remaining cost savings, 63% were associated with specialized health care, 15% with adapting to disability and 8.1% with hospital care. Conclusion The road safety policies implemented in Catalonia in recent years were associated with a reduction in the number of deaths and injuries from traffic collisions and with substantial economic benefits to society. PMID:23397348

Spectrum-efficient multipath provisioning with content connectivity for the survivability of elastic optical datacenter networks

NASA Astrophysics Data System (ADS)

Gao, Tao; Li, Xin; Guo, Bingli; Yin, Shan; Li, Wenzhe; Huang, Shanguo

2017-07-01

Multipath provisioning is a survivable and resource efficient solution against increasing link failures caused by natural or man-made disasters in elastic optical datacenter networks (EODNs). Nevertheless, the conventional multipath provisioning scheme is designed only for connecting a specific node pair. Also, it is obvious that the number of node-disjoint paths between any two nodes is restricted to network connectivity, which has a fixed value for a given topology. Recently, the concept of content connectivity in EODNs has been proposed, which guarantees that a user can be served by any datacenter hosting the required content regardless of where it is located. From this new perspective, we propose a survivable multipath provisioning with content connectivity (MPCC) scheme, which is expected to improve the spectrum efficiency and the whole system survivability. We formulate the MPCC scheme with Integer Linear Program (ILP) in static traffic scenario and a heuristic approach is proposed for dynamic traffic scenario. Furthermore, to adapt MPCC to the variation of network state in dynamic traffic scenario, we propose a dynamic content placement (DCP) strategy in the MPCC scheme for detecting the variation of the distribution of user requests and adjusting the content location dynamically. Simulation results indicate that the MPCC scheme can reduce over 20% spectrum consumption than conventional multipath provisioning scheme in static traffic scenario. And in dynamic traffic scenario, the MPCC scheme can reduce over 20% spectrum consumption and over 50% blocking probability than conventional multipath provisioning scheme. Meanwhile, benefiting from the DCP strategy, the MPCC scheme has a good adaption to the variation of the distribution of user requests.

Coordinated traffic incident management using the I-Net embedded sensor architecture

NASA Astrophysics Data System (ADS)

Dudziak, Martin J.

1999-01-01

The I-Net intelligent embedded sensor architecture enables the reconfigurable construction of wide-area remote sensing and data collection networks employing diverse processing and data acquisition modules communicating over thin- server/thin-client protocols. Adaptive initially for operation using mobile remotely-piloted vehicle platforms such as small helicopter robots such as the Hornet and Ascend-I, the I-Net architecture lends itself to a critical problem in the management of both spontaneous and planned traffic congestion and rerouting over major interstate thoroughfares such as the I-95 Corridor. Pre-programmed flight plans and ad hoc operator-assisted navigation of the lightweight helicopter, using an auto-pilot and gyroscopic stabilization augmentation units, allows daytime or nighttime over-the-horizon flights of the unit to collect and transmit real-time video imagery that may be stored or transmitted to other locations. With on-board GPS and ground-based pattern recognition capabilities to augment the standard video collection process, this approach enables traffic management and emergency response teams to plan and assist real-time in the adjustment of traffic flows in high- density or congested areas or during dangerous road conditions such as during ice, snow, and hurricane storms. The I-Net architecture allows for integration of land-based and roadside sensors within a comprehensive automated traffic management system with communications to and form an airborne or other platform to devices in the network other than human-operated desktop computers, thereby allowing more rapid assimilation and response for critical data. Experiments have been conducted using several modified platforms and standard video and still photographic equipment. Current research and development is focused upon modification of the modular instrumentation units in order to accommodate faster loading and reloading of equipment onto the RPV, extension of the I-Net architecture to enable RPV-to-RPV signaling and control, and refinement of safety and emergency mechanisms to handle RPV mechanical failure during flight.

TCP throughput adaptation in WiMax networks using replicator dynamics.

PubMed

Anastasopoulos, Markos P; Petraki, Dionysia K; Kannan, Rajgopal; Vasilakos, Athanasios V

2010-06-01

The high-frequency segment (10-66 GHz) of the IEEE 802.16 standard seems promising for the implementation of wireless backhaul networks carrying large volumes of Internet traffic. In contrast to wireline backbone networks, where channel errors seldom occur, the TCP protocol in IEEE 802.16 Worldwide Interoperability for Microwave Access networks is conditioned exclusively by wireless channel impairments rather than by congestion. This renders a cross-layer design approach between the transport and physical layers more appropriate during fading periods. In this paper, an adaptive coding and modulation (ACM) scheme for TCP throughput maximization is presented. In the current approach, Internet traffic is modulated and coded employing an adaptive scheme that is mathematically equivalent to the replicator dynamics model. The stability of the proposed ACM scheme is proven, and the dependence of the speed of convergence on various physical-layer parameters is investigated. It is also shown that convergence to the strategy that maximizes TCP throughput may be further accelerated by increasing the amount of information from the physical layer.

Workload-Matched Adaptive Automation Support of Air Traffic Controller Information Processing Stages

NASA Technical Reports Server (NTRS)

Kaber, David B.; Prinzel, Lawrence J., III; Wright, Melanie C.; Clamann, Michael P.

2002-01-01

Adaptive automation (AA) has been explored as a solution to the problems associated with human-automation interaction in supervisory control environments. However, research has focused on the performance effects of dynamic control allocations of early stage sensory and information acquisition functions. The present research compares the effects of AA to the entire range of information processing stages of human operators, such as air traffic controllers. The results provide evidence that the effectiveness of AA is dependent on the stage of task performance (human-machine system information processing) that is flexibly automated. The results suggest that humans are better able to adapt to AA when applied to lower-level sensory and psychomotor functions, such as information acquisition and action implementation, as compared to AA applied to cognitive (analysis and decision-making) tasks. The results also provide support for the use of AA, as compared to completely manual control. These results are discussed in terms of implications for AA design for aviation.

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.

Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

1997-04-01

The use of artificial neural networks (NNs) to address the channel assignment problem (CAP) for cellular time-division multiple access and code-division multiple access networks has previously been investigated by this author and many others. The investigations to date have been based on a hexagonal cell structure established by omnidirectional antennas at the base stations. No account was taken of the use of spatial isolation enabled by directional antennas to reduce interference between mobiles. Any reduction in interference translates into increased capacity and consequently alters the performance of the NNs. Previous studies have sought to improve the performance of Hopfield- Tank network algorithms and self-organizing feature map algorithms applied primarily to static channel assignment (SCA) for cellular networks that handle uniformly distributed, stationary traffic in each cell for a single type of service. The resulting algorithms minimize energy functions representing interference constraint and ad hoc conditions that promote convergence to optimal solutions. While the structures of the derived neural network algorithms (NNAs) offer the potential advantages of inherent parallelism and adaptability to changing system conditions, this potential has yet to be fulfilled the CAP for emerging mobile networks. The next-generation communication infrastructures must accommodate dynamic operating conditions. Macrocell topologies are being refined to microcells and picocells that can be dynamically sectored by adaptively controlled, directional antennas and programmable transceivers. These networks must support the time-varying demands for personal communication services (PCS) that simultaneously carry voice, data and video and, thus, require new dynamic channel assignment (DCA) algorithms. This paper examines the impact of dynamic cell sectoring and geometric conditioning on NNAs developed for SCA in omnicell networks with stationary traffic to improve the metrics of convergence rate and call blocking. Genetic algorithms (GAs) are also considered in PCS networks as a means to overcome the known weakness of Hopfield NNAs in determining global minima. The resulting GAs for DCA in PCS networks are compared to improved DCA algorithms based on Hopfield NNs for stationary cellular networks. Algorithm performance is compared on the basis of rate of convergence, blocking probability, analytic complexity, and parametric sensitivity to transient traffic demands and channel interference.

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.

A critical review of principal traffic noise models: Strategies and implications

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

Garg, Naveen, E-mail: ngarg@mail.nplindia.ernet.in; Department of Mechanical, Production and Industrial Engineering, Delhi Technological University, Delhi 110042; Maji, Sagar

2014-04-01

The paper presents an exhaustive comparison of principal traffic noise models adopted in recent years in developed nations. The comparison is drawn on the basis of technical attributes including source modelling and sound propagation algorithms. Although the characterization of source in terms of rolling and propulsion noise in conjunction with advanced numerical methods for sound propagation has significantly reduced the uncertainty in traffic noise predictions, the approach followed is quite complex and requires specialized mathematical skills for predictions which is sometimes quite cumbersome for town planners. Also, it is sometimes difficult to follow the best approach when a variety ofmore » solutions have been proposed. This paper critically reviews all these aspects pertaining to the recent models developed and adapted in some countries and also discusses the strategies followed and implications of these models. - Highlights: • Principal traffic noise models developed are reviewed. • Sound propagation algorithms used in traffic noise models are compared. • Implications of models are discussed.« less

Automatic Data Distribution for CFD Applications on Structured Grids

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Yan, Jerry

1999-01-01

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAPT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAPT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

AFRICOM’s Adaptive Logistics Network: Database Feeds

DTIC Science & Technology

2012-04-11

maintenance, many thoroughfares are easily swallowed up by the nearby vegetation, thus serving to severely limit the already marginal flow of traffic , or...stop it altogether.5 This marginal flow of traffic originating on very few paved roads is usually occupied by vehicles that are generally older and...Liberia Roberts Int’l N/A Mali Senou Int’l N/A Mauritania Nouakchott Int’l Port of Nouadhibou Niger Diori Hamani Int’l Port of Niamey Nigeria Nnamdi

A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

PubMed Central

Wang, Jianqiang; Sun, Xiaoyan; Guo, Junbin

2013-01-01

The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS). This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR) of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

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.

FPGA implementation of advanced FEC schemes for intelligent aggregation networks

NASA Astrophysics Data System (ADS)

Zou, Ding; Djordjevic, Ivan B.

2016-02-01

In state-of-the-art fiber-optics communication systems the fixed forward error correction (FEC) and constellation size are employed. While it is important to closely approach the Shannon limit by using turbo product codes (TPC) and low-density parity-check (LDPC) codes with soft-decision decoding (SDD) algorithm; rate-adaptive techniques, which enable increased information rates over short links and reliable transmission over long links, are likely to become more important with ever-increasing network traffic demands. In this invited paper, we describe a rate adaptive non-binary LDPC coding technique, and demonstrate its flexibility and good performance exhibiting no error floor at BER down to 10-15 in entire code rate range, by FPGA-based emulation, making it a viable solution in the next-generation high-speed intelligent aggregation networks.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

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.

[Profiles of resilience and quality of life in people with acquired disability due to traffic accidents].

PubMed

Suriá Martínez, Raquel

2015-09-01

To identify distinct profiles of resilience in people with spinal cord injuries due to traffic accidents and to determine whether the profiles identified are related to differences in subjective well-being. The Resilience Scale (Wagnild and Young, 1993) and an adapted quality of life scale (GENCAT) were administered to 98 people with physical disabilities due to traffic accidents. Cluster analyses identified three different resilience profiles: a high-resilience group, a low-resilience group, and a group showing a predominance of high scores in self and life acceptance and social competence. The results also revealed statistically significant differences among profiles in most domains of subjective well-being. The results suggest the need to study resilience in greater depth and to design programs to enhance quality of life among people with disabilities due to traffic accidents. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

Exposure to lateral collision in signalized intersections with protected left turn under different traffic control strategies.

PubMed

Midenet, Sophie; Saunier, Nicolas; Boillot, Florence

2011-11-01

This paper proposes an original definition of the exposure to lateral collision in signalized intersections and discusses the results of a real world experiment. This exposure is defined as the duration of situations where the stream that is given the right-of-way goes through the conflict zone while road users are waiting in the cross-traffic approach. This measure, obtained from video sensors, makes it possible to compare different operating conditions such as different traffic signal strategies. The data from a real world experiment is used, where the adaptive real-time strategy CRONOS (ContRol Of Networks by Optimization of Switchovers) and a time-plan strategy with vehicle-actuated ranges alternately controlled an isolated intersection near Paris. Hourly samples with similar traffic volumes are compared and the exposure to lateral collision is different in various areas of the intersection and various traffic conditions for the two strategies. The total exposure under peak hour traffic conditions drops by roughly 5 min/h with the CRONOS strategy compared to the time-plan strategy, which occurs mostly on entry streams. The results are analyzed through the decomposition of cycles in phase sequences and recommendations are made for traffic control strategies. Copyright © 2011 Elsevier Ltd. All rights reserved.

Two-dimensional priority-based dynamic resource allocation algorithm for QoS in WDM/TDM PON networks

NASA Astrophysics Data System (ADS)

Sun, Yixin; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Zhang, Qi; Rao, Lan

2018-01-01

Wavelength division multiplexing/time division multiplexing (WDM/TDM) passive optical networks (PON) is being viewed as a promising solution for delivering multiple services and applications. The hybrid WDM / TDM PON uses the wavelength and bandwidth allocation strategy to control the distribution of the wavelength channels in the uplink direction, so that it can ensure the high bandwidth requirements of multiple Optical Network Units (ONUs) while improving the wavelength resource utilization. Through the investigation of the presented dynamic bandwidth allocation algorithms, these algorithms can't satisfy the requirements of different levels of service very well while adapting to the structural characteristics of mixed WDM / TDM PON system. This paper introduces a novel wavelength and bandwidth allocation algorithm to efficiently utilize the bandwidth and support QoS (Quality of Service) guarantees in WDM/TDM PON. Two priority based polling subcycles are introduced in order to increase system efficiency and improve system performance. The fixed priority polling subcycle and dynamic priority polling subcycle follow different principles to implement wavelength and bandwidth allocation according to the priority of different levels of service. A simulation was conducted to study the performance of the priority based polling in dynamic resource allocation algorithm in WDM/TDM PON. The results show that the performance of delay-sensitive services is greatly improved without degrading QoS guarantees for other services. Compared with the traditional dynamic bandwidth allocation algorithms, this algorithm can meet bandwidth needs of different priority traffic class, achieve low loss rate performance, and ensure real-time of high priority traffic class in terms of overall traffic on the network.

Scene-Aware Adaptive Updating for Visual Tracking via Correlation Filters

PubMed Central

Zhang, Sirou; Qiao, Xiaoya

2017-01-01

In recent years, visual object tracking has been widely used in military guidance, human-computer interaction, road traffic, scene monitoring and many other fields. The tracking algorithms based on correlation filters have shown good performance in terms of accuracy and tracking speed. However, their performance is not satisfactory in scenes with scale variation, deformation, and occlusion. In this paper, we propose a scene-aware adaptive updating mechanism for visual tracking via a kernel correlation filter (KCF). First, a low complexity scale estimation method is presented, in which the corresponding weight in five scales is employed to determine the final target scale. Then, the adaptive updating mechanism is presented based on the scene-classification. We classify the video scenes as four categories by video content analysis. According to the target scene, we exploit the adaptive updating mechanism to update the kernel correlation filter to improve the robustness of the tracker, especially in scenes with scale variation, deformation, and occlusion. We evaluate our tracker on the CVPR2013 benchmark. The experimental results obtained with the proposed algorithm are improved by 33.3%, 15%, 6%, 21.9% and 19.8% compared to those of the KCF tracker on the scene with scale variation, partial or long-time large-area occlusion, deformation, fast motion and out-of-view. PMID:29140311

An ultra low-power and traffic-adaptive medium access control protocol for wireless body area network.

PubMed

Ullah, Sana; Kwak, Kyung Sup

2012-06-01

Wireless Body Area Network (WBAN) consists of low-power, miniaturized, and autonomous wireless sensor nodes that enable physicians to remotely monitor vital signs of patients and provide real-time feedback with medical diagnosis and consultations. It is the most reliable and cheaper way to take care of patients suffering from chronic diseases such as asthma, diabetes and cardiovascular diseases. Some of the most important attributes of WBAN is low-power consumption and delay. This can be achieved by introducing flexible duty cycling techniques on the energy constraint sensor nodes. Stated otherwise, low duty cycle nodes should not receive frequent synchronization and control packets if they have no data to send/receive. In this paper, we introduce a Traffic-adaptive MAC protocol (TaMAC) by taking into account the traffic information of the sensor nodes. The protocol dynamically adjusts the duty cycle of the sensor nodes according to their traffic-patterns, thus solving the idle listening and overhearing problems. The traffic-patterns of all sensor nodes are organized and maintained by the coordinator. The TaMAC protocol is supported by a wakeup radio that is used to accommodate emergency and on-demand events in a reliable manner. The wakeup radio uses a separate control channel along with the data channel and therefore it has considerably low power consumption requirements. Analytical expressions are derived to analyze and compare the performance of the TaMAC protocol with the well-known beacon-enabled IEEE 802.15.4 MAC, WiseMAC, and SMAC protocols. The analytical derivations are further validated by simulation results. It is shown that the TaMAC protocol outperforms all other protocols in terms of power consumption and delay.

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.

Behavioral Weight Loss Treatment in Antipsychotic Treated Youth.

PubMed

Nicol, Ginger E; Kolko, Rachel P; Mills, Monica; Gunnarsdottir, Thrudur; Yingling, Michael D; Schweiger, Julia A; Lenze, Eric J; Newcomer, John W; Wilfley, Denise

2016-05-01

Antipsychotic-treated youth have increased risk for the development of obesity and type 2 diabetes. Behavioral weight loss treatments show promise in reducing obesity and diabetes risk in antipsychotic treated adults, but have received no study in antipsychotic treated youth. We describe a rationale for behavioral weight loss interventions in high-weight antipsychotic treated youth, and report behavioral, anthropomorphic, and metabolic findings from a case series of obese antipsychotic-treated adolescents participating in a short-term, family-based behavioral weight loss intervention. We adapted the Traffic Light Plan, a 16-week family-based weight loss intervention that promotes healthy energy balance using the colors of the traffic light to categorize the nutritional value of foods and intensity of physical activity, adapting a social ecological framework to address health behavior change in multiple social contexts. The intervention was administered to three obese adolescents with long-term antipsychotic medication exposure. Efficacy of the intervention was evaluated with a battery of anthropomorphic and metabolic assessments including weight, body mass index percentile, whole body adiposity, liver fat content, and fasting plasma glucose and lipids. Participants and their parents also filled out a treatment satisfaction questionnaire upon study completion. Two males and 1 female (all aged 14 years) participated. All 3 participants attended all 16 sessions, and experienced beneficial changes in adiposity, fasting lipids and liver fat content associated with weight stabilization or weight loss. Adolescents and their parents all reported a high level of satisfaction with the treatment. Family-based behavioral weight loss treatment can be feasibly delivered and is acceptable to antipsychotic-treated youth and their families. Randomized controlled trials are needed to fully evaluate the effectiveness and acceptability of behavioral weight loss interventions in antipsychotic treated youth and their families.

Adaptable Assignment

DOT National Transportation Integrated Search

1997-01-01

This paper reports on a practical, simple method for adjusting a vehicle trip table so that the resulting assignments more closely match available traffic counts. "Practical" means that this is not purely a research effort - the procedure described h...

ZeroCal: Automatic MAC Protocol Calibration

NASA Astrophysics Data System (ADS)

Meier, Andreas; Woehrle, Matthias; Zimmerling, Marco; Thiele, Lothar

Sensor network MAC protocols are typically configured for an intended deployment scenario once and for all at compile time. This approach, however, leads to suboptimal performance if the network conditions deviate from the expectations. We present ZeroCal, a distributed algorithm that allows nodes to dynamically adapt to variations in traffic volume. Using ZeroCal, each node autonomously configures its MAC protocol at runtime, thereby trying to reduce the maximum energy consumption among all nodes. While the algorithm is readily usable for any asynchronous low-power listening or low-power probing protocol, we validate and demonstrate the effectiveness of ZeroCal on X-MAC. Extensive testbed experiments and simulations indicate that ZeroCal quickly adapts to traffic variations. We further show that ZeroCal extends network lifetime by 50% compared to an optimal configuration with identical and static MAC parameters at all nodes.

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.

Highly Dynamic and Adaptive Traffic Congestion Avoidance in Real-Time Inspired by Honey Bee Behavior

NASA Astrophysics Data System (ADS)

Wedde, Horst F.; Lehnhoff, Sebastian; van Bonn, Bernhard; Bay, Z.; Becker, S.; Böttcher, S.; Brunner, C.; Büscher, A.; Fürst, T.; Lazarescu, A. M.; Rotaru, E.; Senge, S.; Steinbach, B.; Yilmaz, F.; Zimmermann, T.

Traffic congestions have become a major problem in metropolitan areas world-wide, within and between cities, to an extent where they make driving and transportation times largely unpredictable. Due to the highly dynamic character of congestion building and dissolving this phenomenon appears even to resist a formal treatment. Static approaches, and even more their global management, have proven counterproductive in practice. Given the latest progress in VANET technology and the remarkable commercially driven efforts like in the European C2C consortium, or the VSC Project in the US, allow meanwhile to tackle various aspects of traffic regulation through VANET communication. In this paper we introduce a novel, completely decentralized multi-agent routing algorithm (termed BeeJamA) which we have derived from the foraging behavior of honey bees. It is highly dynamic, adaptive, robust, and scalable, and it allows for both avoiding congestions, and minimizing traveling times to individual destinations. Vehicle guidance is provided well ahead of every intersection, depending on the individual speeds. Thus strict deadlines are imposed on, and respected by, the BeeJamA algorithm. We report on extensive simulation experiments which show the superior performance of BeeJamA over conventional approaches.

MWAHCA: a multimedia wireless ad hoc cluster architecture.

PubMed

Diaz, Juan R; Lloret, Jaime; Jimenez, Jose M; Sendra, Sandra

2014-01-01

Wireless Ad hoc networks provide a flexible and adaptable infrastructure to transport data over a great variety of environments. Recently, real-time audio and video data transmission has been increased due to the appearance of many multimedia applications. One of the major challenges is to ensure the quality of multimedia streams when they have passed through a wireless ad hoc network. It requires adapting the network architecture to the multimedia QoS requirements. In this paper we propose a new architecture to organize and manage cluster-based ad hoc networks in order to provide multimedia streams. Proposed architecture adapts the network wireless topology in order to improve the quality of audio and video transmissions. In order to achieve this goal, the architecture uses some information such as each node's capacity and the QoS parameters (bandwidth, delay, jitter, and packet loss). The architecture splits the network into clusters which are specialized in specific multimedia traffic. The real system performance study provided at the end of the paper will demonstrate the feasibility of the proposal.

Study of Personnel Attrition and Revocation within U.S. Marine Corps Air Traffic Control Specialties

DTIC Science & Technology

2012-03-01

Entrance Processing Stations (MEPS) and recruit depots, to include non-cognitive testing, such as Navy Computer Adaptive Personality Scales ( NCAPS ...Revocation, Selection, MOS, Regression, Probit, dProbit, STATA, Statistics, Marginal Effects, ASVAB, AFQT, Composite Scores, Screening, NCAPS 15. NUMBER...Navy Computer Adaptive Personality Scales ( NCAPS ), during recruitment. It is also recommended that an economic analysis be conducted comparing the

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.

Adaptivity in Agent-Based Routing for Data Networks

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Kirshner, Sergey; Merz, Chris J.; Turner, Kagan

2000-01-01

Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS s) in noisy environments. One important consideration in designing adaptive agents is choosing their action spaces to be as amenable as possible to machine learning techniques, especially to reinforcement learning (RL) techniques. One important way to have the interaction structure connecting agents itself be adaptive is to have the intentions and/or actions of the agents be in the input spaces of the other agents, much as in Stackelberg games. We consider both kinds of adaptivity in the design of a MAS to control network packet routing. We demonstrate on the OPNET event-driven network simulator the perhaps surprising fact that simply changing the action space of the agents to be better suited to RL can result in very large improvements in their potential performance: at their best settings, our learning-amenable router agents achieve throughputs up to three and one half times better than that of the standard Bellman-Ford routing algorithm, even when the Bellman-Ford protocol traffic is maintained. We then demonstrate that much of that potential improvement can be realized by having the agents learn their settings when the agent interaction structure is itself adaptive.

An improved car-following model with multiple preceding cars' velocity fluctuation feedback

NASA Astrophysics Data System (ADS)

Guo, Lantian; Zhao, Xiangmo; Yu, Shaowei; Li, Xiuhai; Shi, Zhongke

2017-04-01

In order to explore and evaluate the effects of velocity variation trend of multiple preceding cars used in the Cooperative Adaptive Cruise Control (CACC) strategy on the dynamic characteristic, fuel economy and emission of the corresponding traffic flow, we conduct a study as follows: firstly, with the real-time car-following (CF) data, the close relationship between multiple preceding cars' velocity fluctuation feedback and the host car's behaviors is explored, the evaluation results clearly show that multiple preceding cars' velocity fluctuation with different time window-width are highly correlated to the host car's acceleration/deceleration. Then, a microscopic traffic flow model is proposed to evaluate the effects of multiple preceding cars' velocity fluctuation feedback in the CACC strategy on the traffic flow evolution process. Finally, numerical simulations on fuel economy and exhaust emission of the traffic flow are also implemented by utilizing VT-micro model. Simulation results prove that considering multiple preceding cars' velocity fluctuation feedback in the control strategy of the CACC system can improve roadway traffic mobility, fuel economy and exhaust emission performance.

76 FR 27743 - Notice of Availability of a Draft Environmental Assessment for a Proposed Airport Traffic Control...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-12

... Environmental Assessment for a Proposed Airport Traffic Control Tower and Base Building, University of Illinois... Availability of a Draft Environmental Assessment for a Proposed Airport Traffic Control Tower and Base Building...) proposes to fund, construct, and operate a new Airport Traffic Control Tower (ATCT) and Base Building at...

Traffic and Driving Simulator Based on Architecture of Interactive Motion.

PubMed

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination.

Traffic and Driving Simulator Based on Architecture of Interactive Motion

PubMed Central

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination. PMID:26491711

Enhanced adaptive signal control using dedicated short-range communications.

DOT National Transportation Integrated Search

2014-05-01

Connected vehicle technology with dedicated short-range communications can provide traffic : information in a spatial domain that conventional fixed-point detectors cannot provide. However, because : of low market penetration with this new data sourc...

A dynamical framework for integrated corridor management.

DOT National Transportation Integrated Search

2016-01-11

We develop analysis and control synthesis tools for dynamic traffic flow over networks. Our analysis : relies on exploiting monotonicity properties of the dynamics, and on adapting relevant tools from : stochastic queuing networks. We develop proport...

Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks.

PubMed

Al-Medhwahi, Mohammed; Hashim, Fazirulhisyam; Ali, Borhanuddin Mohd; Sali, Aduwati

2016-01-01

The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.

Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks

PubMed Central

Ali, Borhanuddin Mohd; Sali, Aduwati

2016-01-01

The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications. PMID:27257964

Impact analysis of traffic-related air pollution based on real-time traffic and basic meteorological information.

PubMed

Pan, Long; Yao, Enjian; Yang, Yang

2016-12-01

With the rapid development of urbanization and motorization in China, traffic-related air pollution has become a major component of air pollution which constantly jeopardizes public health. This study proposes an integrated framework for estimating the concentration of traffic-related air pollution with real-time traffic and basic meteorological information and also for further evaluating the impact of traffic-related air pollution. First, based on the vehicle emission factor models sensitive to traffic status, traffic emissions are calculated according to the real-time link-based average traffic speed, traffic volume, and vehicular fleet composition. Then, based on differences in meteorological conditions, traffic pollution sources are divided into line sources and point sources, and the corresponding methods to determine the dynamic affecting areas are also proposed. Subsequently, with basic meteorological data, Gaussian dispersion model and puff integration model are applied respectively to estimate the concentration of traffic-related air pollution. Finally, the proposed estimating framework is applied to calculate the distribution of CO concentration in the main area of Beijing, and the population exposure is also calculated to evaluate the impact of traffic-related air pollution on public health. Results show that there is a certain correlation between traffic indicators (i.e., traffic speed and traffic intensity) of the affecting area and traffic-related CO concentration of the target grid, which indicates the methods to determine the affecting areas are reliable. Furthermore, the reliability of the proposed estimating framework is verified by comparing the predicted and the observed ambient CO concentration. In addition, results also show that the traffic-related CO concentration is higher in morning and evening peak hours, and has a heavier impact on public health within the Fourth Ring Road of Beijing due to higher population density and higher CO concentration under calm wind condition in this area. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automated Decomposition of Model-based Learning Problems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Millar, Bill

1996-01-01

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

Adaptive Subframe Partitioning and Efficient Packet Scheduling in OFDMA Cellular System with Fixed Decode-and-Forward Relays

NASA Astrophysics Data System (ADS)

Wang, Liping; Ji, Yusheng; Liu, Fuqiang

The integration of multihop relays with orthogonal frequency-division multiple access (OFDMA) cellular infrastructures can meet the growing demands for better coverage and higher throughput. Resource allocation in the OFDMA two-hop relay system is more complex than that in the conventional single-hop OFDMA system. With time division between transmissions from the base station (BS) and those from relay stations (RSs), fixed partitioning of the BS subframe and RS subframes can not adapt to various traffic demands. Moreover, single-hop scheduling algorithms can not be used directly in the two-hop system. Therefore, we propose a semi-distributed algorithm called ASP to adjust the length of every subframe adaptively, and suggest two ways to extend single-hop scheduling algorithms into multihop scenarios: link-based and end-to-end approaches. Simulation results indicate that the ASP algorithm increases system utilization and fairness. The max carrier-to-interference ratio (Max C/I) and proportional fairness (PF) scheduling algorithms extended using the end-to-end approach obtain higher throughput than those using the link-based approach, but at the expense of more overhead for information exchange between the BS and RSs. The resource allocation scheme using ASP and end-to-end PF scheduling achieves a tradeoff between system throughput maximization and fairness.

A Fault Tolerance Mechanism for On-Road Sensor Networks

PubMed Central

Feng, Lei; Guo, Shaoyong; Sun, Jialu; Yu, Peng; Li, Wenjing

2016-01-01

On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%. PMID:27918483

Should I Text or Call Here? A Situation-Based Analysis of Drivers' Perceived Likelihood of Engaging in Mobile Phone Multitasking.

PubMed

Oviedo-Trespalacios, Oscar; Haque, Md Mazharul; King, Mark; Washington, Simon

2018-05-29

This study investigated how situational characteristics typically encountered in the transport system influence drivers' perceived likelihood of engaging in mobile phone multitasking. The impacts of mobile phone tasks, perceived environmental complexity/risk, and drivers' individual differences were evaluated as relevant individual predictors within the behavioral adaptation framework. An innovative questionnaire, which includes randomized textual and visual scenarios, was administered to collect data from a sample of 447 drivers in South East Queensland-Australia (66% females; n = 296). The likelihood of engaging in a mobile phone task across various scenarios was modeled by a random parameters ordered probit model. Results indicated that drivers who are female, are frequent users of phones for texting/answering calls, have less favorable attitudes towards safety, and are highly disinhibited were more likely to report stronger intentions of engaging in mobile phone multitasking. However, more years with a valid driving license, self-efficacy toward self-regulation in demanding traffic conditions and police enforcement, texting tasks, and demanding traffic conditions were negatively related to self-reported likelihood of mobile phone multitasking. The unobserved heterogeneity warned of riskier groups among female drivers and participants who need a lot of convincing to believe that multitasking while driving is dangerous. This research concludes that behavioral adaptation theory is a robust framework explaining self-regulation of distracted drivers. © 2018 Society for Risk Analysis.

Environmentally Reformed Travel Habits During the 2006 Congestion Charge Trial in Stockholm—A Qualitative Study

PubMed Central

Henriksson, Greger; Hagman, Olle; Andréasson, Håkan

2011-01-01

Policy measures that reduce or replace road traffic can improve environmental conditions in most large cities. In Stockholm a congestion charge was introduced during a test period in 2006. This was a full-scale trial that proved to meet its targets by reducing traffic crossing the inner city segment during rush hours by 20%. Emissions of carbon dioxide and particles were also substantially reduced. This study, based on in-depth interviews with 40 inhabitants, analyses how and why new travel habits emerged. The results show that particular, sometimes unexpected, features of everyday life (habits, resources, opportunities, values, etc.) were crucial for adjustment of travel behaviour in relation to the policy instrument. One example was that those accustomed to mixing different modes of transport on a daily basis more easily adapted their travel in the targeted way. On a more general level, the results revealed that the policy measure could actually tip the scales for the individual towards trying out a new behaviour. PMID:21909301

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Designing for flexible interaction between humans and automation: delegation interfaces for supervisory control.

PubMed

Miller, Christopher A; Parasuraman, Raja

2007-02-01

To develop a method enabling human-like, flexible supervisory control via delegation to automation. Real-time supervisory relationships with automation are rarely as flexible as human task delegation to other humans. Flexibility in human-adaptable automation can provide important benefits, including improved situation awareness, more accurate automation usage, more balanced mental workload, increased user acceptance, and improved overall performance. We review problems with static and adaptive (as opposed to "adaptable") automation; contrast these approaches with human-human task delegation, which can mitigate many of the problems; and revise the concept of a "level of automation" as a pattern of task-based roles and authorizations. We argue that delegation requires a shared hierarchical task model between supervisor and subordinates, used to delegate tasks at various levels, and offer instruction on performing them. A prototype implementation called Playbook is described. On the basis of these analyses, we propose methods for supporting human-machine delegation interactions that parallel human-human delegation in important respects. We develop an architecture for machine-based delegation systems based on the metaphor of a sports team's "playbook." Finally, we describe a prototype implementation of this architecture, with an accompanying user interface and usage scenario, for mission planning for uninhabited air vehicles. Delegation offers a viable method for flexible, multilevel human-automation interaction to enhance system performance while maintaining user workload at a manageable level. Most applications of adaptive automation (aviation, air traffic control, robotics, process control, etc.) are potential avenues for the adaptable, delegation approach we advocate. We present an extended example for uninhabited air vehicle mission planning.

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.

Infrared traffic image enhancement algorithm based on dark channel prior and gamma correction

NASA Astrophysics Data System (ADS)

Zheng, Lintao; Shi, Hengliang; Gu, Ming

2017-07-01

The infrared traffic image acquired by the intelligent traffic surveillance equipment has low contrast, little hierarchical differences in perceptions of image and the blurred vision effect. Therefore, infrared traffic image enhancement, being an indispensable key step, is applied to nearly all infrared imaging based traffic engineering applications. In this paper, we propose an infrared traffic image enhancement algorithm that is based on dark channel prior and gamma correction. In existing research dark channel prior, known as a famous image dehazing method, here is used to do infrared image enhancement for the first time. Initially, in the proposed algorithm, the original degraded infrared traffic image is transformed with dark channel prior as the initial enhanced result. A further adjustment based on the gamma curve is needed because initial enhanced result has lower brightness. Comprehensive validation experiments reveal that the proposed algorithm outperforms the current state-of-the-art algorithms.

Preceding Vehicle Detection and Tracking Adaptive to Illumination Variation in Night Traffic Scenes Based on Relevance Analysis

PubMed Central

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-01-01

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation. PMID:25195855

Preceding vehicle detection and tracking adaptive to illumination variation in night traffic scenes based on relevance analysis.

PubMed

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-08-19

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation.

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

NASA Technical Reports Server (NTRS)

Karr, David A.; Vivona, Robert A.; Woods, Sharon E.; Wing, David J.

2017-01-01

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

Video Conferences through the Internet: How to Survive in a Hostile Environment

PubMed Central

Fernández, Carlos; Fernández-Navajas, Julián; Sequeira, Luis; Casadesus, Luis

2014-01-01

This paper analyzes and compares two different video conference solutions, widely used in corporate and home environments, with a special focus on the mechanisms used for adapting the traffic to the network status. The results show how these mechanisms are able to provide a good quality in the hostile environment of the public Internet, a best effort network without delay or delivery guarantees. Both solutions are evaluated in a laboratory, where different network impairments (bandwidth limit, delay, and packet loss) are set, in both the uplink and the downlink, and the reaction of the applications is measured. The tests show how these solutions modify their packet size and interpacket time, in order to increase or reduce the sent data. One of the solutions also uses a scalable video codec, able to adapt the traffic to the network status and to the end devices. PMID:24605066

GIS and RDBMS Used with Offline FAA Airspace Databases

NASA Technical Reports Server (NTRS)

Clark, J.; Simmons, J.; Scofield, E.; Talbott, B.

1994-01-01

A geographic information system (GIS) and relational database management system (RDBMS) were used in a Macintosh environment to access, manipulate, and display off-line FAA databases of airport and navigational aid locations, airways, and airspace boundaries. This proof-of-concept effort used data available from the Adaptation Controlled Environment System (ACES) and Digital Aeronautical Chart Supplement (DACS) databases to allow FAA cartographers and others to create computer-assisted charts and overlays as reference material for air traffic controllers. These products were created on an engineering model of the future GRASP (GRaphics Adaptation Support Position) workstation that will be used to make graphics and text products for the Advanced Automation System (AAS), which will upgrade and replace the current air traffic control system. Techniques developed during the prototyping effort have shown the viability of using databases to create graphical products without the need for an intervening data entry step.

City traffic flow breakdown prediction based on fuzzy rough set

NASA Astrophysics Data System (ADS)

Yang, Xu; Da-wei, Hu; Bing, Su; Duo-jia, Zhang

2017-05-01

In city traffic management, traffic breakdown is a very important issue, which is defined as a speed drop of a certain amount within a dense traffic situation. In order to predict city traffic flow breakdown accurately, in this paper, we propose a novel city traffic flow breakdown prediction algorithm based on fuzzy rough set. Firstly, we illustrate the city traffic flow breakdown problem, in which three definitions are given, that is, 1) Pre-breakdown flow rate, 2) Rate, density, and speed of the traffic flow breakdown, and 3) Duration of the traffic flow breakdown. Moreover, we define a hazard function to represent the probability of the breakdown ending at a given time point. Secondly, as there are many redundant and irrelevant attributes in city flow breakdown prediction, we propose an attribute reduction algorithm using the fuzzy rough set. Thirdly, we discuss how to predict the city traffic flow breakdown based on attribute reduction and SVM classifier. Finally, experiments are conducted by collecting data from I-405 Freeway, which is located at Irvine, California. Experimental results demonstrate that the proposed algorithm is able to achieve lower average error rate of city traffic flow breakdown prediction.

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.

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.

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 Evaluation of Controller and Pilot Performance, Workload and Acceptability under a NextGen Concept for Dynamic Weather Adapted Arrival Routing

NASA Technical Reports Server (NTRS)

Johnson, Walter W.; Lachter, Joel; Brandt, Summer; Koteskey, Robert; Dao, Arik-Quang; Kraut, Josh; Ligda, Sarah; Battiste, Vernol

2012-01-01

In todays terminal operations, controller workload increases and throughput decreases when fixed standard terminal arrival routes (STARs) are impacted by storms. To circumvent this operational constraint, Prete, Krozel, Mitchell, Kim and Zou (2008) proposed to use automation to dynamically adapt arrival and departure routing based on weather predictions. The present study examined this proposal in the context of a NextGen trajectory-based operation concept, focusing on the acceptability and its effect on the controllers ability to manage traffic flows. Six controllers and twelve transport pilots participated in a human-in-the-loop simulation of arrival operations into Louisville International Airport with interval management requirements. Three types of routing structures were used: Static STARs (similar to current routing, which require the trajectories of individual aircraft to be modified to avoid the weather), Dynamic routing (automated adaptive routing around weather), and Dynamic Adjusted routing (automated adaptive routing around weather with aircraft entry time adjusted to account for differences in route length). Spacing Responsibility, whether responsibility for interval management resided with the controllers (as today), or resided with the pilot (who used a flight deck based automated spacing algorithm), was also manipulated. Dynamic routing as a whole was rated superior to static routing, especially by pilots, both in terms of workload reduction and flight path safety. A downside of using dynamic routing was that the paths flown in the dynamic conditions tended to be somewhat longer than the paths flown in the static condition.

Tissue adaptation: Implications for gut immunity and tolerance

PubMed Central

2017-01-01

Tissue adaptation is an intrinsic component of immune cell development, influencing both resistance to pathogens and tolerance. Chronically stimulated surfaces of the body, in particular the gut mucosa, are the major sites where immune cells traffic and reside. Their adaptation to these environments requires constant discrimination between natural stimulation coming from harmless microbiota and food, and pathogens that need to be cleared. This review will focus on the adaptation of lymphocytes to the gut mucosa, a highly specialized environment that can help us understand the plasticity of leukocytes arriving at various tissue sites and how tissue-related factors operate to shape immune cell fate and function. PMID:28432200

PEMNetwork: Barriers and Enablers to Collaboration and Multimedia Education in the Digital Age.

PubMed

Lumba-Brown, Angela; Tat, Sonny; Auerbach, Marc A; Kessler, David O; Alletag, Michelle; Grover, Purva; Schnadower, David; Macias, Charles G; Chang, Todd P

2016-08-01

In January 2005, PEMFellows.com was created to unify fellows in pediatric emergency medicine. Since then, the website has expanded, contracted, and focused to adapt to the interests of the pediatric emergency medicine practitioner during the internet boom. This review details the innovation of the PEMNetwork, from the inception of the initial website and its evolution into a needs-based, user-directed educational hub. Barriers and enablers to success are detailed with unique examples from descriptive analysis and metrics of PEMNetwork web traffic as well as examples from other online medical communities and digital education websites.

Quality of Life, Sleep, and Health of Air Traffic Controllers With Rapid Counterclockwise Shift Rotation.

PubMed

Sonati, Jaqueline Girnos; De Martino, Milva Maria Figueiredo; Vilarta, Roberto; da Silva Maciel, Érika; Sonati, Renato José Ferreira; Paduan, Paulo Cézar

2016-08-01

Rotating shiftwork is common for air traffic controllers and usually causes sleep deprivation, biological adaptations, and life changes for these workers. This study assessed quality of life, the sleep, and the health of 30 air traffic controllers employed at an international airport in Brazil. The objective was to identify health and quality of life concerns of these professionals. The results identified physical inactivity, overweight, excess body fat, low scores for physical and social relationships, and sleep deprivation for workers in all four workshifts. In conclusion, these workers are at risk for chronic non-transmittable diseases and compromised work performance, suggesting the need for more rest time before working nightshifts and work environments that stimulate physical activity and healthy diets. © 2016 The Author(s).

A Wideband Satcom Based Avionics Network with CDMA Uplink and TDM Downlink

NASA Technical Reports Server (NTRS)

Agrawal, D.; Johnson, B. S.; Madhow, U.; Ramchandran, K.; Chun, K. S.

2000-01-01

The purpose of this paper is to describe some key technical ideas behind our vision of a future satcom based digital communication network for avionics applications The key features of our design are as follows: (a) Packetized transmission to permit efficient use of system resources for multimedia traffic; (b) A time division multiplexed (TDM) satellite downlink whose physical layer is designed to operate the satellite link at maximum power efficiency. We show how powerful turbo codes (invented originally for linear modulation) can be used with nonlinear constant envelope modulation, thus permitting the satellite amplifier to operate in a power efficient nonlinear regime; (c) A code division multiple access (CDMA) satellite uplink, which permits efficient access to the satellite from multiple asynchronous users. Closed loop power control is difficult for bursty packetized traffic, especially given the large round trip delay to the satellite. We show how adaptive interference suppression techniques can be used to deal with the ensuing near-far problem; (d) Joint source-channel coding techniques are required both at the physical and the data transport layer to optimize the end-to-end performance. We describe a novel approach to multiple description image encoding at the data transport layer in this paper.

Android-based E-Traffic law enforcement system in Surakarta City

NASA Astrophysics Data System (ADS)

Yulianto, Budi; Setiono

2018-03-01

The urban advancement is always overpowered by the increasing number of vehicles as the need for movement of people and goods. This can lead to traffic problems if there is no effort on the implementation of traffic management and engineering, and traffic law enforcement. In this case, the Government of Surakarta City has implemented various policies and regulations related to traffic management and engineering in order to run traffic in an orderly, safe and comfortable manner according to the applicable law. However, conditions in the field shows that traffic violations still occurred frequently due to the weakness of traffic law enforcement in terms of human resources and the system. In this connection, a tool is needed to support traffic law enforcement, especially in relation to the reporting system of traffic violations. This study aims to develop an Android-based traffic violations reporting application (E-Traffic Law Enforcement) as part of the traffic law enforcement system in Surakarta City. The Android-apps records the location and time of the traffic violations incident along with the visual evidence of the infringement. This information will be connected to the database system to detect offenders and to do the traffic law enforcement process.

A new kind of high durable traffic weighbridge based on FBG sensors

NASA Astrophysics Data System (ADS)

Zhou, Zhi; Liu, Jing; Li, Hui; Ou, Jinping

2005-05-01

Durability is the key problem of traditional traffic weighbridge based on electrical gauges. In this paper, a new kind of high durable traffic weighbridge based on FBG (Fiber Bragg Grating) sensors has been studied and developed. The principle of the smart FBG-weighbridge is based on that the traffic weight can be gotten from the deformation of the reinforced concrete beam with embedded FRP (Fiber Reinforced Polymer) - packaged FBG strain sensors. The FBG-based weighbridge is designed to be a reinforced concrete board supported by composite beams, and the truck load is shared by the composite beams. A 30-ton full scale FBG-based weighbridge has been set up, and the results from the tests and calibration analysis show that this kind of weighbridge features high durability, simplicity, convenience, low cost, etc. This new kind of FBG-based weighbridge shows good prospect in future to replace the traditional traffic weighbridge for long-term monitoring of traffic load.

The Dynamic Planner: The Sequencer, Scheduler, and Runway Allocator for Air Traffic Control Automation

NASA Technical Reports Server (NTRS)

Wong, Gregory L.; Denery, Dallas (Technical Monitor)

2000-01-01

The Dynamic Planner (DP) has been designed, implemented, and integrated into the Center-TRACON Automation System (CTAS) to assist Traffic Management Coordinators (TMCs), in real time, with the task of planning and scheduling arrival traffic approximately 35 to 200 nautical miles from the destination airport. The TMC may input to the DP a series of current and future scheduling constraints that reflect the operation and environmental conditions of the airspace. Under these constraints, the DP uses flight plans, track updates, and Estimated Time of Arrival (ETA) predictions to calculate optimal runway assignments and arrival schedules that help ensure an orderly, efficient, and conflict-free flow of traffic into the terminal area. These runway assignments and schedules can be shown directly to controllers or they can be used by other CTAS tools to generate advisories to the controllers. Additionally, the TMC and controllers may override the decisions made by the DP for tactical considerations. The DP will adapt to computations to accommodate these manual inputs.

Reconfigurable origami sonic barriers with tunable bandgaps for traffic noise mitigation

NASA Astrophysics Data System (ADS)

Thota, M.; Wang, K. W.

2017-10-01

An origami sonic barrier composed of cylindrical inclusions attached onto an origami sheet is proposed. The idea allows for tunable sound blocking properties for application in attenuating complex traffic noise spectra. Folding of the underlying origami sheet transforms the periodicity of the inclusions between different Bravais lattices, viz. between a square and a hexagonal lattice, and such significant lattice re-configuration leads to drastic tuning of dispersion characteristics. The wave tuning capabilities are corroborated via performing theoretical and numerical investigations using a plane wave expansion method and an acoustic simulation package of COMSOL, while experiments are performed on a one-seventh scaled-down model of origami sonic barrier to demonstrate the lattice re-configuration between different Bravais lattices and the associated bandgap adaptability. Good sound blocking performance in the frequency range of traffic noise spectra combined with less efforts, required for actuating one-degree of freedom folding mechanism, makes the origami sonic barrier a potential candidate for mitigating complex traffic noise.

A field study on solar-induced chlorophyll fluorescence and pigment parameters along a vertical canopy gradient of four tree species in an urban environment.

PubMed

Van Wittenberghe, Shari; Alonso, Luis; Verrelst, Jochem; Hermans, Inge; Valcke, Roland; Veroustraete, Frank; Moreno, José; Samson, Roeland

2014-01-01

To better understand the potential uses of vegetation indices based on the sun-induced upward and downward chlorophyll fluorescence at leaf and at canopy scales, a field study was carried out in the city of Valencia (Spain). Fluorescence yield (FY) indices were derived for trees at different traffic intensity locations and at three canopy heights. This allowed investigating within-tree and between-tree variations of FY indices for four tree species. Several FY indices showed a significant (p < 0.05) and important effect of tree location for the species Morus alba (white mulberry) and Phoenix canariensis (Canary Island date palm). The upward FY parameters of M. alba, and the upward to downward ratios at 687 and 741 nm for both species, were significantly related to tree location. It was found that not the total chlorophyll (Chl) content, but rather the Chl a/b ratio showed the strongest correlations with several of the indices applied. Chl a/b was lowest at the bottom level of the highest traffic intensity location for both species due to an increased Chl b, indicating a larger light harvesting complex related to Photosystem II (LHCII) as a response to limiting light. The leaf deposits from traffic observed at this sampling location possibly led to a shading effect, resulting further in an adaptive response of the photosynthetic system and subsequent difference of FY indices. This study therefore indicated the importance of the size of LHCII on the fluorescence emission, observed under different traffic generated pollution conditions. © 2013.

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.

Green cooperative adaptive control systems in the vicinity of signalized intersections.

DOT National Transportation Integrated Search

2014-10-01

Vehicle stops and speed variations account for a large percentage of vehicle fuel losses especially at signalized intersections. : Recently, researchers have attempted to develop tools that reduce these losses by capitalizing on traffic signal inform...

Pedestrian hybrid beacon guide : recommendations and case study.

DOT National Transportation Integrated Search

2014-01-01

A pedestrian hybrid beacon (PHB) is a traffic control : device similar to a European pedestrian signal : (PELICAN) that was imported to the US and adapted by : engineers in Arizona to increase motorists awareness of : pedestrian crossings at uncon...

Dynamic Density: An Air Traffic Management Metric

NASA Technical Reports Server (NTRS)

Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.

1998-01-01

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

enviroCar - citizen science for sustainable traffic

NASA Astrophysics Data System (ADS)

Stasch, Christoph; Remke, Albert; Jirka, Simon; Nuest, Daniel

2015-04-01

Optimizing traffic flow is a challenging task, affecting both the mobility of people and the environment. Up to now, traffic monitoring is based on small samples using GPS devices or remote sensors such as cameras. Citizens are usually not actively involved in the process of collecting or analyzing traffic data. The enviroCar project (www.envirocar.org) aims at addressing this situation by providing an open platform that can be used by everyone to collect and analyze traffic-related data and thus to achieve sustainable traffic management by answering questions such as: How is the average speed on a certain route? Where are exceptionally long waiting times in front of traffic lights? At which crossings do more cars stop than drive through? Where are hotspots of fuel consumption and air pollutant emission during a certain time interval? In this presentation, an overview on the enviroCar project is given and current research challenges addressed in the context of the project are presented. Citizens are able to participate by registering at the enviroCar portal and downloading the enviroCar Android app. Once installed, the Android app allows citizens to collect car sensor data, e.g. speed, mass air flow, or intake temperature via an On-Board Diagnosis 2 (OBD-II) Adapter. After finishing a car ride, the data can be uploaded to the central enviroCar server where the data is anonymized and published as open data. Each enviroCar member has a profile page giving control on his own data and providing statistics on personal driving behavior. The portal also allows comparing personal statistics with the statistics of other members. It thus facilitates analysis whether, for example, a member is driving in a more fuel saving manner than other users. Besides only acting as a data collector, citizens can also explore the enviroCar data in online maps or download the data in standard formats for certain spatial areas and/or time intervals allowing them to conduct spatio-temporal analyses by themselves. Thus, the platform also provides a means to analyze issues, such as repeated stops at a particular traffic light, and to communicate the results to other stakeholders, e.g. traffic planners or politicians. For traffic planners, the enviroCar project can also serve as a valuable additional data source for evaluating certain decisions, e.g. changing traffic light sequences. As not only the pure GPS data but also the car sensor data is collected, enviroCar enables to directly relate the traffic data to environmental parameters such as air pollutant emissions and thus to identify, for example, hotspots of CO2 emissions in a street network. Current research activities comprise technical issues, such as implementing scalable solutions for visualizing and analyzing big data sets, on improving estimation methods for fuel consumption and air pollutant emissions, but also include the development of novel spatio-temporal analysis and visualization methods and novel incentives for participation in crowd-sourcing and analyzing geospatial information.

Multifractal Internet Traffic Model and Active Queue Management

DTIC Science & Technology

2003-01-01

dropped by the Adaptive RED , ssthresh decreases from 64KB to 4KB and the new con- gestion window cwnd is decreased from 8KB to 1KB (Tahoe). The situation...method to predict the queuing behavior of FIFO and RED queues. In order to satisfy a given delay and jitter requirement for real time connections, and to...5.2 Vulnerability of Adaptive RED to Web-mice . . . . . . . . . . . . . 103 5.3 A Parallel Virtual Queues Structure

Adaptation technology between IP layer and optical layer in optical Internet

NASA Astrophysics Data System (ADS)

Ji, Yuefeng; Li, Hua; Sun, Yongmei

2001-10-01

Wavelength division multiplexing (WDM) optical network provides a platform with high bandwidth capacity and is supposed to be the backbone infrastructure supporting the next-generation high-speed multi-service networks (ATM, IP, etc.). In the foreseeable future, IP will be the predominant data traffic, to make fully use of the bandwidth of the WDM optical network, many attentions have been focused on IP over WDM, which has been proposed as the most promising technology for new kind of network, so-called Optical Internet. According to OSI model, IP is in the 3rd layer (network layer) and optical network is in the 1st layer (physical layer), so the key issue is what adaptation technology should be used in the 2nd layer (data link layer). In this paper, firstly, we analyze and compare the current adaptation technologies used in backbone network nowadays. Secondly, aiming at the drawbacks of above technologies, we present a novel adaptation protocol (DONA) between IP layer and optical layer in Optical Internet and describe it in details. Thirdly, the gigabit transmission adapter (GTA) we accomplished based on the novel protocol is described. Finally, we set up an experiment platform to apply and verify the DONA and GTA, the results and conclusions of the experiment are given.

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.

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors.

PubMed

Ma, Xiaolei; Luan, Sen; Du, Bowen; Yu, Bin

2017-09-21

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks.

Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 1. Summary.

DOT National Transportation Integrated Search

1974-02-01

The report contains the results of studies and analyses directed toward the definition of a Satellite-Based Advanced Air Traffic Management System (SAATMS). This system is an advanced, integrated air traffic control system which is based on the use o...

Adaptive MANET multipath routing algorithm based on the simulated annealing approach.

PubMed

Kim, Sungwook

2014-01-01

Mobile ad hoc network represents a system of wireless mobile nodes that can freely and dynamically self-organize network topologies without any preexisting communication infrastructure. Due to characteristics like temporary topology and absence of centralized authority, routing is one of the major issues in ad hoc networks. In this paper, a new multipath routing scheme is proposed by employing simulated annealing approach. The proposed metaheuristic approach can achieve greater and reciprocal advantages in a hostile dynamic real world network situation. Therefore, the proposed routing scheme is a powerful method for finding an effective solution into the conflict mobile ad hoc network routing problem. Simulation results indicate that the proposed paradigm adapts best to the variation of dynamic network situations. The average remaining energy, network throughput, packet loss probability, and traffic load distribution are improved by about 10%, 10%, 5%, and 10%, respectively, more than the existing schemes.

Analysis of Child-related Road Traffic Accidents in Vietnam

NASA Astrophysics Data System (ADS)

Vu, Anh Tuan; Nguyen, Dinh Vinh Man

2018-04-01

In recent years, the number of road traffic accidents, fatalities and injuries have been decreasing, but the figures of children road traffic accidents have been increasing in Ho Chi Minh City of Vietnam. This fact strongly calls for implementing effective solutions to improve traffic safety for children by the local government. This paper presents the trends, patterns and causes of road traffic accidents involving children based on the analysis of road traffic accident data over the period 2010-2015 and the video-based observations of road traffic law violations at 15 typical school gates and 10 typical roads. The results could be useful for the city government to formulate solutions to effectively improve traffic safety for children in Ho Chi Minh City and other cities in Vietnam.

Pilot Study of Instrumentation to Collect Behavioral Data to Identify On-Road Rider Behaviors

DOT National Transportation Integrated Search

2011-04-01

Motorcycle-related research questions of interest to the National Highway Traffic Safety Administration (NHTSA) were reviewed. Instrumentation techniques and study procedures that have been used for light- and heavy-vehicle studies were adapted for u...

Right-\\0xADturn traffic volume adjustment in traffic signal warrant analysis : final report.

DOT National Transportation Integrated Search

2016-05-06

This report was based on the research project, Right-Turn Traffic Volume Adjustment in : Traffic Signal Warrants, sponsored by the Nevada Department of Transportation (NDOT) : and SOLARIS. Right-turn traffic does not affect intersection performance i...

Right-­turn traffic volume adjustment in traffic signal warrant analysis : final report.

DOT National Transportation Integrated Search

2016-05-06

This report was based on the research project, Right-Turn Traffic Volume Adjustment in Traffic Signal Warrants, sponsored by the Nevada Department of Transportation (NDOT) and SOLARIS. Right-turn traffic does not affect intersection performance in th...

Characterization, adaptive traffic shaping, and multiplexing of real-time MPEG II video

NASA Astrophysics Data System (ADS)

Agrawal, Sanjay; Barry, Charles F.; Binnai, Vinay; Kazovsky, Leonid G.

1997-01-01

We obtain network traffic model for real-time MPEG-II encoded digital video by analyzing video stream samples from real-time encoders from NUKO Information Systems. MPEG-II sample streams include a resolution intensive movie, City of Joy, an action intensive movie, Aliens, a luminance intensive (black and white) movie, Road To Utopia, and a chrominance intensive (color) movie, Dick Tracy. From our analysis we obtain a heuristic model for the encoded video traffic which uses a 15-stage Markov process to model the I,B,P frame sequences within a group of pictures (GOP). A jointly-correlated Gaussian process is used to model the individual frame sizes. Scene change arrivals are modeled according to a gamma process. Simulations show that our MPEG-II traffic model generates, I,B,P frame sequences and frame sizes that closely match the sample MPEG-II stream traffic characteristics as they relate to latency and buffer occupancy in network queues. To achieve high multiplexing efficiency we propose a traffic shaping scheme which sets preferred 1-frame generation times among a group of encoders so as to minimize the overall variation in total offered traffic while still allowing the individual encoders to react to scene changes. Simulations show that our scheme results in multiplexing gains of up to 10% enabling us to multiplex twenty 6 Mbps MPEG-II video streams instead of 18 streams over an ATM/SONET OC3 link without latency or cell loss penalty. This scheme is due for a patent.

Birds and anthropogenic noise: are urban songs adaptive?

PubMed

Nemeth, Erwin; Brumm, Henrik

2010-10-01

In cities with intense low-frequency traffic noise, birds have been observed to sing louder and at a higher pitch. Several studies argue that higher song pitch is an adaptation to reduce masking from noise, and it has even been suggested that the song divergence between urban and nonurban songs might lead to reproductive isolation. Here we present models of signal transmission to compare the benefits of raised song amplitude and song pitch in terms of sound transmission. We chose two bird species that sing with higher pitch in urban areas, the great tit (Parus major) and the blackbird (Turdus merula). For both species, we calculated communication distances in response to different levels of urban noise and in their natural forest habitats. We found that an increase in vocal pitch increased communication distance only marginally. In contrast, vocal amplitude adjustments had a strong and significantly larger effect. Our results indicate that frequency changes of urban songs are not very effective in mitigating masking from traffic noise. Increased song pitch might not be an adaptation to reduce signal masking but a physiological side effect of singing at high amplitudes or an epiphenomenon of urbanization that is not related to signal transmission.

5G: rethink mobile communications for 2020+.

PubMed

Chih-Lin, I; Han, Shuangfeng; Xu, Zhikun; Sun, Qi; Pan, Zhengang

2016-03-06

The 5G network is anticipated to meet the challenging requirements of mobile traffic in the 2020s, which are characterized by super high data rate, low latency, high mobility, high energy efficiency and high traffic density. This paper provides an overview of China Mobile's 5G vision and potential solutions. Three key characteristics of 5G are analysed, i.e. super fast, soft and green. The main 5G R&D themes are further elaborated, which include five fundamental rethinkings of the traditional design methodologies. The 5G network design considerations are also discussed, with cloud radio access network, ultra-dense network, software defined network and network function virtualization examined as key potential solutions towards a green and soft 5G network. The paradigm shift to user-centric network operation from the traditional cell-centric operation is also investigated, where the decoupled downlink and uplink, control and data, and adaptive multiple connections provide sufficient means to achieve a user-centric 5G network with 'no more cells'. The software defined air interface is investigated under a uniform framework and can adaptively adapt the parameters to well satisfy various requirements in different 5G scenarios. © 2016 The Author(s).

Bag-of-visual-phrases and hierarchical deep models for traffic sign detection and recognition in mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yu, Yongtao; Li, Jonathan; Wen, Chenglu; Guan, Haiyan; Luo, Huan; Wang, Cheng

2016-03-01

This paper presents a novel algorithm for detection and recognition of traffic signs in mobile laser scanning (MLS) data for intelligent transportation-related applications. The traffic sign detection task is accomplished based on 3-D point clouds by using bag-of-visual-phrases representations; whereas the recognition task is achieved based on 2-D images by using a Gaussian-Bernoulli deep Boltzmann machine-based hierarchical classifier. To exploit high-order feature encodings of feature regions, a deep Boltzmann machine-based feature encoder is constructed. For detecting traffic signs in 3-D point clouds, the proposed algorithm achieves an average recall, precision, quality, and F-score of 0.956, 0.946, 0.907, and 0.951, respectively, on the four selected MLS datasets. For on-image traffic sign recognition, a recognition accuracy of 97.54% is achieved by using the proposed hierarchical classifier. Comparative studies with the existing traffic sign detection and recognition methods demonstrate that our algorithm obtains promising, reliable, and high performance in both detecting traffic signs in 3-D point clouds and recognizing traffic signs on 2-D images.

Programmable bandwidth management in software-defined EPON architecture

NASA Astrophysics Data System (ADS)

Li, Chengjun; Guo, Wei; Wang, Wei; Hu, Weisheng; Xia, Ming

2016-07-01

This paper proposes a software-defined EPON architecture which replaces the hardware-implemented DBA module with reprogrammable DBA module. The DBA module allows pluggable bandwidth allocation algorithms among multiple ONUs adaptive to traffic profiles and network states. We also introduce a bandwidth management scheme executed at the controller to manage the customized DBA algorithms for all date queues of ONUs. Our performance investigation verifies the effectiveness of this new EPON architecture, and numerical results show that software-defined EPONs can achieve less traffic delay and provide better support to service differentiation in comparison with traditional EPONs.

MWAHCA: A Multimedia Wireless Ad Hoc Cluster Architecture

PubMed Central

Diaz, Juan R.; Jimenez, Jose M.; Sendra, Sandra

2014-01-01

Wireless Ad hoc networks provide a flexible and adaptable infrastructure to transport data over a great variety of environments. Recently, real-time audio and video data transmission has been increased due to the appearance of many multimedia applications. One of the major challenges is to ensure the quality of multimedia streams when they have passed through a wireless ad hoc network. It requires adapting the network architecture to the multimedia QoS requirements. In this paper we propose a new architecture to organize and manage cluster-based ad hoc networks in order to provide multimedia streams. Proposed architecture adapts the network wireless topology in order to improve the quality of audio and video transmissions. In order to achieve this goal, the architecture uses some information such as each node's capacity and the QoS parameters (bandwidth, delay, jitter, and packet loss). The architecture splits the network into clusters which are specialized in specific multimedia traffic. The real system performance study provided at the end of the paper will demonstrate the feasibility of the proposal. PMID:24737996

Service differentiated and adaptive CSMA/CA over IEEE 802.15.4 for Cyber-Physical Systems.

PubMed

Xia, Feng; Li, Jie; Hao, Ruonan; Kong, Xiangjie; Gao, Ruixia

2013-01-01

Cyber-Physical Systems (CPS) that collect, exchange, manage information, and coordinate actions are an integral part of the Smart Grid. In addition, Quality of Service (QoS) provisioning in CPS, especially in the wireless sensor/actuator networks, plays an essential role in Smart Grid applications. IEEE 802.15.4, which is one of the most widely used communication protocols in this area, still needs to be improved to meet multiple QoS requirements. This is because IEEE 802.15.4 slotted Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) employs static parameter configuration without supporting differentiated services and network self-adaptivity. To address this issue, this paper proposes a priority-based Service Differentiated and Adaptive CSMA/CA (SDA-CSMA/CA) algorithm to provide differentiated QoS for various Smart Grid applications as well as dynamically initialize backoff exponent according to traffic conditions. Simulation results demonstrate that the proposed SDA-CSMA/CA scheme significantly outperforms the IEEE 802.15.4 slotted CSMA/CA in terms of effective data rate, packet loss rate, and average delay.

Service Differentiated and Adaptive CSMA/CA over IEEE 802.15.4 for Cyber-Physical Systems

PubMed Central

Gao, Ruixia

2013-01-01

Cyber-Physical Systems (CPS) that collect, exchange, manage information, and coordinate actions are an integral part of the Smart Grid. In addition, Quality of Service (QoS) provisioning in CPS, especially in the wireless sensor/actuator networks, plays an essential role in Smart Grid applications. IEEE 802.15.4, which is one of the most widely used communication protocols in this area, still needs to be improved to meet multiple QoS requirements. This is because IEEE 802.15.4 slotted Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) employs static parameter configuration without supporting differentiated services and network self-adaptivity. To address this issue, this paper proposes a priority-based Service Differentiated and Adaptive CSMA/CA (SDA-CSMA/CA) algorithm to provide differentiated QoS for various Smart Grid applications as well as dynamically initialize backoff exponent according to traffic conditions. Simulation results demonstrate that the proposed SDA-CSMA/CA scheme significantly outperforms the IEEE 802.15.4 slotted CSMA/CA in terms of effective data rate, packet loss rate, and average delay. PMID:24260021

Laser diodes for sensing applications: adaptive cruise control and more

NASA Astrophysics Data System (ADS)

Heerlein, Joerg; Morgott, Stefan; Ferstl, Christian

2005-02-01

Adaptive Cruise Controls (ACC) and pre-crash sensors require an intelligent eye which can recognize traffic situations and deliver a 3-dimensional view. Both microwave RADAR and "Light RADAR" (LIDAR) systems are well suited as sensors. In order to utilize the advantages of LIDARs -- such as lower cost, simpler assembly and high reliability -- the key component, the laser diode, is of primary importance. Here, we present laser diodes which meet the requirements of the automotive industry.

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.

Evaluation of the impacts of cooperative adaptive cruise control on reducing rear-end collision risks on freeways.

PubMed

Li, Ye; Wang, Hao; Wang, Wei; Xing, Lu; Liu, Shanwen; Wei, Xueyan

2017-01-01

Although plenty of studies have been conducted recently about the impacts of cooperative adaptive cruise control (CACC) system on traffic efficiency, there are few researches analyzing the safety effects of this advanced driving-assistant system. Thus, the primary objective of this study is to evaluate the impacts of the CACC system on reducing rear-end collision risks on freeways. The CACC model is firstly developed, which is based on the Intelligent Driver Model (IDM). Then, two surrogated safety measures, derived from the time-to-collision (TTC), denoting time exposed time-to-collision (TET) and time integrated time-to-collision (TIT), are introduced for quantifying the collision risks. And the safety effects are analyzed both theoretically and experimentally, by the linear stability analysis and simulations. The theoretical and simulation results conformably indicate that the CACC system brings dramatic benefits for reducing rear-end collision risks (TET and TIT are reduced more than 90%, respectively), when the desired time headway and time delay are set properly. The sensitivity analysis indicates there are few differences among different values of the threshold of TTC and the length of a CACC platoon. The results also show that the safety improvements weaken with the decrease of the penetration rates of CACC on the market and the increase of time delay between platoons. We also evaluate the traffic efficiency of the CACC system with different desired time headway. Copyright © 2016 Elsevier Ltd. All rights reserved.

Innovation as Road Safety Felicitator

NASA Astrophysics Data System (ADS)

Sahoo, S.; Mitra, A.; Kumar, J.; Sahoo, B.

2018-03-01

Transportation via Roads should only be used for safely commuting from one place to another. In 2015, when 1.5 Million people, across the Globe started out on a journey, it was meant to be their last. The Global Status Report on Road Safety, 2015, reflected this data from 180 countries as road traffic deaths, worldwide. In India, more than 1.37 Lakh[4] people were victims of road accidents in 2013 alone. That number is more than the number of Indians killed in all the wars put together. With these disturbing facts in mind, we found out some key ambiguities in the Indian Road Traffic Management systems like the non-adaptive nature to fluctuating traffic, pedestrians and motor vehicles not adhering to the traffic norms strictly, to name a few. Introduction of simple systems would greatly erase the effects of this silent epidemic and our Project aims to achieve the same. It would introduce a pair of Barricade systems to cautiously separate the pedestrians and motor vehicles to minimise road mishaps to the extent possible. Exceptional situations like that of an Ambulance or any emergency vehicles will be taken care off by the use of RFID tags to monitor the movement of the Barricades. The varied traffic scenario can be guided properly by using the ADS-B (Automatic Detection System-Broadcast) for monitoring traffic density according to the time and place.

A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations

DOT National Transportation Integrated Search

2018-01-07

Connected and automated vehicles (CAV) are poised to transform surface transportation systems in the United States. Near-term CAV technologies like cooperative adaptive cruise control (CACC) have the potential to deliver energy efficiency and air qua...

Analysis of corridor delay under SCATS control : FAST-TRAC Phase III deliverable

DOT National Transportation Integrated Search

1998-04-01

The study was designed to determine the change in travel time following the implementation of the Sydney Coordinated Adaptive Traffic System (SCATS) in Oakland County, Michigan. A before/after comparison was used to examine the change in travel time ...

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors

PubMed Central

Ma, Xiaolei; Du, Bowen; Yu, Bin

2017-01-01

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks. PMID:28934164

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

NASA Astrophysics Data System (ADS)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

49 CFR 1139.2 - Traffic study.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 8 2010-10-01 2010-10-01 false Traffic study. 1139.2 Section 1139.2... of General Commodities § 1139.2 Traffic study. (a) The respondents shall submit a traffic study for... “base-calendar year—actual.” The study shall include a probability sampling of the actual traffic...

49 CFR 1139.2 - Traffic study.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 8 2011-10-01 2011-10-01 false Traffic study. 1139.2 Section 1139.2... of General Commodities § 1139.2 Traffic study. (a) The respondents shall submit a traffic study for... “base-calendar year—actual.” The study shall include a probability sampling of the actual traffic...

A novel multisensor traffic state assessment system based on incomplete data.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system. PMID:25162055

A Cognitive Game Theoretic Analysis of Conflict Alerts in Air Traffic Control

NASA Technical Reports Server (NTRS)

Erev, Ido; Gopher, Daniel; Remington, Roger

1999-01-01

The current research was motivated by the recommendation made by a joint Government/Industry committee to introduce a new traffic control system, referred to as the Free Flight. This system is designed to use recent new technology to facilitate efficient and safe air transportation. We addressed one of the major difficulties that arise in the design of this and similar multi-agent systems: the adaptive (and slippery) nature of human agents. To facilitate a safe and efficient design of this multi-agent system, designers have to rely on assessments of the expected behavior of the different agents under various scenarios. Whereas the behavior of the computerized agents is predictable, the behavior of the human agents (including air traffic controllers and pilots) is not. Experimental and empirical observations suggest that human agents are likely to adjust their behavior to the design of the system. To see the difficulty that the adaptive nature of human agents creates assume that a good approximation of the way operators currently behave is available. Given this information an optimal design can be performed. The problem arises as the human operator will learn to adjust their behavior to the new system. Following this adjustment process the assumptions made by the designer concerning the operators behavior will no longer be accurate and the system might reach a suboptimal state. In extreme situations these potential suboptimal states might involve unnecessary risk. That is, the fact that operators learn in an adaptive fashion does not imply that the system will become safer as they gain experience. At least in the context of Safety dilemmas, experience can lead to a pareto deficient risk taking behavior.

Traffic Sign Recognition with Invariance to Lighting in Dual-Focal Active Camera System

NASA Astrophysics Data System (ADS)

Gu, Yanlei; Panahpour Tehrani, Mehrdad; Yendo, Tomohiro; Fujii, Toshiaki; Tanimoto, Masayuki

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

Transparent flexible nanogenerator as self-powered sensor for transportation monitoring

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

Wang, Zhong Lin; Hu, Youfan; Lin, Long

2016-06-14

A traffic sensor includes a flexible substrate having a top surface. A piezoelectric structure extends from the first electrode layer. The piezoelectric structure has a top end. An insulating layer is infused into the piezoelectric structure. A first electrode layer is disposed on top of the insulating layer. A second electrode layer is disposed below the flexible substrate. A packaging layer is disposed around the substrate, the first electrode layer, the piezoelectric structure, the insulating layer and the second electrode layer. In a method of sensing a traffic parameter, a piezoelectric nanostructure-based traffic sensor is applied to a roadway. Anmore » electrical event generated by the piezoelectric nanostructure-based traffic sensor in response to a vehicle interacting with the piezoelectric nanostructure-based traffic sensor is detected. The electrical event is correlated with the traffic parameter.« less

Delay-feedback control strategy for reducing CO2 emission of traffic flow system

NASA Astrophysics Data System (ADS)

Zhang, Li-Dong; Zhu, Wen-Xing

2015-06-01

To study the signal control strategy for reducing traffic emission theoretically, we first presented a kind of discrete traffic flow model with relative speed term based on traditional coupled map car-following model. In the model, the relative speed difference between two successive running cars is incorporated into following vehicle's acceleration running equation. Then we analyzed its stability condition with discrete control system stability theory. Third, we designed a delay-feedback controller to suppress traffic jam and decrease traffic emission based on modern controller theory. Last, numerical simulations are made to support our theoretical results, including the comparison of models' stability analysis, the influence of model type and signal control on CO2 emissions. The results show that the temporal behavior of our model is superior to other models, and the traffic signal controller has good effect on traffic jam suppression and traffic CO2 emission, which fully supports the theoretical conclusions.

Prediction based active ramp metering control strategy with mobility and safety assessment

NASA Astrophysics Data System (ADS)

Fang, Jie; Tu, Lili

2018-04-01

Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

A new smart traffic monitoring method using embedded cement-based piezoelectric sensors

NASA Astrophysics Data System (ADS)

Zhang, Jinrui; Lu, Youyuan; Lu, Zeyu; Liu, Chao; Sun, Guoxing; Li, Zongjin

2015-02-01

Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel’s integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h-1 to 70 km h-1, the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement.

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

PubMed Central

Tang, Haijing; Liang, Yu; Huang, Zhongnan; Wang, Taoyi; He, Lin; Du, Yicong; Ding, Gangyi

2016-01-01

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction. PMID:27872637

ECG on the road: robust and unobtrusive estimation of heart rate.

PubMed

Wartzek, Tobias; Eilebrecht, Benjamin; Lem, Jeroen; Lindner, Hans-Joachim; Leonhardt, Steffen; Walter, Marian

2011-11-01

Modern automobiles include an increasing number of assistance systems to increase the driver's safety. This feasibility study investigated unobtrusive capacitive ECG measurements in an automotive environment. Electrodes integrated into the driving seat allowed to measure a reliable ECG in 86% of the drivers; when only (light) cotton clothing was worn by the drivers, this value increased to 95%. Results show that an array of sensors is needed that can adapt to the different drivers and sitting positions. Measurements while driving show that traveling on the highway does not distort the signal any more than with the car engine turned OFF, whereas driving in city traffic results in a lowered detection rate due to the driver's heavier movements. To enable robust and reliable estimation of heart rate, an algorithm is presented (based on principal component analysis) to detect and discard time intervals with artifacts. This, then, allows a reliable estimation of heart rate of up to 61% in city traffic and up to 86% on the highway: as a percentage of the total driving period with at least four consecutive QRS complexes.

Volatile decision dynamics: experiments, stochastic description, intermittency control and traffic optimization

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Schönhof, Martin; Kern, Daniel

2002-06-01

The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.

A cellular automata traffic flow model for three-phase theory

NASA Astrophysics Data System (ADS)

Qian, Yong-Sheng; Feng, Xiao; Zeng, Jun-Wei

2017-08-01

This paper presents a newly-modified KKW model including the subdivided vehicles types, and introduces the changes for a driver's sensitivity into the speed fluctuation. By means of the numerical simulation the following conclusions are obtained herewith: 1. Velocity disturbance propagation in traffic flow is caused by the speed adaptation among vehicles. 2. In free flow phase, very fewer vehicles are affected by the velocity disturbance and the effect can be dissipated quickly thus the time of disturbance in a single vehicle is quite shorter. On the contrary, the impact duration time of the disturbance on a single vehicle is longer in synchronous flow phase, thus, it will affect more vehicles accordingly. 3. Under the free flow phase, the continuous deceleration behavior of a high speed vehicle to adapt the preceding car with slow speed can cause the reduction of the driver's sensitivity, lead to the vehicle over-deceleration and aggravate the effects of velocity perturbations While in the synchronous flow phase, though the reaction delay caused by the driver's sensitivity reduction can induce speed wave dissolving in essence, it increases the impact of disturbance on the traffic flow. 4. The large acceleration and deceleration tendency of an aggressive driver in the free flow phase always increase the influence of the velocity disturbance, while a conservative driver often weakens the influence. However, in the synchronized flow, since the high traffic density and the synchronization between vehicles is very strong, also the main factor which affects the driver's speed choice is the distance among vehicles, therefore the effect of a driver's behavior tendency to the spread of velocity perturbation is not obvious under this state.

Measuring driver satisfaction with an urban arterial before and after deployment of an adaptive timing signal system

DOT National Transportation Integrated Search

2001-02-01

The Minnesota data system includes the following basic files: Accident data (Accident File, Vehicle File, Occupant File); Roadlog File; Reference Post File; Traffic File; Intersection File; Bridge (Structures) File; and RR Grade Crossing File. For ea...

Passive roadside reflectors and communications systems for improvement of radar reliability

DOT National Transportation Integrated Search

2006-06-01

The use of radar in automotive applications such as adaptive cruise control is limited to detecting : target vehicles directly in front of the host vehicle. Vehicles around a curve on a highway and : cross traffic vehicles at an intersection cannot b...

Developing a Web-Based Advisory Expert System for Implementing Traffic Calming Strategies

PubMed Central

Falamarzi, Amir; Borhan, Muhamad Nazri; Rahmat, Riza Atiq O. K.

2014-01-01

Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and people who seek to employ traffic calming strategies including decision makers, engineers, and students. In order to build the expert system, examining sources related to traffic calming studies as well as interviewing with domain experts have been carried out. The system includes above 150 rules and 200 images for different types of measures. The system has three main functions including classifying traffic calming measures, prioritizing traffic calming strategies, and presenting solutions for different traffic safety problems. Verifying, validating processes, and comparing the system with similar works have shown that the system is consistent and acceptable for practical uses. Finally, some recommendations for improving the system are presented. PMID:25276861

Developing a web-based advisory expert system for implementing traffic calming strategies.

PubMed

Falamarzi, Amir; Borhan, Muhamad Nazri; Rahmat, Riza Atiq O K

2014-01-01

Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and people who seek to employ traffic calming strategies including decision makers, engineers, and students. In order to build the expert system, examining sources related to traffic calming studies as well as interviewing with domain experts have been carried out. The system includes above 150 rules and 200 images for different types of measures. The system has three main functions including classifying traffic calming measures, prioritizing traffic calming strategies, and presenting solutions for different traffic safety problems. Verifying, validating processes, and comparing the system with similar works have shown that the system is consistent and acceptable for practical uses. Finally, some recommendations for improving the system are presented.

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.

Symbols and warrants for major traffic generator guide signing.

DOT National Transportation Integrated Search

2009-09-01

The Texas Manual on Uniform Traffic Control Devices (TMUTCD) provides the definition of regular traffic generators based on four population types but not for major traffic generators (MTGs). MTG signs have been considered to supplement the overall si...

Development of a mobile probe-based traffic data fusion and flow management platform for innovative public-private information-based partnerships.

DOT National Transportation Integrated Search

2011-10-17

"Under the aegis of Intelligent Transportation Systems (ITS), real-time traffic information provision strategies are being proposed to manage traffic congestion, alleviate the effects of incidents, enhance response efficiency after disasters, and imp...

Effects of iterative learning based signal control strategies on macroscopic fundamental diagrams of urban road networks

NASA Astrophysics Data System (ADS)

Yan, Fei; Tian, Fuli; Shi, Zhongke

2016-10-01

Urban traffic flows are inherently repeated on a daily or weekly basis. This repeatability can help improve the traffic conditions if it is used properly by the control system. In this paper, we propose a novel iterative learning control (ILC) strategy for traffic signals of urban road networks using the repeatability feature of traffic flow. To improve the control robustness, the ILC strategy is further integrated with an error feedback control law in a complementary manner. Theoretical analysis indicates that the ILC-based traffic signal control methods can guarantee the asymptotic learning convergence, despite the presence of modeling uncertainties and exogenous disturbances. Finally, the impacts of the ILC-based signal control strategies on the network macroscopic fundamental diagram (MFD) are examined. The results show that the proposed ILC-based control strategies can homogenously distribute the network accumulation by controlling the vehicle numbers in each link to the desired levels under different traffic demands, which can result in the network with high capacity and mobility.

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.

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026

Is vehicle automation enough to prevent crashes? Role of traffic operations in automated driving environments for traffic safety.

PubMed

Jeong, Eunbi; Oh, Cheol; Lee, Seolyoung

2017-07-01

Automated driving systems (ADSs) are expected to prevent traffic accidents caused by driver carelessness on freeways. There is no doubt regarding this safety benefit if all vehicles in the transportation system were equipped with ADSs; however, it is implausible to expect that ADSs will reach 100% market penetration rate (MPR) in the near future. Therefore, the following question arises: 'Can ADSs, which consider only situations in the vicinity of an equipped vehicle, really contribute to a significant reduction in traffic accidents?' To address this issue, the interactions between equipped and unequipped vehicles must be investigated, which is the purpose of this study. This study evaluated traffic safety at different MPRs based on a proposed index to represent the overall rear-end crash risk of the traffic stream. Two approaches were evaluated for adjusting longitudinal vehicle maneuvers: vehicle safety-based maneuvering (VSM), which considers the crash risk of an equipped vehicle and its neighboring vehicles, and traffic safety-based maneuvering (TSM), which considers the overall crash risk in the traffic stream. TSM assumes that traffic operational agencies are able to monitor all the vehicles and to intervene in vehicle maneuvering. An optimization process, which attempts to obtain vehicle maneuvering control parameters to minimize the overall crash risk, is integrated into the proposed evaluation framework. The main purpose of employing the optimization process for vehicle maneuvering in this study is to identify opportunities to improve traffic safety through effective traffic management rather than developing a vehicle control algorithm that can be implemented in practice. The microscopic traffic simulator VISSIM was used to simulate the freeway traffic stream and to conduct systematic evaluations based on the proposed methodology. Both TSM and VSM achieved significant reductions in the potential for rear-end crashes. However, TSM obtained much greater reductions when the MPR was greater than 50%. This study should inspire transportation researchers and engineers to develop effective traffic operations strategies for automated driving environments. Copyright © 2017. Published by Elsevier Ltd.

The importance of antipersistence for traffic jams

NASA Astrophysics Data System (ADS)

Krause, Sebastian M.; Habel, Lars; Guhr, Thomas; Schreckenberg, Michael

2017-05-01

Universal characteristics of road networks and traffic patterns can help to forecast and control traffic congestion. The antipersistence of traffic flow time series has been found for many data sets, but its relevance for congestion has been overseen. Based on empirical data from motorways in Germany, we study how antipersistence of traffic flow time-series impacts the duration of traffic congestion on a wide range of time scales. We find a large number of short-lasting traffic jams, which implies a large risk for rear-end collisions.

Data-Link and Surface Map Traffic Intent Displays for NextGen 4DT and Equivalent Visual Surface Operations

NASA Technical Reports Server (NTRS)

Shelton, Kevin J.; Prinzel, Lawrence J., III; Arthur, Jarvis J., III; Jones, Deise R.; Allamandola, Angela S.; Bailey, Randall E.

2009-01-01

By 2025, U.S. air traffic is predicted to increase 3-fold and may strain the current air traffic management system, which may not be able to accommodate this growth. In response to this challenge, a consortium of industry, academia and government agencies have proposed a revolutionary new concept for U.S. aviation operations, termed the Next Generation Air Transportation System or "NextGen". Many key capabilities are being identified to enable NextGen, including the concept of "net-centric" operations whereby each aircraft and air services provider shares information to allow real-time adaptability to ever-changing factors such as weather, traffic, flight trajectories, and security. Data-link is likely to be the primary source of communication in NextGen. Because NextGen represents a radically different approach to air traffic management and requires a dramatic shift in the tasks, roles, and responsibilities for the flight deck, there are numerous research issues and challenges that must be overcome to ensure a safe, sustainable air transportation system. Flight deck display and crew-vehicle interaction concepts are being developed that proactively investigate and overcome potential technology and safety barriers that might otherwise constrain the full realization of NextGen.

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.

Supporting Beacon and Event-Driven Messages in Vehicular Platoons through Token-Based Strategies

PubMed Central

Uhlemann, Elisabeth

2018-01-01

Timely and reliable inter-vehicle communications is a critical requirement to support traffic safety applications, such as vehicle platooning. Furthermore, low-delay communications allow the platoon to react quickly to unexpected events. In this scope, having a predictable and highly effective medium access control (MAC) method is of utmost importance. However, the currently available IEEE 802.11p technology is unable to adequately address these challenges. In this paper, we propose a MAC method especially adapted to platoons, able to transmit beacons within the required time constraints, but with a higher reliability level than IEEE 802.11p, while concurrently enabling efficient dissemination of event-driven messages. The protocol circulates the token within the platoon not in a round-robin fashion, but based on beacon data age, i.e., the time that has passed since the previous collection of status information, thereby automatically offering repeated beacon transmission opportunities for increased reliability. In addition, we propose three different methods for supporting event-driven messages co-existing with beacons. Analysis and simulation results in single and multi-hop scenarios showed that, by providing non-competitive channel access and frequent retransmission opportunities, our protocol can offer beacon delivery within one beacon generation interval while fulfilling the requirements on low-delay dissemination of event-driven messages for traffic safety applications. PMID:29570676

Supporting Beacon and Event-Driven Messages in Vehicular Platoons through Token-Based Strategies.

PubMed

Balador, Ali; Uhlemann, Elisabeth; Calafate, Carlos T; Cano, Juan-Carlos

2018-03-23

Timely and reliable inter-vehicle communications is a critical requirement to support traffic safety applications, such as vehicle platooning. Furthermore, low-delay communications allow the platoon to react quickly to unexpected events. In this scope, having a predictable and highly effective medium access control (MAC) method is of utmost importance. However, the currently available IEEE 802.11p technology is unable to adequately address these challenges. In this paper, we propose a MAC method especially adapted to platoons, able to transmit beacons within the required time constraints, but with a higher reliability level than IEEE 802.11p, while concurrently enabling efficient dissemination of event-driven messages. The protocol circulates the token within the platoon not in a round-robin fashion, but based on beacon data age, i.e., the time that has passed since the previous collection of status information, thereby automatically offering repeated beacon transmission opportunities for increased reliability. In addition, we propose three different methods for supporting event-driven messages co-existing with beacons. Analysis and simulation results in single and multi-hop scenarios showed that, by providing non-competitive channel access and frequent retransmission opportunities, our protocol can offer beacon delivery within one beacon generation interval while fulfilling the requirements on low-delay dissemination of event-driven messages for traffic safety applications.

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors

PubMed Central

Desai, Prajakta; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies. PMID:28792513

Cooperative vehicles for robust traffic congestion reduction: An analysis based on algorithmic, environmental and agent behavioral factors.

PubMed

Desai, Prajakta; Loke, Seng W; Desai, Aniruddha

2017-01-01

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

Signal treatments to reduce heavy vehicle crash-risk at metropolitan highway intersections.

PubMed

Archer, Jeffery; Young, William

2009-05-01

Heavy vehicle red-light running at intersections is a common safety problem that has severe consequences. This paper investigates alternative signal treatments that address this issue. A micro-simulation analysis approach was adopted as a precursor to a field trial. The simulation model emulated traffic conditions at a known problem intersection and provided a baseline measure to compare the effects of: an extension of amber time; an extension of green for heavy vehicles detected in the dilemma zone at the onset of amber; an extension of the all-red safety-clearance time based on the detection of vehicles considered likely to run the red light at two detector locations during amber; an extension of the all-red safety-clearance time based on the detection of potential red-light runners during amber or red; and a combination of the second and fourth alternatives. Results suggested safety improvements for all treatments. An extension of amber provided the best safety effect but is known to be prone to behavioural adaptation effects and wastes traffic movement time unnecessarily. A green extension for heavy vehicles detected in the dilemma zone and an all-red extension for potential red-light runners were deemed to provide a sustainable safety improvement and operational efficiency.

The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

NASA Technical Reports Server (NTRS)

Ansari, Nirwan; Liu, Dequan

1991-01-01

A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

CytoViz: an artistic mapping of network measurements as living organisms in a VR application

NASA Astrophysics Data System (ADS)

López Silva, Brenda A.; Renambot, Luc

2007-02-01

CytoViz is an artistic, real-time information visualization driven by statistical information gathered during gigabit network transfers to the Scalable Adaptive Graphical Environment (SAGE) at various events. Data streams are mapped to cellular organisms defining their structure and behavior as autonomous agents. Network bandwidth drives the growth of each entity and the latency defines its physics-based independent movements. The collection of entity is bound within the 3D representation of the local venue. This visual and animated metaphor allows the public to experience the complexity of high-speed network streams that are used in the scientific community. Moreover, CytoViz displays the presence of discoverable Bluetooth devices carried by nearby persons. The concept is to generate an event-specific, real-time visualization that creates informational 3D patterns based on actual local presence. The observed Bluetooth traffic is put in opposition of the wide-area networking traffic by overlaying 2D animations on top of the 3D world. Each device is mapped to an animation fading over time while displaying the name of the detected device and its unique physical address. CytoViz was publicly presented at two major international conferences in 2005 (iGrid2005 in San Diego, CA and SC05 in Seattle, WA).

Evaluation of traffic responsive control on the Reston Parkway arterial network.

DOT National Transportation Integrated Search

2009-01-01

Traffic responsive plan selection (TRPS) control is considered an effective operational mode in traffic signal systems. Its efficiency stems from the fact that it can capture variations in traffic patterns and switch timing plans based on existing tr...

Balloon-borne air traffic management (ATM) as a precursor to space-based ATM

NASA Astrophysics Data System (ADS)

Brodsky, Yuval; Rieber, Richard; Nordheim, Tom

2012-01-01

The International Space University—Balloon Air traffic control Technology Experiment (I-BATE ) has flown on board two stratospheric balloons and has tracked nearby aircraft by receiving their Automatic Dependent Surveillance-Broadcast (ADS-B) transmissions. Air traffic worldwide is facing increasing congestion. It is predicted that daily European flight volumes will more than double by 2030 compared to 2009 volumes. ADS-B is an air traffic management system being used to mitigate air traffic congestion. Each aircraft is equipped with both a GPS receiver and an ADS-B transponder. The transponder transmits an equipped aircraft's unique identifier, position, heading, and velocity once per second. The ADS-B transmissions can then be received by ground stations for use in traditional air traffic management. Airspace not monitored by these ground stations or other traditional means remains uncontrolled and poorly monitored. A constellation of space-based ADS-B receivers could close these gaps and provide global air traffic monitoring. By flying an ADS-B receiver on a stratospheric balloon, I-BATE has served as a precursor to a constellation of ADS-B-equipped Earth-orbiting satellites. From the ˜30 km balloon altitude, I-BATE tracked aircraft ranging up to 850 km. The experiment has served as a proof of concept for space-based air traffic management and supports a technology readiness level 6 of space-based ADS-B reception. I-BATE: International Space University—Balloon Air traffic control Technology Experiment.

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs.

PubMed

Aslam, Muhammad; Hu, Xiaopeng; Wang, Fan

2017-12-13

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR's routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols.

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs

PubMed Central

Hu, Xiaopeng; Wang, Fan

2017-01-01

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR’s routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols. PMID:29236031

The burden of road traffic injuries in Nigeria: results of a population-based survey.

PubMed

Labinjo, M; Juillard, C; Kobusingye, O C; Hyder, A A

2009-06-01

Mortality from road traffic injuries in sub-Saharan Africa is among the highest in the world, yet data from the region are sparse. To date, no multi-site population-based survey on road traffic injuries has been reported from Nigeria, the most populated country in Africa. To explore the epidemiology of road traffic injury in Nigeria and provide data on the populations affected and risk factors for road traffic injury. Data from a population-based survey using two-stage stratified cluster sampling. SUBJECTS/ SETTING: Road traffic injury status and demographic information were collected on 3082 respondents living in 553 households in seven of Nigeria's 37 states. Incidence rates were estimated with confidence intervals based on a Poisson distribution; Poisson regression analysis was used to calculate relative risks for associated factors. The overall road traffic injury rate was 41 per 1000 population (95% CI 34 to 49), and mortality from road traffic injuries was 1.6 per 1000 population (95% CI 0.5 to 3.8). Motorcycle crashes accounted for 54% of all road traffic injuries. The road traffic injury rates found for rural and urban respondents were not significantly different. Increased risk of injury was associated with male gender among those aged 18-44 years, with a relative risk of 2.96 when compared with women in the same age range (95% CI 1.72 to 5.09, p<0.001). The road traffic injury rates found in this survey highlight a neglected public health problem in Nigeria. Simple extrapolations from this survey suggest that over 4 million people may be injured and as many as 200 000 potentially killed as the result of road traffic crashes annually in Nigeria. Appropriate interventions in both the health and transport sectors are needed to address this significant cause of morbidity and mortality in Nigeria.

Intelligent Traffic Light Based on PLC Control

NASA Astrophysics Data System (ADS)

Mei, Lin; Zhang, Lijian; Wang, Lingling

2017-11-01

The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

Virtual Induction Loops Based on Cooperative Vehicular Communications

PubMed Central

Gramaglia, Marco; Bernardos, Carlos J.; Calderon, Maria

2013-01-01

Induction loop detectors have become the most utilized sensors in traffic management systems. The gathered traffic data is used to improve traffic efficiency (i.e., warning users about congested areas or planning new infrastructures). Despite their usefulness, their deployment and maintenance costs are expensive. Vehicular networks are an emerging technology that can support novel strategies for ubiquitous and more cost-effective traffic data gathering. In this article, we propose and evaluate VIL (Virtual Induction Loop), a simple and lightweight traffic monitoring system based on cooperative vehicular communications. The proposed solution has been experimentally evaluated through simulation using real vehicular traces. PMID:23348033

Simulation and analysis of traffic flow based on cellular automaton

NASA Astrophysics Data System (ADS)

Ren, Xianping; Liu, Xia

2018-03-01

In this paper, single-lane and two-lane traffic model are established based on cellular automaton. Different values of vehicle arrival rate at the entrance and vehicle departure rate at the exit are set to analyze their effects on density, average speed and traffic flow. If the road exit is unblocked, vehicles can pass through the road smoothly despite of the arrival rate at the entrance. If vehicles enter into the road continuously, the traffic condition is varied with the departure rate at the exit. To avoid traffic jam, reasonable vehicle departure rate should be adopted.

Traffic speed data imputation method based on tensor completion.

PubMed

Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

Traffic Speed Data Imputation Method Based on Tensor Completion

PubMed Central

Ran, Bin; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches. PMID:25866501

[Definition of hospital discharge, serious injury and death from traffic injuries].

PubMed

Pérez, Katherine; Seguí-Gómez, María; Arrufat, Vita; Barberia, Eneko; Cabeza, Elena; Cirera, Eva; Gil, Mercedes; Martín, Carlos; Novoa, Ana M; Olabarría, Marta; Lardelli, Pablo; Suelves, Josep Maria; Santamariña-Rubio, Elena

2014-01-01

Road traffic injury surveillance involves methodological difficulties due, among other reasons, to the lack of consensus criteria for case definition. Police records have usually been the main source of information for monitoring traffic injuries, while health system data has hardly been used. Police records usually include comprehensive information on the characteristics of the crash, but often underreport injury cases and do not collect reliable information on the severity of injuries. However, statistics on severe traffic injuries have been based almost exclusively on police data. The aim of this paper is to propose criteria based on medical records to define: a) "Hospital discharge for traffic injuries", b) "Person with severe traffic injury", and c) "Death from traffic injuries" in order to homogenize the use of these sources. Copyright © 2014. Published by Elsevier Espana.

A Turn-Projected State-Based Conflict Resolution Algorithm

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Lewis, Timothy A.

2013-01-01

State-based conflict detection and resolution (CD&R) algorithms detect conflicts and resolve them on the basis on current state information without the use of additional intent information from aircraft flight plans. Therefore, the prediction of the trajectory of aircraft is based solely upon the position and velocity vectors of the traffic aircraft. Most CD&R algorithms project the traffic state using only the current state vectors. However, the past state vectors can be used to make a better prediction of the future trajectory of the traffic aircraft. This paper explores the idea of using past state vectors to detect traffic turns and resolve conflicts caused by these turns using a non-linear projection of the traffic state. A new algorithm based on this idea is presented and validated using a fast-time simulator developed for this study.

Adapting risk management and computational intelligence network optimization techniques to improve traffic throughput and tail risk analysis.

DOT National Transportation Integrated Search

2014-04-01

Risk management techniques are used to analyze fluctuations in uncontrollable variables and keep those fluctuations from impeding : the core function of a system or business. Examples of this are making sure that volatility in copper and aluminum pri...

Automated feedback to foster safe driving in young drivers: phase 2 : traffic tech.

DOT National Transportation Integrated Search

2015-12-01

Intelligent Speed Adaptation (ISA) provides a promising approach to reduce speeding. A core principle of ISA is real-time feedback that lets drivers know when they are driving over the speed limit. The overall goal of the study was to provide insight...

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

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

Analysis of Malicious Traffic in Modbus/TCP Communications

NASA Astrophysics Data System (ADS)

Kobayashi, Tiago H.; Batista, Aguinaldo B.; Medeiros, João Paulo S.; Filho, José Macedo F.; Brito, Agostinho M.; Pires, Paulo S. Motta

This paper presents the results of our analysis about the influence of Information Technology (IT) malicious traffic on an IP-based automation environment. We utilized a traffic generator, called MACE (Malicious trAffic Composition Environment), to inject malicious traffic in a Modbus/TCP communication system and a sniffer to capture and analyze network traffic. The realized tests show that malicious traffic represents a serious risk to critical information infrastructures. We show that this kind of traffic can increase latency of Modbus/TCP communication and that, in some cases, can put Modbus/TCP devices out of communication.

Comparison Between Three Different Types of Routing Algorithms of Network on Chip

NASA Astrophysics Data System (ADS)

Soni, Neetu; Deshmukh, Khemraj

Network on Chip (NoC) is an on-chip communication technology in which a large number of processing elements and storage blocks are integrated on a single chip. Due to scalability, adaptive nature, well resource utilization NoCs have become popular in and has efficiently replaced SoCs. NoCs performance depends mainly on the type of routing algorithm chosen. In this paper three different types of routing algorithms are being compared firstly one is deterministic routing (XY routing algorithm), secondly three partially adaptive routing (West-first, North-last and Negative-first) and two adaptive routing (DyAD, OE) are being compared with respect to Packet Injection Rate (PIR) of load for random traffic pattern for 4 × 4 mesh topology. All these comparison and simulation is done in NOXIM 2.3.1 simulator which is a cycle accurate systemC based simulator. The distribution of packets is Poisson type with Buffer depth (number of buffers) of input channel FIFO is 8. Packet size is taken as 8 bytes. The simulation time is taken 50,000 cycles. We found that XY routing is better when the PIR is low. The partially adaptive routing is good when the PIR is moderate. DyAD routing is suited when the load i.e. PIR is high.

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.

Spectrum efficient distance-adaptive paths for fixed and fixed-alternate routing in elastic optical networks

NASA Astrophysics Data System (ADS)

Agrawal, Anuj; Bhatia, Vimal; Prakash, Shashi

2018-01-01

Efficient utilization of spectrum is a key concern in the soon to be deployed elastic optical networks (EONs). To perform routing in EONs, various fixed routing (FR), and fixed-alternate routing (FAR) schemes are ubiquitously used. FR, and FAR schemes calculate a fixed route, and a prioritized list of a number of alternate routes, respectively, between different pairs of origin o and target t nodes in the network. The route calculation performed using FR and FAR schemes is predominantly based on either the physical distance, known as k -shortest paths (KSP), or on the hop count (HC). For survivable optical networks, FAR usually calculates link-disjoint (LD) paths. These conventional routing schemes have been efficiently used for decades in communication networks. However, in this paper, it has been demonstrated that these commonly used routing schemes cannot utilize the network spectral resources optimally in the newly introduced EONs. Thus, we propose a new routing scheme for EON, namely, k -distance adaptive paths (KDAP) that efficiently utilizes the benefit of distance-adaptive modulation, and bit rate-adaptive superchannel capability inherited by EON to improve spectrum utilization. In the proposed KDAP, routes are found and prioritized on the basis of bit rate, distance, spectrum granularity, and the number of links used for a particular route. To evaluate the performance of KSP, HC, LD, and the proposed KDAP, simulations have been performed for three different sized networks, namely, 7-node test network (TEST7), NSFNET, and 24-node US backbone network (UBN24). We comprehensively assess the performance of various conventional, and the proposed routing schemes by solving both the RSA and the dual RSA problems under homogeneous and heterogeneous traffic requirements. Simulation results demonstrate that there is a variation amongst the performance of KSP, HC, and LD, depending on the o - t pair, and the network topology and its connectivity. However, the proposed KDAP always performs better for all the considered networks and traffic scenarios, as compared to the conventional routing schemes, namely, KSP, HC, and LD. The proposed KDAP achieves up to 60 % , and 10.46 % improvement in terms of spectrum utilization, and resource utilization ratio, respectively, over the conventional routing schemes.

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

NASA Technical Reports Server (NTRS)

Drew, Michael; Sheth, Kapil

2015-01-01

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

Active Traffic Management: Comprehension, Legibility, Distance, and Motorist Behavior In Response to Selected Variable Speed Limit and Lane Control Signing

DOT National Transportation Integrated Search

2016-06-01

Active traffic management (ATM) incorporates a collection of strategies allowing the dynamic management of recurrent and nonrecurrent congestion based on prevailing traffic conditions. These strategies help to increase peak capacity, smooth traffic f...

Remotely Accessed Vehicle Traffic Management System

NASA Astrophysics Data System (ADS)

Al-Alawi, Raida

2010-06-01

The ever increasing number of vehicles in most metropolitan cities around the world and the limitation in altering the transportation infrastructure, led to serious traffic congestion and an increase in the travelling time. In this work we exploit the emergence of novel technologies such as the internet, to design an intelligent Traffic Management System (TMS) that can remotely monitor and control a network of traffic light controllers located at different sites. The system is based on utilizing Embedded Web Servers (EWS) technology to design a web-based TMS. The EWS located at each intersection uses IP technology for communicating remotely with a Central Traffic Management Unit (CTMU) located at the traffic department authority. Friendly GUI software installed at the CTMU will be able to monitor the sequence of operation of the traffic lights and the presence of traffic at each intersection as well as remotely controlling the operation of the signals. The system has been validated by constructing a prototype that resembles the real application.

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 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

Actual situation analyses of rat-run traffic on community streets based on car probe data

NASA Astrophysics Data System (ADS)

Sakuragi, Yuki; Matsuo, Kojiro; Sugiki, Nao

2017-10-01

Lowering of so-called "rat-run" traffic on community streets has been one of significant challenges for improving the living environment of neighborhood. However, it has been difficult to quantitatively grasp the actual situation of rat-run traffic by the traditional surveys such as point observations. This study aims to develop a method for extracting rat-run traffic based on car probe data. In addition, based on the extracted rat-run traffic in Toyohashi city, Japan, we try to analyze the actual situation such as time and location distribution of the rat-run traffic. As a result, in Toyohashi city, the rate of using rat-run route increases in peak time period. Focusing on the location distribution of rat-run traffic, in addition, they pass through a variety of community streets. There is no great inter-district bias of the route frequently used as rat-run traffic. Next, we focused on some trips passing through a heavily used route as rat-run traffic. As a result, we found the possibility that they habitually use the route as rat-run because their trips had some commonalities. We also found that they tend to use the rat-run route due to shorter distance than using the alternative highway route, and that the travel speeds were faster than using the alternative highway route. In conclusions, we confirmed that the proposed method can quantitatively grasp the actual situation and the phenomenal tendencies of the rat-run traffic.

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.

You...Alcohol and Driving.

ERIC Educational Resources Information Center

American Automobile Association, Falls Church, VA. Traffic Engineering and Safety Dept.

This pamphlet is an example of cooperation between the private sector (AAA) and the National Highway Traffic Safety Administration. AAA has adapted materials prepared by the National Public Service Research Institute under an NHTSA contract and developed a 54-page student manual. The manual takes a complete and objective look at drinking and…

An adaptive corridor-wide signal timing optimization methodology for traffic network with multiple highway-rail grade crossings.

DOT National Transportation Integrated Search

2016-06-01

Highway-rail grade crossings (HRGCs) and the intersections in their proximity are areas where potential problems in terms of safety and efficiency often arise if only simple or outdated treatments, such as normal signal timing or passive railroad war...

Traffic Flow Density Distribution Based on FEM

NASA Astrophysics Data System (ADS)

Ma, Jing; Cui, Jianming

In analysis of normal traffic flow, it usually uses the static or dynamic model to numerical analyze based on fluid mechanics. However, in such handling process, the problem of massive modeling and data handling exist, and the accuracy is not high. Finite Element Method (FEM) is a production which is developed from the combination of a modern mathematics, mathematics and computer technology, and it has been widely applied in various domain such as engineering. Based on existing theory of traffic flow, ITS and the development of FEM, a simulation theory of the FEM that solves the problems existing in traffic flow is put forward. Based on this theory, using the existing Finite Element Analysis (FEA) software, the traffic flow is simulated analyzed with fluid mechanics and the dynamics. Massive data processing problem of manually modeling and numerical analysis is solved, and the authenticity of simulation is enhanced.

The Impact of Trajectory Prediction Uncertainty on Air Traffic Controller Performance and Acceptability

NASA Technical Reports Server (NTRS)

Mercer, Joey S.; Bienert, Nancy; Gomez, Ashley; Hunt, Sarah; Kraut, Joshua; Martin, Lynne; Morey, Susan; Green, Steven M.; Prevot, Thomas; Wu, Minghong G.

2013-01-01

A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decision-support tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automations ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.

Development of the Oregon traffic safety data archive : phases 1 and 2.

DOT National Transportation Integrated Search

2012-03-01

"This report describes the preliminary work to develop the Oregon Traffic Safety Data Archive (OrTSDA). The mission of OrTSDA is to build : the knowledge base of traffic safety data in Oregon. The archive hopes to become a valuable traffic safe...

Development of minimum standards for event-based data collection loggers and performance measure definitions for signalized intersections [summary].

DOT National Transportation Integrated Search

2017-01-01

New traffic signal controllers, which have advanced data collection abilities, offer better information about the response of traffic signal timings to traffic flows. However, traffic engineers need more than raw data. The controllers must be set up ...

Estimating AADT from combined air photos and ground based data : system design, prototyping, and testing.

DOT National Transportation Integrated Search

2009-09-15

Average annual daily traffic (AADT) is perhaps the most fundamental measure of traffic flow. The data used to produce AADT estimates are largely collected by in-highway traffic counters operated by traffic monitoring crews who must cover thousands of...

Design and Operational Evaluation of the Traffic Management Advisor at the Fort Worth Air Route Traffic Control Center

DOT National Transportation Integrated Search

1997-06-19

NASA and the Federal Aviation Administration (FAA) have designed and developed an automation tool known as the Traffic Management Advisor (TMA). The TMA is a time-based strategic planning tool that provides Traffic Management Coordinators (TMCs) and ...

An assessment of traffic safety culture related to engagement efforts to improve traffic safety : research programs.

DOT National Transportation Integrated Search

2016-12-01

The Center for Health and Safety Culture at Montana State University developed a survey to investigate the traffic safety culture related to engagement in traffic safety citizenship behaviors. The development of the survey was based on an augmented f...

Development of a model performance-based sign sheeting specification based on the evaluation of nighttime traffic signs using legibility and eye-tracker data.

DOT National Transportation Integrated Search

2010-09-01

This project focused on the evaluation of traffic sign sheeting performance in terms of meeting the nighttime : driver needs. The goal was to develop a nighttime driver needs specification for traffic signs. The : researchers used nighttime sign legi...

Manycast routing, modulation level and spectrum assignment over elastic optical networks

NASA Astrophysics Data System (ADS)

Luo, Xiao; Zhao, Yang; Chen, Xue; Wang, Lei; Zhang, Min; Zhang, Jie; Ji, Yuefeng; Wang, Huitao; Wang, Taili

2017-07-01

Manycast is a point to multi-point transmission framework that requires a subset of destination nodes successfully reached. It is particularly applicable for dealing with large amounts of data simultaneously in bandwidth-hungry, dynamic and cloud-based applications. As rapid increasing of traffics in these applications, the elastic optical networks (EONs) may be relied on to achieve high throughput manycast. In terms of finer spectrum granularity, the EONs could reach flexible accessing to network spectrum and efficient providing exact spectrum resource to demands. In this paper, we focus on the manycast routing, modulation level and spectrum assignment (MA-RMLSA) problem in EONs. Both EONs planning with static manycast traffic and EONs provisioning with dynamic manycast traffic are investigated. An integer linear programming (ILP) model is formulated to derive MA-RMLSA problem in static manycast scenario. Then corresponding heuristic algorithm called manycast routing, modulation level and spectrum assignment genetic algorithm (MA-RMLSA-GA) is proposed to adapt for both static and dynamic manycast scenarios. The MA-RMLSA-GA optimizes MA-RMLSA problem in destination nodes selection, routing light-tree constitution, modulation level allocation and spectrum resource assignment jointly, to achieve an effective improvement in network performance. Simulation results reveal that MA-RMLSA strategies offered by MA-RMLSA-GA have slightly disparity from the optimal solutions provided by ILP model in static scenario. Moreover, the results demonstrate that MA-RMLSA-GA realizes a highly efficient MA-RMLSA strategy with the lowest blocking probability in dynamic scenario compared with benchmark algorithms.

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

NASA Technical Reports Server (NTRS)

Idris, Husni; Shen, Ni; Wing, David J.

2011-01-01

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Variable cycle control model for intersection based on multi-source information

NASA Astrophysics Data System (ADS)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

Examining Road Traffic Mortality Status in China: A Simulation Study

PubMed Central

Schwebel, David C.; Li, Li; Hu, Guoqing

2016-01-01

Background Data from the Chinese police service suggest substantial reductions in road traffic injuries since 2002, but critics have questioned the accuracy of those data, especially considering conflicting data reported by the health department. Methods To address the gap between police and health department data and to determine which may be more accurate, we conducted a simulation study based on the modified Smeed equation, which delineates a non-linear relation between road traffic mortality and the level of motorization in a country or region. Our goal was to simulate trends in road traffic mortality in China and compare performances in road traffic safety management between China and 13 other countries. Results Chinese police data indicate a peak in road traffic mortalities in 2002 and a significant and a gradual decrease in population-based road traffic mortality since 2002. Health department data show the road traffic mortality peaked in 2012. In addition, police data suggest China’s road traffic mortality peaked at a much lower motorization level (0.061 motor vehicles per person) in 2002, followed by a reduction in mortality to a level comparable to that of developed countries. Simulation results based on health department data suggest high road traffic mortality, with a mortality peak in 2012 at a moderate motorization level (0.174 motor vehicles per person). Comparisons to the other 13 countries suggest the health data from China may be more valid than the police data. Conclusion Our simulation data indicate China is still at a stage of high road traffic mortality, as suggested by health data, rather than a stage of low road traffic mortality, as suggested by police data. More efforts are needed to integrate safety into road design, improve road traffic management, improve data quality, and alter unsafe behaviors of pedestrians, drivers and passengers in China. PMID:27071008

Restoration of Motion-Blurred Image Based on Border Deformation Detection: A Traffic Sign Restoration Model

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently. PMID:25849350

Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Using the Traffic monitoring guide to develop a truck weight sampling procedure for use in Virginia : final report.

DOT National Transportation Integrated Search

1992-01-01

The Traffic Monitoring Guide (TMG) provides a method for the development of a statistically based procedure to monitor traffic characteristics such as traffic loadings. Truck weight data in particular are a major element of the pavement management pr...

Automatic Traffic Advisory and Resolution Service (ATARS) Multi-Site Algorithms. Revision 1,

DTIC Science & Technology

1980-10-01

Summary Concept Description The Automatic Traffic Advisory and Resolution Service is a ground based collision avoidance system to be implemented in the...capability. A ground based computer processes the data and continuously provides proximity warning information and, when necessary, resolution advisories to...of ground- based air traffic control which provides proximity warning and separation services to uncontrolled aircraft in a given region of airspace. it

Traffic Aware Planner for Cockpit-Based Trajectory Optimization

NASA Technical Reports Server (NTRS)

Woods, Sharon E.; Vivona, Robert A.; Henderson, Jeffrey; Wing, David J.; Burke, Kelly A.

2016-01-01

The Traffic Aware Planner (TAP) software application is a cockpit-based advisory tool designed to be hosted on an Electronic Flight Bag and to enable and test the NASA concept of Traffic Aware Strategic Aircrew Requests (TASAR). The TASAR concept provides pilots with optimized route changes (including altitude) that reduce fuel burn and/or flight time, avoid interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a route and/or altitude change from Air Traffic Control. Developed using an iterative process, TAP's latest improvements include human-machine interface design upgrades and added functionality based on the results of human-in-the-loop simulation experiments and flight trials. Architectural improvements have been implemented to prepare the system for operational-use trials with partner commercial airlines. Future iterations will enhance coordination with airline dispatch and add functionality to improve the acceptability of TAP-generated route-change requests to pilots, dispatchers, and air traffic controllers.

Adaptive Response Criteria in Road Hazard Detection Among Older Drivers

PubMed Central

Feng, Jing; Choi, HeeSun; Craik, Fergus I. M.; Levine, Brian; Moreno, Sylvain; Naglie, Gary; Zhu, Motao

2018-01-01

OBJECTIVES The majority of existing investigations on attention, aging, and driving have focused on the negative impacts of age-related declines in attention on hazard detection and driver performance. However, driving skills and behavioral compensation may accommodate the negative effects that age-related attentional decline places on driving performance. In this study, we examined an important question that had been largely neglected in the literature linking attention, aging, and driving: can top-down factors such as behavioral compensation, specifically adaptive response criteria, accommodate the negative impacts from age-related attention declines on hazard detection during driving? METHODS In the experiment, we used the Drive Aware Task, a task combining the driving context with well-controlled laboratory procedures measuring attention. We compared younger (n = 16, age 21 – 30) and older drivers (n = 21, age 65 – 79) on their attentional processing of hazards in driving scenes, indexed by percentage of correct and reaction time of hazard detection, as well as sensitivity and response criterion using the signal detection analysis. RESULTS Older drivers, in general, were less accurate and slower on the task than younger drivers. However, results from this experiment also revealed that older, but not younger, drivers adapted their response criteria when the traffic condition changed in the driving scenes. When there was more traffic in the driving scene, older drivers became more liberal in their responses, meaning that they were more likely to report that a driving hazard was detected. CONCLUSIONS Older drivers adopt compensatory strategies on hazard detection during driving . Our findings showed that, in the driving context, even at an old age our attentional functions are still adaptive according to environmental conditions. This leads to considerations on potential training methods to promote adaptive strategies which may help older drivers maintaining performance in road hazard detection. PMID:28898116

Road sign recognition with fuzzy adaptive pre-processing models.

PubMed

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Research on quality metrics of wireless adaptive video streaming

NASA Astrophysics Data System (ADS)

Li, Xuefei

2018-04-01

With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

PubMed Central

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

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.

An optimal model-based trajectory following architecture synthesising the lateral adaptive preview strategy and longitudinal velocity planning for highly automated vehicle

NASA Astrophysics Data System (ADS)

Cao, Haotian; Song, Xiaolin; Zhao, Song; Bao, Shan; Huang, Zhi

2017-08-01

Automated driving has received a broad of attentions from the academia and industry, since it is effective to greatly reduce the severity of potential traffic accidents and achieve the ultimate automobile safety and comfort. This paper presents an optimal model-based trajectory following architecture for highly automated vehicle in its driving tasks such as automated guidance or lane keeping, which includes a velocity-planning module, a steering controller and a velocity-tracking controller. The velocity-planning module considering the optimal time-consuming and passenger comforts simultaneously could generate a smooth velocity profile. The robust sliding mode control (SMC) steering controller with adaptive preview time strategy could not only track the target path well, but also avoid a big lateral acceleration occurred in its path-tracking progress due to a fuzzy-adaptive preview time mechanism introduced. In addition, an SMC controller with input-output linearisation method for velocity tracking is built and validated. Simulation results show this trajectory following architecture are effective and feasible for high automated driving vehicle, comparing with the Driver-in-the-Loop simulations performed by an experienced driver and novice driver, respectively. The simulation results demonstrate that the present trajectory following architecture could plan a satisfying longitudinal speed profile, track the target path well and safely when dealing with different road geometry structure, it ensures a good time efficiency and driving comfort simultaneously.

Conflict Resolution Performance in an Experimental Study of En Route Free Maneuvering Operations

NASA Technical Reports Server (NTRS)

Doble, Nathan A.; Barhydt, Richard; Hitt, James M., II

2005-01-01

NASA has developed a far-term air traffic management concept, termed Distributed Air/Ground Traffic Management (DAG-TM). One component of DAG-TM, En Route Free Maneuvering, allows properly trained flight crews of equipped autonomous aircraft to assume responsibility for separation from other autonomous aircraft and from Instrument Flight Rules (IFR) aircraft. Ground-based air traffic controllers continue to separate IFR traffic and issue flow management constraints to all aircraft. To examine En Route Free Maneuvering operations, a joint human-in-the-loop experiment was conducted in summer 2004 at the NASA Ames and Langley Research Centers. Test subject pilots used desktop flight simulators to resolve traffic conflicts and adhere to air traffic flow constraints issued by subject controllers. The experimental airspace integrated both autonomous and IFR aircraft at varying traffic densities. This paper presents a subset of the En Route Free Maneuvering experimental results, focusing on airborne and ground-based conflict resolution, and the effects of increased traffic levels on the ability of pilots and air traffic controllers to perform this task. The results show that, in general, increases in autonomous traffic do not significantly impact conflict resolution performance. In addition, pilot acceptability of autonomous operations remains high throughout the range of traffic densities studied. Together with previously reported findings, these results continue to support the feasibility of the En Route Free Maneuvering component of DAG-TM.

Real-time traffic sign recognition based on a general purpose GPU and deep-learning.

PubMed

Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

Effect of Pokémon GO on incidence of fatal traffic injuries: a population-based quasi-experimental study using the national traffic collisions database in Japan.

PubMed

Ono, Sachiko; Ono, Yosuke; Michihata, Nobuaki; Sasabuchi, Yusuke; Yasunaga, Hideo

2017-10-12

Pokémon GO (Niantic Labs, released on 22 July 2016 in Japan) is an augmented reality game that gained huge popularity worldwide. Despite concern about Pokémon GO-related traffic collisions, the effect of playing Pokémon GO on the incidence of traffic injuries remains unknown. We performed a population-based quasi-experimental study using national data from the Institute for Traffic Accident Research and Data Analysis, Japan. The outcome was incidence of traffic injuries. Of 127 082 000 people in Japan, 886 fatal traffic injuries were observed between 1 June and 31 August in 2016. Regression discontinuity analysis showed a non-significant change in incidence of fatal traffic injuries after the Pokémon GO release (0.017 deaths per million, 95%CI -0.036 to 0.071). This finding was similar to that obtained from a difference-in-differences analysis. Effect of Pokémon GO on fatal traffic injuries may be negligible. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Collaborative Aviation Weather Statement - An Impact-based Decision Support Tool

NASA Astrophysics Data System (ADS)

Blondin, Debra

2016-04-01

Historically, convection causes the highest number of air traffic constraints on the United States National Air Space (NAS). Increased NAS predictability allows traffic flow managers to more effectively initiate, amend or terminate planned or active traffic management initiatives, resulting in more efficient use of available airspace. A Collaborative Aviation Weather Statement (CAWS) is an impact-based decision support tool used for the timely delivery of high-confidence, high-relevance aviation convective weather forecasts to air traffic managers. The CAWS is a graphical and textual forecast produced by a collaborative team of meteorologists from the Aviation Weather Center (AWC), Center Weather Service Units, and airlines to bring attention to high impact areas of thunderstorms. The CAWS addresses thunderstorm initiation or movement into the airports having the highest volume of traffic or into traffic sensitive jet routes. These statements are assessed by planners at the Federal Aviation Administration's (FAA) Air Route Traffic Control Centers and are used for planning traffic management initiatives to balance air traffic flow across the United States. The FAA and the airline industry use the CAWS to plan, manage, and execute operations in the NAS, thereby improving the system efficiency and safety and also saving dollars for industry and the traveling public.

Impact of aggregation on scaling behavior of Internet backbone traffic

NASA Astrophysics Data System (ADS)

Zhang, Zhi-Li; Ribeiro, Vinay J.; Moon, Sue B.; Diot, Christophe

2002-07-01

We study the impact of aggregation on the scaling behavior of Internet backbone tra ffic, based on traces collected from OC3 and OC12 links in a tier-1 ISP. We make two striking observations regarding the sub-second small time scaling behaviors of Internet backbone traffic: 1) for a majority of these traces, the Hurst parameters at small time scales (1ms - 100ms) are fairly close to 0.5. Hence the traffic at these time scales are nearly uncorrelated; 2) the scaling behaviors at small time scales are link-dependent, and stay fairly invariant over changing utilization and time. To understand the scaling behavior of network traffic, we develop analytical models and employ them to demonstrate how traffic composition -- aggregation of traffic with different characteristics -- affects the small-time scalings of network traffic. The degree of aggregation and burst correlation structure are two major factors in traffic composition. Our trace-based data analysis confirms this. Furthermore, we discover that traffic composition on a backbone link stays fairly consistent over time and changing utilization, which we believe is the cause for the invariant small-time scalings we observe in the traces.

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.

A Cockpit-Based Application for Traffic Aware Trajectory Optimization

NASA Technical Reports Server (NTRS)

Woods, Sharon E.; Vivona, Robert A.; Roscoe, David A.; LeFebvre, Brendan C.; Wing, David J.; Ballin, Mark G.

2013-01-01

The Traffic Aware Planner (TAP) is a cockpit-based advisory tool designed to be hosted on a Class 2 Electronic Flight Bag and developed to enable the concept of Traffic Aware Strategic Aircrew Requests (TASAR). This near-term concept provides pilots with optimized route changes that reduce fuel burn or flight time, avoids interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a trajectory change from air traffic control. TAP's internal architecture and algorithms are derived from the Autonomous Operations Planner, a flight-deck automation system developed by NASA to support research into aircraft self-separation. This paper reviews the architecture, functionality and operation of TAP.

An observation tool to study air traffic control and flightdeck collaboration.

PubMed

Cox, Gemma; Sharples, Sarah; Stedmon, Alex; Wilson, John

2007-07-01

The complex systems of the flightdeck (FD) and the Air Traffic Control Centre (ATC) are characterised by numerous concurrently operating and interacting communication channels between people and between people and machines/computer systems. This paper describes work in support of investigating the impact of changes to technologies and responsibilities within this system with respect to human factors. It focuses primarily on the introduction of datalink (text-based communication rather than traditional radio communication) and the move towards freeflight (pilot-mediated air traffic control). Air traffic management investigations have outlined these specific changes as strategies to enable further increases in the volume of air traffic. A systems approach was taken and field studies were conducted. Small numbers of domain experts such as air traffic controllers (ATCOs) were involved in the field-based observations of how people interact with systems and each other. This paper summarises the overall research approach taken and then specifically reports on the field-based observations including the justification, development, and findings of the observation tool used. The observation tool examined information propagation through the air traffic control-flightdeck (ATC-FD) system, and resulted in models of possible information trajectories through the system.

Dynamics of traffic flow with real-time traffic information

NASA Astrophysics Data System (ADS)

Yokoya, Yasushi

2004-01-01

We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

Multi-Center Traffic Management Advisor Operational Field Test Results

NASA Technical Reports Server (NTRS)

Farley, Todd; Landry, Steven J.; Hoang, Ty; Nickelson, Monicarol; Levin, Kerry M.; Rowe, Dennis W.

2005-01-01

The Multi-Center Traffic Management Advisor (McTMA) is a research prototype system which seeks to bring time-based metering into the mainstream of air traffic control (ATC) operations. Time-based metering is an efficient alternative to traditional air traffic management techniques such as distance-based spacing (miles-in-trail spacing) and managed arrival reservoirs (airborne holding). While time-based metering has demonstrated significant benefit in terms of arrival throughput and arrival delay, its use to date has been limited to arrival operations at just nine airports nationally. Wide-scale adoption of time-based metering has been hampered, in part, by the limited scalability of metering automation. In order to realize the full spectrum of efficiency benefits possible with time-based metering, a much more modular, scalable time-based metering capability is required. With its distributed metering architecture, multi-center TMA offers such a capability.

Large Scale Traffic Simulations

DOT National Transportation Integrated Search

1997-01-01

Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computation speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated "looping" between t...

0-6775 : NTCIP-based traffic signal evaluation and optimization toolbox.

DOT National Transportation Integrated Search

2014-08-01

Routine maintenance of traffic signals requires : identification and resolution of hardware faults : and operational inefficiencies. Like most : agencies in charge of operating and maintaining : traffic signals scattered over large geographic : regio...

Community structure in traffic zones based on travel demand

NASA Astrophysics Data System (ADS)

Sun, Li; Ling, Ximan; He, Kun; Tan, Qian

2016-09-01

Large structure in complex networks can be studied by dividing it into communities or modules. Urban traffic system is one of the most critical infrastructures. It can be abstracted into a complex network composed of tightly connected groups. Here, we analyze community structure in urban traffic zones based on the community detection method in network science. Spectral algorithm using the eigenvectors of matrices is employed. Our empirical results indicate that the traffic communities are variant with the travel demand distribution, since in the morning the majority of the passengers are traveling from home to work and in the evening they are traveling a contrary direction. Meanwhile, the origin-destination pairs with large number of trips play a significant role in urban traffic network's community division. The layout of traffic community in a city also depends on the residents' trajectories.

Fostering Self-Regulation in Training Complex Cognitive Tasks

ERIC Educational Resources Information Center

van Meeuwen, Ludo W.; Brand-Gruwel, Saskia; Kirschner, Paul A.; de Bock, Jeano J. P. R.; van Merriënboer, Jeroen J. G.

2018-01-01

In complex cognitive domains such as air traffic control, professionals must be able to adapt to and act upon continuing changes in a highly advanced technological work environment. To function optimally in such an environment, the controllers must be able to regulate their learning. Although these regulation skills should be part of their…

Physics of automated driving in framework of three-phase traffic theory.

PubMed

Kerner, Boris S

2018-04-01

We have revealed physical features of automated driving in the framework of the three-phase traffic theory for which there is no fixed time headway to the preceding vehicle. A comparison with the classical model approach to automated driving for which an automated driving vehicle tries to reach a fixed (desired or "optimal") time headway to the preceding vehicle has been made. It turns out that automated driving in the framework of the three-phase traffic theory can exhibit the following advantages in comparison with the classical model of automated driving: (i) The absence of string instability. (ii) Considerably smaller speed disturbances at road bottlenecks. (iii) Automated driving vehicles based on the three-phase theory can decrease the probability of traffic breakdown at the bottleneck in mixed traffic flow consisting of human driving and automated driving vehicles; on the contrary, even a single automated driving vehicle based on the classical approach can provoke traffic breakdown at the bottleneck in mixed traffic flow.

Physics of automated driving in framework of three-phase traffic theory

NASA Astrophysics Data System (ADS)

Kerner, Boris S.

2018-04-01

We have revealed physical features of automated driving in the framework of the three-phase traffic theory for which there is no fixed time headway to the preceding vehicle. A comparison with the classical model approach to automated driving for which an automated driving vehicle tries to reach a fixed (desired or "optimal") time headway to the preceding vehicle has been made. It turns out that automated driving in the framework of the three-phase traffic theory can exhibit the following advantages in comparison with the classical model of automated driving: (i) The absence of string instability. (ii) Considerably smaller speed disturbances at road bottlenecks. (iii) Automated driving vehicles based on the three-phase theory can decrease the probability of traffic breakdown at the bottleneck in mixed traffic flow consisting of human driving and automated driving vehicles; on the contrary, even a single automated driving vehicle based on the classical approach can provoke traffic breakdown at the bottleneck in mixed traffic flow.

An improved car-following model considering velocity fluctuation of the immediately ahead car

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Huang, Mengxing; Ren, Jia; Shi, Zhongke

2016-05-01

To better describe car-following behaviors in the adaptive cruise control strategy and further increase roadway traffic mobility and reduce fuel consumptions, the linkage between velocity fluctuation of the immediately ahead car and the following car's acceleration or deceleration is explored with respect to the measured car-following data by employing the gray correlation analysis theory and then an improved car-following model considering velocity fluctuation of the immediately ahead car on basis of the full velocity difference model is proposed. Numerical simulations are carried out and the effects of velocity fluctuation of the immediately ahead car on each car's velocity, acceleration, vehicular gap, fuel consumptions and the total fuel consumptions of the whole car-following system with different time window lengths are investigated in detail. The results show that velocity fluctuation of the immediately ahead car has significant effects on car-following behaviors and fuel consumptions, and that considering velocity fluctuation of the immediately ahead car in designing the adaptive cruise control system can improve traffic flow stability and reduce fuel consumptions.

Mapping edge-based traffic measurements onto the internal links in MPLS network

NASA Astrophysics Data System (ADS)

Zhao, Guofeng; Tang, Hong; Zhang, Yi

2004-09-01

Applying multi-protocol label switching techniques to IP-based backbone for traffic engineering goals has shown advantageous. Obtaining a volume of load on each internal link of the network is crucial for traffic engineering applying. Though collecting can be available for each link, such as applying traditional SNMP scheme, the approach may cause heavy processing load and sharply degrade the throughput of the core routers. Then monitoring merely at the edge of the network and mapping the measurements onto the core provides a good alternative way. In this paper, we explore a scheme for traffic mapping with edge-based measurements in MPLS network. It is supposed that the volume of traffic on each internal link over the domain would be mapped onto by measurements available only at ingress nodes. We apply path-based measurements at ingress nodes without enabling measurements in the core of the network. We propose a method that can infer a path from the ingress to the egress node using label distribution protocol without collecting routing data from core routers. Based on flow theory and queuing theory, we prove that our approach is effective and present the algorithm for traffic mapping. We also show performance simulation results that indicate potential of our approach.

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.

Traffic Behavior Recognition Using the Pachinko Allocation Model

PubMed Central

Huynh-The, Thien; Banos, Oresti; Le, Ba-Vui; Bui, Dinh-Mao; Yoon, Yongik; Lee, Sungyoung

2015-01-01

CCTV-based behavior recognition systems have gained considerable attention in recent years in the transportation surveillance domain for identifying unusual patterns, such as traffic jams, accidents, dangerous driving and other abnormal behaviors. In this paper, a novel approach for traffic behavior modeling is presented for video-based road surveillance. The proposed system combines the pachinko allocation model (PAM) and support vector machine (SVM) for a hierarchical representation and identification of traffic behavior. A background subtraction technique using Gaussian mixture models (GMMs) and an object tracking mechanism based on Kalman filters are utilized to firstly construct the object trajectories. Then, the sparse features comprising the locations and directions of the moving objects are modeled by PAM into traffic topics, namely activities and behaviors. As a key innovation, PAM captures not only the correlation among the activities, but also among the behaviors based on the arbitrary directed acyclic graph (DAG). The SVM classifier is then utilized on top to train and recognize the traffic activity and behavior. The proposed model shows more flexibility and greater expressive power than the commonly-used latent Dirichlet allocation (LDA) approach, leading to a higher recognition accuracy in the behavior classification. PMID:26151213

A Cooperative Traffic Control of Vehicle–Intersection (CTCVI) for the Reduction of Traffic Delays and Fuel Consumption

PubMed Central

Li, Jinjian; Dridi, Mahjoub; El-Moudni, Abdellah

2016-01-01

The problem of reducing traffic delays and decreasing fuel consumption simultaneously in a network of intersections without traffic lights is solved by a cooperative traffic control algorithm, where the cooperation is executed based on the connection of Vehicle-to-Infrastructure (V2I). This resolution of the problem contains two main steps. The first step concerns the itinerary of which intersections are chosen by vehicles to arrive at their destination from their starting point. Based on the principle of minimal travel distance, each vehicle chooses its itinerary dynamically based on the traffic loads in the adjacent intersections. The second step is related to the following proposed cooperative procedures to allow vehicles to pass through each intersection rapidly and economically: on one hand, according to the real-time information sent by vehicles via V2I in the edge of the communication zone, each intersection applies Dynamic Programming (DP) to cooperatively optimize the vehicle passing sequence with minimal traffic delays so that the vehicles may rapidly pass the intersection under the relevant safety constraints; on the other hand, after receiving this sequence, each vehicle finds the optimal speed profiles with the minimal fuel consumption by an exhaustive search. The simulation results reveal that the proposed algorithm can significantly reduce both travel delays and fuel consumption compared with other papers under different traffic volumes. PMID:27999333

Real-time traffic sign recognition based on a general purpose GPU and deep-learning

PubMed Central

Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea). PMID:28264011

Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 8. Operational Logic Flow Diagrams for a Generic Advanced Air Traffic Management system

DOT National Transportation Integrated Search

1974-02-01

The volume presents a description of the services a generic Advanced Air Traffic Management System (AATMS) should provide to the useres of the system to facilitate the safe, efficient flow of traffic. It provides a definition of the functions which t...

2004-2006 Puget Sound Traffic Choices Study | Transportation Secure Data

Science.gov Websites

Center | NREL 04-2006 Puget Sound Traffic Choices Study 2004-2006 Puget Sound Traffic Choices Study The 2004-2006 Puget Sound Traffic Choices Study tested the hypothesis that time-of-day variable Administration for a pilot project on congestion-based tolling. Methodology To test the hypothesis, the study

Drawing for Traffic Marking Using Bidirectional Gradient-Based Detection with MMS LIDAR Intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Nakamura, K.

2016-06-01

Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS) equipped with high-density Laser imaging Detection and Ranging (LiDAR) scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014). The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

Packet Traffic Dynamics Near Onset of Congestion in Data Communication Network Model

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-05-01

The dominant technology of data communication networks is the Packet Switching Network (PSN). It is a complex technology organized as various hierarchical layers according to the International Standard Organization (ISO) Open Systems Interconnect (OSI) Reference Model. The Network Layer of the ISO OSI Reference Model is responsible for delivering packets from their sources to their destinations and for dealing with congestion if it arises in a network. Thus, we focus on this layer and present an abstraction of the Network Layer of the ISO OSI Reference Model. Using this abstraction we investigate how onset of traffic congestion is affected for various routing algorithms by changes in network connection topology. We study how aggregate measures of network performance depend on network connection topology and routing. We explore packets traffic spatio-temporal dynamics near the phase transition point from free flow to congestion for various network connection topologies and routing algorithms. We consider static and adaptive routings. We present selected simulation results.

Digital watermarking for secure and adaptive teleconferencing

NASA Astrophysics Data System (ADS)

Vorbrueggen, Jan C.; Thorwirth, Niels

2002-04-01

The EC-sponsored project ANDROID aims to develop a management system for secure active networks. Active network means allowing the network's customers to execute code (Java-based so-called proxylets) on parts of the network infrastructure. Secure means that the network operator nonetheless retains full control over the network and its resources, and that proxylets use ANDROID-developed facilities to provide secure applications. Management is based on policies and allows autonomous, distributed decisions and actions to be taken. Proxylets interface with the system via policies; among actions they can take is controlling execution of other proxylets or redirection of network traffic. Secure teleconferencing is used as the application to demonstrate the approach's advantages. A way to control a teleconference's data streams is to use digital watermarking of the video, audio and/or shared-whiteboard streams, providing an imperceptible and inseparable side channel that delivers information from originating or intermediate stations to downstream stations. Depending on the information carried by the watermark, these stations can take many different actions. Examples are forwarding decisions based on security classifications (possibly time-varying) at security boundaries, set-up and tear-down of virtual private networks, intelligent and adaptive transcoding, recorder or playback control (e.g., speaking off the record), copyright protection, and sender authentication.

Satellite Communications for Aeronautical Applications: Recent research and Development Results

NASA Technical Reports Server (NTRS)

Kerczewski, Robert J.

2001-01-01

Communications systems have always been a critical element in aviation. Until recently, nearly all communications between the ground and aircraft have been based on analog voice technology. But the future of global aviation requires a more sophisticated "information infrastructure" which not only provides more and better communications, but integrates the key information functions (communications, navigation, and surveillance) into a modern, network-based infrastructure. Satellite communications will play an increasing role in providing information infrastructure solutions for aviation. Developing and adapting satellite communications technologies for aviation use is now receiving increased attention as the urgency to develop information infrastructure solutions grows. The NASA Glenn Research Center is actively involved in research and development activities for aeronautical satellite communications, with a key emphasis on air traffic management communications needs. This paper describes the recent results and status of NASA Glenn's research program.

Traffic Sign Detection Based on Biologically Visual Mechanism

NASA Astrophysics Data System (ADS)

Hu, X.; Zhu, X.; Li, D.

2012-07-01

TSR (Traffic sign recognition) is an important problem in ITS (intelligent traffic system), which is being paid more and more attention for realizing drivers assisting system and unmanned vehicle etc. TSR consists of two steps: detection and recognition, and this paper describe a new traffic sign detection method. The design principle of the traffic sign is comply with the visual attention mechanism of human, so we propose a method using visual attention mechanism to detect traffic sign ,which is reasonable. In our method, the whole scene will firstly be analyzed by visual attention model to acquire the area where traffic signs might be placed. And then, these candidate areas will be analyzed according to the shape characteristics of the traffic sign to detect traffic signs. In traffic sign detection experiments, the result shows the proposed method is effectively and robust than other existing saliency detection method.

A knowledge-based system for controlling automobile traffic

NASA Technical Reports Server (NTRS)

Maravas, Alexander; Stengel, Robert F.

1994-01-01

Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

Text Line Detection from Rectangle Traffic Panels of Natural Scene

NASA Astrophysics Data System (ADS)

Wang, Shiyuan; Huang, Linlin; Hu, Jian

2018-01-01

Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

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.

Right-Turn Traffic Volume Adjustments in Traffic Signal Warrant Analysis

DOT National Transportation Integrated Search

2015-01-01

To accomplish this research, a comprehensive literature review of existing guidelines and findings based on national and local studies was conducted. Ultimately, guidelines for consistent application for adjusting right-turn traffic volumes were deve...

A new model to improve aggregate air traffic demand predictions

DOT National Transportation Integrated Search

2007-08-20

Federal Aviation Administration (FAA) air traffic flow management (TFM) : decision-making is based primarily on a comparison of predictions of traffic demand and : available capacity at various National Airspace System (NAS) elements such as airports...

Discovering urban mobility patterns with PageRank based traffic modeling and prediction

NASA Astrophysics Data System (ADS)

Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

2017-11-01

Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.

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.

Software Tools to Support Research on Airport Departure Planning

NASA Technical Reports Server (NTRS)

Carr, Francis; Evans, Antony; Feron, Eric; Clarke, John-Paul

2003-01-01

A simple, portable and useful collection of software tools has been developed for the analysis of airport surface traffic. The tools are based on a flexible and robust traffic-flow model, and include calibration, validation and simulation functionality for this model. Several different interfaces have been developed to help promote usage of these tools, including a portable Matlab(TM) implementation of the basic algorithms; a web-based interface which provides online access to automated analyses of airport traffic based on a database of real-world operations data which covers over 250 U.S. airports over a 5-year period; and an interactive simulation-based tool currently in use as part of a college-level educational module. More advanced applications for airport departure traffic include taxi-time prediction and evaluation of "windowing" congestion control.

Web-based Traffic Noise Control Support System for Sustainable Transportation

NASA Astrophysics Data System (ADS)

Fan, Lisa; Dai, Liming; Li, Anson

Traffic noise is considered as one of the major pollutions that will affect our communities in the future. This paper presents a framework of web-based traffic noise control support system (WTNCSS) for a sustainable transportation. WTNCSS is to provide the decision makers, engineers and publics a platform to efficiently access the information, and effectively making decisions related to traffic control. The system is based on a Service Oriented Architecture (SOA) which takes the advantages of the convenience of World Wide Web system with the data format of XML. The whole system is divided into different modules such as the prediction module, ontology-based expert module and dynamic online survey module. Each module of the system provides a distinct information service to the decision support center through the HTTP protocol.

An agent-based model for queue formation of powered two-wheelers in heterogeneous traffic

NASA Astrophysics Data System (ADS)

Lee, Tzu-Chang; Wong, K. I.

2016-11-01

This paper presents an agent-based model (ABM) for simulating the queue formation of powered two-wheelers (PTWs) in heterogeneous traffic at a signalized intersection. The main novelty is that the proposed interaction rule describing the position choice behavior of PTWs when queuing in heterogeneous traffic can capture the stochastic nature of the decision making process. The interaction rule is formulated as a multinomial logit model, which is calibrated by using a microscopic traffic trajectory dataset obtained from video footage. The ABM is validated against the survey data for the vehicular trajectory patterns, queuing patterns, queue lengths, and discharge rates. The results demonstrate that the proposed model is capable of replicating the observed queue formation process for heterogeneous traffic.

Phase diagram of congested traffic flow: An empirical study

PubMed

Lee; Lee; Kim

2000-10-01

We analyze traffic data from a highway section containing one effective on-ramp. Based on two criteria, local velocity variation patterns and expansion (or nonexpansion) of congested regions, three distinct congested traffic states are identified. These states appear at different levels of the upstream flux and the on-ramp flux, thereby generating a phase digram of the congested traffic flow. Observed traffic states are compared with recent theoretical analyses and both agreeing and disagreeing features are found.

Development and application of traffic flow information collecting and analysis system based on multi-type video

NASA Astrophysics Data System (ADS)

Lu, Mujie; Shang, Wenjie; Ji, Xinkai; Hua, Mingzhuang; Cheng, Kuo

2015-12-01

Nowadays, intelligent transportation system (ITS) has already become the new direction of transportation development. Traffic data, as a fundamental part of intelligent transportation system, is having a more and more crucial status. In recent years, video observation technology has been widely used in the field of traffic information collecting. Traffic flow information contained in video data has many advantages which is comprehensive and can be stored for a long time, but there are still many problems, such as low precision and high cost in the process of collecting information. This paper aiming at these problems, proposes a kind of traffic target detection method with broad applicability. Based on three different ways of getting video data, such as aerial photography, fixed camera and handheld camera, we develop a kind of intelligent analysis software which can be used to extract the macroscopic, microscopic traffic flow information in the video, and the information can be used for traffic analysis and transportation planning. For road intersections, the system uses frame difference method to extract traffic information, for freeway sections, the system uses optical flow method to track the vehicles. The system was applied in Nanjing, Jiangsu province, and the application shows that the system for extracting different types of traffic flow information has a high accuracy, it can meet the needs of traffic engineering observations and has a good application prospect.

Rate-based congestion control in networks with smart links, revision. B.S. Thesis - May 1988

NASA Technical Reports Server (NTRS)

Heybey, Andrew Tyrrell

1990-01-01

The author uses a network simulator to explore rate-based congestion control in networks with smart links that can feed back information to tell senders to adjust their transmission rates. This method differs in a very important way from congestion control in which a congested network component just drops packets - the most commonly used method. It is clearly advantageous for the links in the network to communicate with the end users about the network capacity, rather than the users unilaterally picking a transmission rate. The components in the middle of the network, not the end users, have information about the capacity and traffic in the network. The author experiments with three different algorithms for calculating the control rate to feed back to the users. All of the algorithms exhibit problems in the form of large queues when simulated with a configuration modeling the dynamics of a packet-voice system. However, the problems are not with the algorithms themselves, but with the fact that feedback takes time. If the network steady-state utilization is low enough that it can absorb transients in the traffic through it, then the large queues disappear. If the users are modified to start sending slowly, to allow the network to adapt to a new flow without causing congestion, a greater portion of the network's bandwidth can be used.

Cross-layer cluster-based energy-efficient protocol for wireless sensor networks.

PubMed

Mammu, Aboobeker Sidhik Koyamparambil; Hernandez-Jayo, Unai; Sainz, Nekane; de la Iglesia, Idoia

2015-04-09

Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).

Coexistence of ZigBee-Based WBAN and WiFi for Health Telemonitoring Systems.

PubMed

Kim, Yena; Lee, SeungSeob; Lee, SuKyoung

2016-01-01

The development of telemonitoring via wireless body area networks (WBANs) is an evolving direction in personalized medicine and home-based mobile health. A WBAN consists of small, intelligent medical sensors which collect physiological parameters such as electrocardiogram, electroencephalography, and blood pressure. The recorded physiological signals are sent to a coordinator via wireless technologies, and are then transmitted to a healthcare monitoring center. One of the most widely used wireless technologies in WBANs is ZigBee because it is targeted at applications that require a low data rate and long battery life. However, ZigBee-based WBANs face severe interference problems in the presence of WiFi networks. This problem is caused by the fact that most ZigBee channels overlap with WiFi channels, severely affecting the ability of healthcare monitoring systems to guarantee reliable delivery of physiological signals. To solve this problem, we have developed an algorithm that controls the load in WiFi networks to guarantee the delay requirement for physiological signals, especially for emergency messages, in environments with coexistence of ZigBee-based WBAN and WiFi. Since WiFi applications generate traffic with different delay requirements, we focus only on WiFi traffic that does not have stringent timing requirements. In this paper, therefore, we propose an adaptive load control algorithm for ZigBee-based WBAN/WiFi coexistence environments, with the aim of guaranteeing that the delay experienced by ZigBee sensors does not exceed a maximally tolerable period of time. Simulation results show that our proposed algorithm guarantees the delay performance of ZigBee-based WBANs by mitigating the effects of WiFi interference in various scenarios.

Design and Operational Evaluation of the Traffic Management Advisor at the Ft. Worth Air Route Traffic Control Center

NASA Technical Reports Server (NTRS)

Swenson, Harry N.; Vincent, Danny; Tobias, Leonard (Technical Monitor)

1997-01-01

NASA and the FAA have designed and developed and an automation tool known as the Traffic Management Advisor (TMA). The system was operationally evaluated at the Ft. Worth Air Route Traffic Control Center (ARTCC). The TMA is a time-based strategic planning tool that provides Traffic Management Coordinators and En Route Air Traffic Controllers the ability to efficiently optimize the capacity of a demand impacted airport. The TMA consists of trajectory prediction, constraint-based runway scheduling, traffic flow visualization and controllers advisories. The TMA was used and operationally evaluated for forty-one rush traffic periods during a one month period in the Summer of 1996. The evaluations included all shifts of air traffic operations as well as periods of inclement weather. Performance data was collected for engineering and human factor analysis and compared with similar operations without the TMA. The engineering data indicates that the operations with the TMA show a one to two minute per aircraft delay reduction during rush periods. The human factor data indicate a perceived reduction in en route controller workload as well as an increase in job satisfaction. Upon completion of the evaluation, the TMA has become part of the normal operations at the Ft. Worth ARTCC.

Elastic all-optical multi-hop interconnection in data centers with adaptive spectrum allocation

NASA Astrophysics Data System (ADS)

Hong, Yuanyuan; Hong, Xuezhi; Chen, Jiajia; He, Sailing

2017-01-01

In this paper, a novel flex-grid all-optical interconnect scheme that supports transparent multi-hop connections in data centers is proposed. An inter-rack all-optical multi-hop connection is realized with an optical loop employed at flex-grid wavelength selective switches (WSSs) in an intermediate rack rather than by relaying through optical-electric-optical (O-E-O) conversions. Compared with the conventional O-E-O based approach, the proposed all-optical scheme is able to off-load the traffic at intermediate racks, leading to a reduction of the power consumption and cost. The transmission performance of the proposed flex-grid multi-hop all-optical interconnect scheme with various modulation formats, including both coherently detected and directly detected approaches, are investigated by Monte-Carlo simulations. To enhance the spectrum efficiency (SE), number-of-hop adaptive bandwidth allocation is introduced. Numerical results show that the SE can be improved by up to 33.3% at 40 Gbps, and by up to 25% at 100 Gbps. The impact of parameters, such as targeted bit error rate (BER) level and insertion loss of components, on the transmission performance of the proposed approach are also explored. The results show that the maximum SE improvement of the adaptive approach over the non-adaptive one is enhanced with the decrease of the targeted BER levels and the component insertion loss.

Autonomic and Coevolutionary Sensor Networking

NASA Astrophysics Data System (ADS)

Boonma, Pruet; Suzuki, Junichi

(WSNs) applications are often required to balance the tradeoffs among conflicting operational objectives (e.g., latency and power consumption) and operate at an optimal tradeoff. This chapter proposes and evaluates a architecture, called BiSNET/e, which allows WSN applications to overcome this issue. BiSNET/e is designed to support three major types of WSN applications: , and hybrid applications. Each application is implemented as a decentralized group of, which is analogous to a bee colony (application) consisting of bees (agents). Agents collect sensor data or detect an event (a significant change in sensor reading) on individual nodes, and carry sensor data to base stations. They perform these data collection and event detection functionalities by sensing their surrounding network conditions and adaptively invoking behaviors such as pheromone emission, reproduction, migration, swarming and death. Each agent has its own behavior policy, as a set of genes, which defines how to invoke its behaviors. BiSNET/e allows agents to evolve their behavior policies (genes) across generations and autonomously adapt their performance to given objectives. Simulation results demonstrate that, in all three types of applications, agents evolve to find optimal tradeoffs among conflicting objectives and adapt to dynamic network conditions such as traffic fluctuations and node failures/additions. Simulation results also illustrate that, in hybrid applications, data collection agents and event detection agents coevolve to augment their adaptability and performance.

Arrival metering fuel consumption analysis

DOT National Transportation Integrated Search

2011-01-01

Arrival metering is a method of time-based traffic management that is used by the Federal Aviation Administration to plan and manage streams of arrival traffic during periods of : high demand at busy airports. The Traffic Management Advisor is an aut...

Symbols for cockpit displays of traffic information

DOT National Transportation Integrated Search

2009-10-25

A web-based study assessed pilots ability to learn and remember traffic symbols that may be shown on a Cockpit Display of Traffic Information (CDTI). These displays convey data obtained from Automatic Dependent Surveillance-Broadcast (ADS B) and rela...

Application of dynamic traffic assignment to advanced managed lane modeling.

DOT National Transportation Integrated Search

2013-11-01

In this study, a demand estimation framework is developed for assessing the managed lane (ML) : strategies by utilizing dynamic traffic assignment (DTA) modeling, instead of the traditional : approaches that are based on the static traffic assignment...

Using Mobile Device Samples to Estimate Traffic Volumes

DOT National Transportation Integrated Search

2017-12-01

In this project, TTI worked with StreetLight Data to evaluate a beta version of its traffic volume estimates derived from global positioning system (GPS)-based mobile devices. TTI evaluated the accuracy of average annual daily traffic (AADT) volume :...

Traffic data collection and anonymous vehicle detection using wireless sensor networks.

DOT National Transportation Integrated Search

2012-05-01

New traffic sensing devices based on wireless sensing technologies were designed and tested. Such devices encompass a cost-effective, battery-free, and energy self-sustained architecture for real-time traffic measurement over distributed points in a ...

Symbols for cockpit displays of traffic information

DOT National Transportation Integrated Search

2010-03-01

A web-based study assessed pilots ability to learn and remember traffic symbols that may be shown on a Cockpit Display of Traffic Information (CDTI). These displays convey data obtained from Automatic Dependent Surveillance-Broadcast (ADS B) and rela...

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.

Solutions to Improve Road Circulation in the Pitesti City Based on Analysis-Diagnostics of Road Traffic

NASA Astrophysics Data System (ADS)

Vîlcan, A.; Neagu, E.; Badarau Suster, H.; Boroiu, A. A.

2017-10-01

Road traffic congestion has become a daily phenomenon in the central area of Pitesti in the peak traffic periods. In order to achieve the mobility plan of Pitesti, an important stage is the diagnostic analysis of the road traffic. For this purpose, the urban road network was formalized through a graph containing the most important 40 intersections and traffic measurements were made at all these intersections and on the main roads connecting the peri-urban area. The data obtained by traffic macrosimulation confirmed the overloading of the street network during peak traffic hours and the analyzes made for various road traffic organization scenarios have shown that there are sustainable solutions for urban mobility only if the road network is fundamentally reconfigured (a belt outside the city and a median ring). Thus, the necessity of realizing the road passage in the Prundu neighbourhood and the finishing of the city belt by realizing the “detour West” of the city is argued. The importance of the work is that it brings scientific arguments for the realization of these road infrastructure projects, integrated in the urban mobility plan, which will base the development strategy of the Pitesti municipality.

A new simulation system of traffic flow based on cellular automata principle

NASA Astrophysics Data System (ADS)

Shan, Junru

2017-05-01

Traffic flow is a complex system of multi-behavior so it is difficult to give a specific mathematical equation to express it. With the rapid development of computer technology, it is an important method to study the complex traffic behavior by simulating the interaction mechanism between vehicles and reproduce complex traffic behavior. Using the preset of multiple operating rules, cellular automata is a kind of power system which has discrete time and space. It can be a good simulation of the real traffic process and a good way to solve the traffic problems.

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.

Strobe Traffic Lights Warn of Approaching Emergency Vehicles

NASA Technical Reports Server (NTRS)

Bachelder, Aaron

2004-01-01

Strobe-enhanced traffic signals have been developed to aid in the preemption of road intersections for emergency vehicles. The strobe-enhanced traffic signals can be incorporated into both new and pre-existing traffic-control systems in which the traffic-signal heads are of a relatively new type based on arrays of light-emitting diodes (LEDs). The strobe-enhanced traffic signals offer a less expensive, less complex alternative to a recently developed system of LED-based warning signs placed next to traffic signals. Because of its visual complexity, the combination of traffic signals and warning signs is potentially confusing to motorists. The strobe-enhanced traffic signals present less visual clutter. In a given traffic-signal head, the strobe-enhanced traffic signal is embedded in the red LED array of the stop signal. Two strobe LED strips one horizontal and one vertical are made capable of operating separately from the rest of the red LED matrix. When no emergency vehicle is approaching, the red LED array functions as a normal stop signal: all the red LEDs are turned on and off together. When the intersection is to be preempted for an approaching emergency vehicle, only the LEDs in one of the strobe strips are lit, and are turned on in a sequence that indicates the direction of approach. For example (see figure), if an emergency vehicle approaches from the right, the strobe LEDs are lit in a sequence moving from right to left. Important to the success of strobe-enhanced traffic signals is conformance to city ordinances and close relation to pre-existing traffic standards. For instance, one key restriction is that new icons must not include arrows, so that motorists will not confuse new icons with conventional arrows that indicate allowed directions of movement. It is also critical that new displays like strobe-enhanced traffic signals be similar to displays used in traffic-control systems in large cities. For example, Charleston, South Carolina uses horizontal strobes on red traffic lights to alert motorists and thereby help motorists not to miss red lights. The one significant potential disadvantage of strobe-enhanced traffic lights is initial unfamiliarity on the part of motorists.

Energy Savings in Cellular Networks Based on Space-Time Structure of Traffic Loads

NASA Astrophysics Data System (ADS)

Sun, Jingbo; Wang, Yue; Yuan, Jian; Shan, Xiuming

Since most of energy consumed by the telecommunication infrastructure is due to the Base Transceiver Station (BTS), switching off BTSs when traffic load is low has been recognized as an effective way of saving energy. In this letter, an energy saving scheme is proposed to minimize the number of active BTSs based on the space-time structure of traffic loads as determined by principal component analysis. Compared to existing methods, our approach models traffic loads more accurately, and has a much smaller input size. As it is implemented in an off-line manner, our scheme also avoids excessive communications and computing overheads. Simulation results show that the proposed method has a comparable performance in energy savings.

Decision support tools to support the operations of traffic management centers (TMC)

DOT National Transportation Integrated Search

2011-01-31

The goal of this project is to develop decision support tools to support traffic management operations based on collected intelligent transportation system (ITS) data. The project developments are in accordance with the needs of traffic management ce...

Improving the effectiveness of traffic monitoring based on wireless location technology.

DOT National Transportation Integrated Search

2004-01-01

A fundamental requirement for effectively monitoring and operating transportation facilities is reliable, accurate data on traffic flow. The current state of the practice is to use networks of point detectors to gather information on traffic flow at ...

Dynamic traffic assignment based trailblazing guide signing for major traffic generator.

DOT National Transportation Integrated Search

2009-11-01

The placement of guide signs and the display of dynamic massage signs greatly affect drivers : understanding of the network and therefore their route choices. Most existing dynamic traffic assignment : models assume that drivers heading to a Major...

A Framework for Validating Traffic Simulation Models at the Vehicle Trajectory Level

DOT National Transportation Integrated Search

2017-03-01

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

Evaluation of the impacts of traffic states on crash risks on freeways.

PubMed

Xu, Chengcheng; Liu, Pan; Wang, Wei; Li, Zhibin

2012-07-01

The primary objective of this study is to divide freeway traffic flow into different states, and to evaluate the safety performance associated with each state. Using traffic flow data and crash data collected from a northbound segment of the I-880 freeway in the state of California, United States, K-means clustering analysis was conducted to classify traffic flow into five different states. Conditional logistic regression models using case-controlled data were then developed to study the relationship between crash risks and traffic states. Traffic flow characteristics in each traffic state were compared to identify the underlying phenomena that made certain traffic states more hazardous than others. Crash risk models were also developed for different traffic states to identify how traffic flow characteristics such as speed and speed variance affected crash risks in different traffic states. The findings of this study demonstrate that the operations of freeway traffic can be divided into different states using traffic occupancy measured from nearby loop detector stations, and each traffic state can be assigned with a certain safety level. The impacts of traffic flow parameters on crash risks are different across different traffic flow states. A method based on discriminant analysis was further developed to identify traffic states given real-time freeway traffic flow data. Validation results showed that the method was of reasonably high accuracy for identifying freeway traffic states. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Kriging based spatiotemporal approach for traffic volume data imputation

PubMed Central

Han, Lee D.; Liu, Xiaohan; Pu, Li; Chin, Shih-miao; Hwang, Ho-ling

2018-01-01

Along with the rapid development of Intelligent Transportation Systems, traffic data collection technologies have progressed fast. The emergence of innovative data collection technologies such as remote traffic microwave sensor, Bluetooth sensor, GPS-based floating car method, and automated license plate recognition, has significantly increased the variety and volume of traffic data. Despite the development of these technologies, the missing data issue is still a problem that poses great challenge for data based applications such as traffic forecasting, real-time incident detection, dynamic route guidance, and massive evacuation optimization. A thorough literature review suggests most current imputation models either focus on the temporal nature of the traffic data and fail to consider the spatial information of neighboring locations or assume the data follow a certain distribution. These two issues reduce the imputation accuracy and limit the use of the corresponding imputation methods respectively. As a result, this paper presents a Kriging based data imputation approach that is able to fully utilize the spatiotemporal correlation in the traffic data and that does not assume the data follow any distribution. A set of scenarios with different missing rates are used to evaluate the performance of the proposed method. The performance of the proposed method was compared with that of two other widely used methods, historical average and K-nearest neighborhood. Comparison results indicate that the proposed method has the highest imputation accuracy and is more flexible compared to other methods. PMID:29664928

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

PubMed

Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

2018-01-01

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

Real-time color/shape-based traffic signs acquisition and recognition system

NASA Astrophysics Data System (ADS)

Saponara, Sergio

2013-02-01

A real-time system is proposed to acquire from an automotive fish-eye CMOS camera the traffic signs, and provide their automatic recognition on the vehicle network. Differently from the state-of-the-art, in this work color-detection is addressed exploiting the HSI color space which is robust to lighting changes. Hence the first stage of the processing system implements fish-eye correction and RGB to HSI transformation. After color-based detection a noise deletion step is implemented and then, for the classification, a template-based correlation method is adopted to identify potential traffic signs, of different shapes, from acquired images. Starting from a segmented-image a matching with templates of the searched signs is carried out using a distance transform. These templates are organized hierarchically to reduce the number of operations and hence easing real-time processing for several types of traffic signs. Finally, for the recognition of the specific traffic sign, a technique based on extraction of signs characteristics and thresholding is adopted. Implemented on DSP platform the system recognizes traffic signs in less than 150 ms at a distance of about 15 meters from 640x480-pixel acquired images. Tests carried out with hundreds of images show a detection and recognition rate of about 93%.

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.

The Attention Window: A Narrative Review of Limitations and Opportunities Influencing the Focus of Attention

ERIC Educational Resources Information Center

Hüttermann, Stefanie; Memmert, Daniel

2017-01-01

Purpose: Visual attention is essential in many areas ranging from everyday life situations to the workplace. Different circumstances such as driving in traffic or participating in sports require immediate adaptation to constantly changing situations and frequently the conscious perception of 2 objects or scenes at the same time. Method: The…

Making Air Pollution Visible: A Tool for Promoting Environmental Health Literacy.

PubMed

Cleary, Ekaterina Galkina; Patton, Allison P; Wu, Hsin-Ching; Xie, Alan; Stubblefield, Joseph; Mass, William; Grinstein, Georges; Koch-Weser, Susan; Brugge, Doug; Wong, Carolyn

2017-04-12

Digital maps are instrumental in conveying information about environmental hazards geographically. For laypersons, computer-based maps can serve as tools to promote environmental health literacy about invisible traffic-related air pollution and ultrafine particles. Concentrations of these pollutants are higher near major roadways and increasingly linked to adverse health effects. Interactive computer maps provide visualizations that can allow users to build mental models of the spatial distribution of ultrafine particles in a community and learn about the risk of exposure in a geographic context. The objective of this work was to develop a new software tool appropriate for educating members of the Boston Chinatown community (Boston, MA, USA) about the nature and potential health risks of traffic-related air pollution. The tool, the Interactive Map of Chinatown Traffic Pollution ("Air Pollution Map" hereafter), is a prototype that can be adapted for the purpose of educating community members across a range of socioeconomic contexts. We built the educational visualization tool on the open source Weave software platform. We designed the tool as the centerpiece of a multimodal and intergenerational educational intervention about the health risk of traffic-related air pollution. We used a previously published fine resolution (20 m) hourly land-use regression model of ultrafine particles as the algorithm for predicting pollution levels and applied it to one neighborhood, Boston Chinatown. In designing the map, we consulted community experts to help customize the user interface to communication styles prevalent in the target community. The product is a map that displays ultrafine particulate concentrations averaged across census blocks using a color gradation from white to dark red. The interactive features allow users to explore and learn how changing meteorological conditions and traffic volume influence ultrafine particle concentrations. Users can also select from multiple map layers, such as a street map or satellite view. The map legends and labels are available in both Chinese and English, and are thus accessible to immigrants and residents with proficiency in either language. The map can be either Web or desktop based. The Air Pollution Map incorporates relevant language and landmarks to make complex scientific information about ultrafine particles accessible to members of the Boston Chinatown community. In future work, we will test the map in an educational intervention that features intergenerational colearning and the use of supplementary multimedia presentations. ©Ekaterina Galkina Cleary, Allison P Patton, Hsin-Ching Wu, Alan Xie, Joseph Stubblefield, William Mass, Georges Grinstein, Susan Koch-Weser, Doug Brugge, Carolyn Wong. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 12.04.2017.

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.

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.

Road traffic sign detection and classification from mobile LiDAR point clouds

NASA Astrophysics Data System (ADS)

Weng, Shengxia; Li, Jonathan; Chen, Yiping; Wang, Cheng

2016-03-01

Traffic signs are important roadway assets that provide valuable information of the road for drivers to make safer and easier driving behaviors. Due to the development of mobile mapping systems that can efficiently acquire dense point clouds along the road, automated detection and recognition of road assets has been an important research issue. This paper deals with the detection and classification of traffic signs in outdoor environments using mobile light detection and ranging (Li- DAR) and inertial navigation technologies. The proposed method contains two main steps. It starts with an initial detection of traffic signs based on the intensity attributes of point clouds, as the traffic signs are always painted with highly reflective materials. Then, the classification of traffic signs is achieved based on the geometric shape and the pairwise 3D shape context. Some results and performance analyses are provided to show the effectiveness and limits of the proposed method. The experimental results demonstrate the feasibility and effectiveness of the proposed method in detecting and classifying traffic signs from mobile LiDAR point clouds.

Headlamps for light based driver assistance

NASA Astrophysics Data System (ADS)

Götz, M.; Kleinkes, M.

2008-04-01

Driving at night is dangerous. Although only 25% of all driving tasks are performed at night, nearly half of all fatal accidents happen in this time. In order to increase safety when driving under poor visibility conditions, automotive front lighting systems have undergone a strong development in the last fifteen years. One important milestone was the introduction of Xenon headlamps in 1992, which provide more and brighter light for road illumination than ever before. Since then the paradigm of simply providing more light has changed toward providing optimised light distributions, which support the driver's perception. A first step in this direction was the introduction of dynamic bend lighting and cornering light in 2003. In 2006 the first full AFS headlamp (Adaptive Front Lighting System) allowed an optimised adoption of the light distribution to the driving situation. These systems use information provided by vehicle sensors and an intelligent algorithm to guide light towards those areas where needed. Nowadays, even more information about the vehicle's environment is available. Image processing systems, for example, allow to detect other traffic participants, their speed and their driving directions. In future headlamp systems these data will be used to constantly regulate the reach of the light distribution thus allowing a maximal reach without providing glare. Moreover, technologies that allow to constantly use a high-beam light distribution are under development. These systems will illuminate the whole traffic area only excluding other traffic participants. LED light sources will play a significant role in these scenarios, since they allow to precisely illuminate certain areas of the road, while neighbouring parts will be left in dark.

Will higher traffic flow lead to more traffic conflicts? A crash surrogate metric based analysis

PubMed Central

Kuang, Yan; Yan, Yadan

2017-01-01

In this paper, we aim to examine the relationship between traffic flow and potential conflict risks by using crash surrogate metrics. It has been widely recognized that one traffic flow corresponds to two distinct traffic states with different speeds and densities. In view of this, instead of simply aggregating traffic conditions with the same traffic volume, we represent potential conflict risks at a traffic flow fundamental diagram. Two crash surrogate metrics, namely, Aggregated Crash Index and Time to Collision, are used in this study to represent the potential conflict risks with respect to different traffic conditions. Furthermore, Beijing North Ring III and Next Generation SIMulation Interstate 80 datasets are utilized to carry out case studies. By using the proposed procedure, both datasets generate similar trends, which demonstrate the applicability of the proposed methodology and the transferability of our conclusions. PMID:28787022

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.

Will higher traffic flow lead to more traffic conflicts? A crash surrogate metric based analysis.

PubMed

Kuang, Yan; Qu, Xiaobo; Yan, Yadan

2017-01-01

In this paper, we aim to examine the relationship between traffic flow and potential conflict risks by using crash surrogate metrics. It has been widely recognized that one traffic flow corresponds to two distinct traffic states with different speeds and densities. In view of this, instead of simply aggregating traffic conditions with the same traffic volume, we represent potential conflict risks at a traffic flow fundamental diagram. Two crash surrogate metrics, namely, Aggregated Crash Index and Time to Collision, are used in this study to represent the potential conflict risks with respect to different traffic conditions. Furthermore, Beijing North Ring III and Next Generation SIMulation Interstate 80 datasets are utilized to carry out case studies. By using the proposed procedure, both datasets generate similar trends, which demonstrate the applicability of the proposed methodology and the transferability of our conclusions.

Road Traffic Accident Victims’ Experiences of Return to Normal Life: A Qualitative Study

PubMed Central

Pashaei Sabet, Fatemeh; Norouzi Tabrizi, Kian; Khankeh, Hamid Reza; Saadat, Soheil; Abedi, Heidar Ali; Bastami, Alireza

2016-01-01

Background Road traffic accident (RTA) victims also suffer from different types of injuries and disabilities, which can affect their quality of life. They usually face with various physical, mental, and social problems. Most traffic accident victims had difficulty to return to normal life. Objectives This study aimed to understand the experiences of return to normal life in RTA victims. Patients and Methods This qualitative study with content analysis approach was conducted on 18 Iranian patients with disability in the upper or lower limbs caused by traffic accidents, who had passed a time between 3 months till 2 years. A purposeful sampling method was applied until reaching data saturation. Data were collected using semi-structured interviews. Afterwards, the gathered data were analyzed through conventional content analysis. Results By analyzing 498 primary codes, four main categories, including supportive needs, adaptation to the new situation, seeking information, and transition from functional limitation, were extracted from traffic accident victims’ experiences of reintegration to normal life. Conclusions The results of this study may help policy-makers to take steps toward health promotion and recovery of RTA victims. Considering the results of this study, it is a need for further research to investigate RTAs victims’ needs for reintegration to home and community. Access to training and supportive facilities like strong therapeutic, nursing and social support, and the possibility to participate in self-care activities is essential for reintegration to community in RTA victims. PMID:27275399

Air pollution and survival within the Washington University-EPRI veterans cohort: risks based on modeled estimates of ambient levels of hazardous and criteria air pollutants.

PubMed

Lipfert, Frederick W; Wyzga, Ronald E; Baty, Jack D; Miller, J Philip

2009-04-01

For this paper, we considered relationships between mortality, vehicular traffic density, and ambient levels of 12 hazardous air pollutants, elemental carbon (EC), oxides of nitrogen (NOx), sulfur dioxide (SO2), and sulfate (SO4(2-)). These pollutant species were selected as markers for specific types of emission sources, including vehicular traffic, coal combustion, smelters, and metal-working industries. Pollutant exposures were estimated using emissions inventories and atmospheric dispersion models. We analyzed associations between county ambient levels of these pollutants and survival patterns among approximately 70,000 U.S. male veterans by mortality period (1976-2001 and subsets), type of exposure model, and traffic density level. We found significant associations between all-cause mortality and traffic-related air quality indicators and with traffic density per se, with stronger associations for benzene, formaldehyde, diesel particulate, NOx, and EC. The maximum effect on mortality for all cohort subjects during the 26-yr follow-up period is approximately 10%, but most of the pollution-related deaths in this cohort occurred in the higher-traffic counties, where excess risks approach 20%. However, mortality associations with diesel particulates are similar in high- and low-traffic counties. Sensitivity analyses show risks decreasing slightly over time and minor differences between linear and logarithmic exposure models. Two-pollutant models show stronger risks associated with specific traffic-related pollutants than with traffic density per se, although traffic density retains statistical significance in most cases. We conclude that tailpipe emissions of both gases and particles are among the most significant and robust predictors of mortality in this cohort and that most of those associations have weakened over time. However, we have not evaluated possible contributions from road dust or traffic noise. Stratification by traffic density level suggests the presence of response thresholds, especially for gaseous pollutants. Because of their wider distributions of estimated exposures, risk estimates based on emissions and atmospheric dispersion models tend to be more precise than those based on local ambient measurements.

Adaptive neuro fuzzy system for modelling and prediction of distance pantograph catenary in railway transportation

NASA Astrophysics Data System (ADS)

Panoiu, M.; Panoiu, C.; Lihaciu, I. L.

2018-01-01

This research presents an adaptive neuro-fuzzy system which is used in the prediction of the distance between the pantograph and contact line of the electrical locomotives used in railway transportation. In railway transportation any incident that occurs in the electrical system can have major negative effects: traffic interrupts, equipment destroying. Therefore, a prediction as good as possible of such situations is very useful. In the paper was analyzing the possibility of modeling and prediction the variation of the distance between the pantograph and the contact line using intelligent techniques

Evaluation and analysis of noise levels at traffic intersections of Nagpur city, India.

PubMed

Vijay, Ritesh; Popat, Rishabh; Pisode, Mayur; Sharma, Asheesh; Manoj, Kumar; Chakrabarti, T; Gupta, Rajesh

2013-04-01

The objective of the present study was to monitor and assess the noise levels at traffic intersections in Napgur city under heterogenic traffic activities. For this, traffic volume and noise level were measured at intersections on highways, major roads andring road during morning and evening peak hours. Traffic volume was categorized in light, medium and heavy vehicles while noise levels were measured for Lmin, Lmax, Leq , L10 and L90. Equivalent noise was observed in the range of 71.3 to 79.3 dB(A) at the traffic intersections. Due to heterogenic traffic conditions and activities at the intersection like honking, idling, gear noise, bearing noise, breaking noise, tyre-road noise and exhaust noise, no correlation was established between traffic volume and observed noise levels except West High Court road. A strong correlation was found at West High Court road due to controlled traffic flow and less impact of heavy vehicles. Impact of noisy vehicles on general traffic was also assessed at the traffic intersections based on noise pollution levels and traffic noise index. The study suggests that control measures are required at the traffic intersections to minimize noise pollution levels.

Optimal loop placement and models for length - based vehicle classification and stop - and - go traffic.

DOT National Transportation Integrated Search

2011-01-01

Inductive loops are widely used nationwide for traffic monitoring as a data source for a variety of : needs in generating traffic information for operation and planning analysis, validations of travel : demand models, freight studies, pavement design...

Effect of changing driving conditions on driver behavior towards design of a safe and efficient traffic system.

DOT National Transportation Integrated Search

2013-12-01

This simulation-based study explores the effects of different work zone configurations, varying distances : between traffic signs, traffic density and individual differences on drivers behavior. Conventional Lane : Merge (CLM) and Joint Lane Merge...

Proof of Concept for the Trajectory-Level Validation Framework for Traffic Simulation Models

DOT National Transportation Integrated Search

2017-10-30

Based on current practices, traffic simulation models are calibrated and validated using macroscopic measures such as 15-minute averages of traffic counts or average point-to-point travel times. For an emerging number of applications, including conne...

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.

Packetized Video On MAGNET

NASA Astrophysics Data System (ADS)

Lazar, Aurel A.; White, John S.

1987-07-01

Theoretical analysis of integrated local area network model of MAGNET, an integrated network testbed developed at Columbia University, shows that the bandwidth freed up during video and voice calls during periods of little movement in the images and periods of silence in the speech signals could be utilized efficiently for graphics and data transmission. Based on these investigations, an architecture supporting adaptive protocols that are dynamicaly controlled by the requirements of a fluctuating load and changing user environment has been advanced. To further analyze the behavior of the network, a real-time packetized video system has been implemented. This system is embedded in the real-time multimedia workstation EDDY, which integrates video, voice, and data traffic flows. Protocols supporting variable-bandwidth, fixed-quality packetized video transport are described in detail.

Packetized video on MAGNET

NASA Astrophysics Data System (ADS)

Lazar, Aurel A.; White, John S.

1986-11-01

Theoretical analysis of an ILAN model of MAGNET, an integrated network testbed developed at Columbia University, shows that the bandwidth freed up by video and voice calls during periods of little movement in the images and silence periods in the speech signals could be utilized efficiently for graphics and data transmission. Based on these investigations, an architecture supporting adaptive protocols that are dynamically controlled by the requirements of a fluctuating load and changing user environment has been advanced. To further analyze the behavior of the network, a real-time packetized video system has been implemented. This system is embedded in the real time multimedia workstation EDDY that integrates video, voice and data traffic flows. Protocols supporting variable bandwidth, constant quality packetized video transport are descibed in detail.

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.

LAVIA--an evaluation of the potential safety benefits of the French intelligent speed adaptation project.

PubMed

Driscoll, R; Page, Y; Lassarre, S; Ehrlich, J

2007-01-01

This paper presents the potential safety benefits of the experimental French LAVIA Intelligent Speed Adaptation system, according to road network and system mode, based on observed driving speeds, distributions of crash severity and crash injury risk. Results are given for car frontal and side impacts that together, represent 80% of all serious and fatal injuries in France. Of the three system modes tested (advisory, driver select, mandatory), our results suggest that driver select would most significantly reduce serious injuries and death. We estimate this 100% utilization of cars equipped with this type of speed adaptation system would decrease injury rates by 6% to 16% over existing conditions depending on the type of crash (frontal or side) and road environment considered. Some limitations associated with the analysis are also identified. LAVIA is the acronym for Limiteur s'Adaptant à la VItesse Autorisée, a French Intelligent Speed Adaptation (ISA) project that was set up towards the end of 1999. At the time, 1998 French national road safety statistics recorded 8437 road related deaths, a figure which had shown virtually no positive evolution since 1994. Detailed analysis of the contributory factors involved in fatal road crashes highlighted the time-honoured crash and injury causation mechanisms - alcohol, speed and seatbelts. Of the three, excessive speed (over and above the posted speed limit) was a contributory factor in half of all fatal crashes Inappropriate behaviour such as excessive speeding can be dealt with either by legislative or driver-incentive programmes. The first of these two solutions involves the introduction of new legislation and/or the enforcement of existing laws. This is the domain of Public Authorities and will not be discussed in detail here. Alternatively, incentive schemes can involve the implementation of speed related driver assistance systems, categorised according to their voluntary or mandatory character and the degree of autonomy proposed to or imposed on the driver. The LAVIA project set out to address several possible combinations of these two factors. The generic term Intelligent Speed Adaptation (ISA) encompasses a wide range of different technologies aimed at improving road safety by reducing traffic speed and homogenising traffic flow, within the limit of posted speed limits. "Fixed speed limit" systems inform the vehicle of the posted speed limit whereas "variable speed limit" systems take into account certain locations on the road network where a speed below the posted limit is desirable, such as sharp curves, pedestrian crossings or crash black spots. Taken one step further, speed limit systems may also take into account weather and traffic flow conditions. These systems are known as "dynamic speed limit" systems and benefit from real time updates for a specific location. The different ISA systems are generally characterised by the degree of freedom of choice given to the driver in moderating his or her speed. Speed limit technologies may be advisory (informing drivers of the current speed limit and speed limit changes), voluntary (allowing the driver to decide whether or not to implement speed limitation) or mandatory (imposing the current speed limit). The information supplied may be provided by way of the road infrastructure (and associated equipment), may be acquired autonomously by the vehicle or may be based on an interaction between the infrastructure and the vehicle. Even the most basic of these systems should be considered as a very useful driver aid, helping the driver to stay within the posted speed limit, avoiding "unnecessary" speeding fines through inattention, modelling driver behaviour through the long term reduction of speeds and reducing driver workload by limiting visual speedometer controls. Vehicle-based ISA systems should not be confused with internal systems. These latter systems rely upon the driver entering the desired travel speed, which is then maintained by cruise control or set as a maximum value by automatic speed regulators. Although these systems will not be discussed in detail here, it should be noted that the engine management technologies that they employ are a vital component of ISA systems.

A SPATIOTEMPORAL APPROACH FOR HIGH RESOLUTION TRAFFIC FLOW IMPUTATION

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

Han, Lee; Chin, Shih-Miao; Hwang, Ho-Ling

Along with the rapid development of Intelligent Transportation Systems (ITS), traffic data collection technologies have been evolving dramatically. The emergence of innovative data collection technologies such as Remote Traffic Microwave Sensor (RTMS), Bluetooth sensor, GPS-based Floating Car method, automated license plate recognition (ALPR) (1), etc., creates an explosion of traffic data, which brings transportation engineering into the new era of Big Data. However, despite the advance of technologies, the missing data issue is still inevitable and has posed great challenges for research such as traffic forecasting, real-time incident detection and management, dynamic route guidance, and massive evacuation optimization, because themore » degree of success of these endeavors depends on the timely availability of relatively complete and reasonably accurate traffic data. A thorough literature review suggests most current imputation models, if not all, focus largely on the temporal nature of the traffic data and fail to consider the fact that traffic stream characteristics at a certain location are closely related to those at neighboring locations and utilize these correlations for data imputation. To this end, this paper presents a Kriging based spatiotemporal data imputation approach that is able to fully utilize the spatiotemporal information underlying in traffic data. Imputation performance of the proposed approach was tested using simulated scenarios and achieved stable imputation accuracy. Moreover, the proposed Kriging imputation model is more flexible compared to current models.« less

[Traffic accidents: a qualitative approach from Campinas, São Paulo, Brazil].

PubMed

Queiroz, Marcos S; Oliveira, Patrícia C P

2002-01-01

This article takes an interdisciplinary qualitative approach to the problem of traffic accidents in Campinas, São Paulo, Brazil. The authors begin by analyzing the "municipalization" (i.e., decentralization to the municipal level) of transport and traffic management in Campinas based on social representations by members of the local government's technical staff. Data demonstrate a significant drop in traffic accident mortality in Campinas in the last ten years. The findings illustrate how new transport and traffic policies had several positive effects. Special attention is given to the objectives, strategies, and obstacles dealt with by local government in the "municipalization" of traffic. The paper concludes by emphasizing the need for specific public policies to revitalize urban mass transportation, including special traffic safety educational programs.

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

Integrating internet GPS vehicle tracking data into a bottom-up vehicular emissions inventory and atmospheric simulation in South-East, Brazil

NASA Astrophysics Data System (ADS)

Ibarra Espinosa, S.; Ynoue, R.; Giannotti, M., , Dr

2017-12-01

It has been shown the importance of emissions inventories for air quality studies and environmental planning at local, regional (REAS), hemispheric (CLRTAP) and global (IPCC) scales. It has been shown also that vehicules are becoming the most important sources in urban centers. Several efforts has been made in order to model vehicular emissions to obtain more accurate emission factors based on Vehicular Specific Power (VPS) with IVE and MOVES based on VSP, MOBILE, VERSIT and COPERT based on average speed, or ARTEMIS and HBEFA based on traffic situations. However, little effort has been made to improve traffic activity data. In this study we are proposing using a novel approach to develop vehicular emissions inventory including point data from MAPLINK a company that feeds with traffic data to Google. This includes working and transforming massive amount of data to generate traffic flow and speeds. The region of study is the south east of Brazil including São Paulo metropolitan areas. To estimate vehicular emissions we are using the open source model VEIN available at https://CRAN.R-project.org/package=vein. We generated hourly traffic between 2010-04-21 and 2010-10-22, totalizing 145 hours. This data consists GPS readings from vehicles with assurance policy, applications and other sources. This type data presents spacial bias meaning that only a part of the vehicles are tracked. We corrected this bias using the calculated speed as proxy of traffic flow using measurements of traffic flow and speed per lane made in São Paulo. Then we calibrated the total traffic estimating Fuel Consumption with VEIN and comparing Fuel Sales for the region. We estimated the hourly vehicular emissions and produced emission maps and data-bases. In addition, we simulated atmospheric simulations using WRF-Chem to identify which inventory produces better agreement with air pollutant observations. New technologies and big data provides opportunities to improve vehicular emissions inventories.

Trajectory-Oriented Approach to Managing Traffic Complexity: Trajectory Flexibility Metrics and Algorithms and Preliminary Complexity Impact Assessment

NASA Technical Reports Server (NTRS)

Idris, Husni; Vivona, Robert A.; Al-Wakil, Tarek

2009-01-01

This document describes exploratory research on a distributed, trajectory oriented approach for traffic complexity management. The approach is to manage traffic complexity based on preserving trajectory flexibility and minimizing constraints. In particular, the document presents metrics for trajectory flexibility; a method for estimating these metrics based on discrete time and degree of freedom assumptions; a planning algorithm using these metrics to preserve flexibility; and preliminary experiments testing the impact of preserving trajectory flexibility on traffic complexity. The document also describes an early demonstration capability of the trajectory flexibility preservation function in the NASA Autonomous Operations Planner (AOP) platform.

Methods and systems for detecting abnormal digital traffic

DOEpatents

Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA

2011-03-22

Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

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...

Probabilistic Predictions of Traffic Demand for En Route Sectors Based on Individual Flight Data

DOT National Transportation Integrated Search

2010-01-01

The Traffic Flow Management System (TFMS) predicts the demand for each sector, and traffic managers use these predictions to spot possible congestion and to take measures to prevent it. These predictions of sector demand, however, are currently made ...

Flow-aggregated traffic-driven label mapping in label-switching networks

NASA Astrophysics Data System (ADS)

Nagami, Kenichi; Katsube, Yasuhiro; Esaki, Hiroshi; Nakamura, Osamu

1998-12-01

Label switching technology enables high performance, flexible, layer-3 packet forwarding based on the fixed length label information mapped to the layer-3 packet stream. A Label Switching Router (LSR) forwards layer-3 packets based on their label information mapped to the layer-3 address information as well as their layer-3 address information. This paper evaluates the required number of labels under traffic-driven label mapping policy using the real backbone traffic traces. The evaluation shows that the label mapping policy requires a large number of labels. In order to reduce the required number of labels, we propose a label mapping policy which is a traffic-driven label mapping for the traffic toward the same destination network. The evaluation shows that the proposed label mapping policy requires only about one tenth as many labels compared with the traffic-driven label mapping for the host-pair packet stream,and the topology-driven label mapping for the destination network packet stream.

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.

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.

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.

A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

NASA Astrophysics Data System (ADS)

Yang, Wei; Hall, Trevor J.

2013-12-01

The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

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

A refined and dynamic cellular automaton model for pedestrian-vehicle mixed traffic flow

NASA Astrophysics Data System (ADS)

Liu, Mianfang; Xiong, Shengwu

2016-12-01

Mixed traffic flow sharing the “same lane” and having no discipline on road is a common phenomenon in the developing countries. For example, motorized vehicles (m-vehicles) and nonmotorized vehicles (nm-vehicles) may share the m-vehicle lane or nm-vehicle lane and pedestrians may share the nm-vehicle lane. Simulating pedestrian-vehicle mixed traffic flow consisting of three kinds of traffic objects: m-vehicles, nm-vehicles and pedestrians, can be a challenge because there are some erratic drivers or pedestrians who fail to follow the lane disciplines. In the paper, we investigate various moving and interactive behavior associated with mixed traffic flow, such as lateral drift including illegal lane-changing and transverse crossing different lanes, overtaking and forward movement, and propose some new moving and interactive rules for pedestrian-vehicle mixed traffic flow based on a refined and dynamic cellular automaton (CA) model. Simulation results indicate that the proposed model can be used to investigate the traffic flow characteristic in a mixed traffic flow system and corresponding complicated traffic problems, such as, the moving characteristics of different traffic objects, interaction phenomenon between different traffic objects, traffic jam, traffic conflict, etc., which are consistent with the actual mixed traffic system. Therefore, the proposed model provides a solid foundation for the management, planning and evacuation of the mixed traffic flow.

Development of a traffic noise prediction model for an urban environment.

PubMed

Sharma, Asheesh; Bodhe, G L; Schimak, G

2014-01-01

The objective of this study is to develop a traffic noise model under diverse traffic conditions in metropolitan cities. The model has been developed to calculate equivalent traffic noise based on four input variables i.e. equivalent traffic flow (Q e ), equivalent vehicle speed (S e ) and distance (d) and honking (h). The traffic data is collected and statistically analyzed in three different cases for 15-min during morning and evening rush hours. Case I represents congested traffic where equivalent vehicle speed is <30 km/h while case II represents free-flowing traffic where equivalent vehicle speed is >30 km/h and case III represents calm traffic where no honking is recorded. The noise model showed better results than earlier developed noise model for Indian traffic conditions. A comparative assessment between present and earlier developed noise model has also been presented in the study. The model is validated with measured noise levels and the correlation coefficients between measured and predicted noise levels were found to be 0.75, 0.83 and 0.86 for case I, II and III respectively. The noise model performs reasonably well under different traffic conditions and could be implemented for traffic noise prediction at other region as well.

32 CFR 634.52 - Search incident to impoundment based on criminal activity.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... This situation could also arise during cases of intoxicated driving or traffic accidents in which the... (CONTINUED) LAW ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Impounding... general situations: (a) The owner or operator is not present. This situation could arise during traffic...

Stationary LiDAR for traffic and safety applications - vehicles interpretation and tracking.

DOT National Transportation Integrated Search

2014-01-01

The goal of the T-Scan project is to develop a data processing module for a novel LiDAR-based traffic scanner to collect highly accurate microscopic traffic data at road intersections. : T-Scan uses Light Detection and Ranging (LiDAR) technology that...

Development of prototype decision support systems for real-time freeway traffic routing. Volume I.

DOT National Transportation Integrated Search

1998-01-01

For a traffic management system (TMS) to improve traffic flow, TMS operators must develop effective routing strategies based on the data collected by the system. The purpose of this research was to build prototype decision support systems (DSS) for t...

Improved characterization of truck traffic volumes and axle loads for mechanistic-empirical pavement design : [executive summary report].

DOT National Transportation Integrated Search

2012-12-01

Traffic is one of the primary inputs in pavement design. Traditional pavement design procedures account for traffic using the equivalent single axle loads (ESALs) accumulated during the life of the pavement structure. This procedure is based on co...

Improving travel times for emergency response vehicles : traffic control strategies based on connected vehicles technologies.

DOT National Transportation Integrated Search

2014-09-01

This research is focused on developing and evaluating new traffic control strategies to enable emergency response vehicles : (EVs) to travel in transportation networks as quickly as possible while the disruption to the rest of the traffic is kept to ...

[Risk factors for road traffic injury in agricultural vehicle drivers].

PubMed

Cui, M J; Chen, Y; Li, Y; Hu, J; Zhang, X J

2017-08-20

Objective: To examine the risk factors for road traffic injury in agricultural vehicle drivers. Methods: A total of 103 drivers (who had suffered agricultural vehicle road traffic injury within the past year based on the road traffic injury registrar from the Traffic Management Bureau) who were involved in the annual agricultural vehicle inspection from December 2014 to January 2015 were randomly sampled from the Yixing Agricultural Vehicle Station as the case group for this study. Based on a 1∶2 assignment ratio and matched for sex, age, and education, a total of 206 drivers who had not suffered any agricultural vehicle road traffic injury within the past year were selected as the control group. The general information, vehicle information, driving information, driving behavior, and accident details of the agricultural vehicle drivers were analyzed. Results: The incidence rate of road traffic injury was 7.24% given the 103 agricultural vehicle drivers who had suffered agricultural vehicle road traffic injury in the past year. Univariate logistic regression analysis showed that drinking, debt, pressure, history of car accident, history of drunk driving, smoking and phone use during driving, fatigue driving, and driving with illness were the risk factors for road traffic injury in agricultural vehicle drivers ( OR =2.332, 2.429, 19.778, 5.589, 8.517, 2.125, 3.203, 10.249 and 5.639, respectively) . Multivariate logistic regression analysis also demonstrated that pressure, history of car accident, history of drunk driving, fatigue driving, and driving with illness were the risk factors for road traffic injury in agricultural vehicle drivers ( OR =12.139, 11.184, 6.729, 5.939, and 6.544, respectively) . Conclusion: Pressure, history of car accident, history of drunk driving, fatigue driving, and driving with illness are the major risk factors for road traffic injury in agricultural vehicle drivers.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Comparison of two MAC protocols based on LEO satellite networks

NASA Astrophysics Data System (ADS)

Guan, Mingxiang; Wang, Ruichun

2009-12-01

With the development of LEO satellite communication, it is the basic requirement that various kinds of services will be provided. Considering that weak channel collision detection ability, long propagation delay and heavy load in LEO satellite communication system, a valid adaptive access control protocol APRMA is proposed. Different access probability functions for different services are obtained and appropriate access probabilities for voice and data users are updated slot by slot based on the estimation of the voice traffic and the channel status. Finally simulation results demonstrate that the performance of system is improved by the APRMA compared with the conventional PRMA, with an acceptable trade-off between QoS of voice and delay of data. Also the APRMA protocol will be suitable for HAPS (high altitude platform station) with the characters of weak channel collision detection ability, long propagation delay and heavy load.

Hoarseness and vocal tract discomfort and associated risk factors in air traffic controllers.

PubMed

Korn, Gustavo Polacow; Villar, Anna Carolina; Azevedo, Renata Rangel

2018-04-05

An air traffic controller is a professional who performs air traffic control functions in air traffic control units and is responsible for controlling the various stages of a flight. To compare hoarseness and vocal tract discomfort and their risk factors among air traffic controllers in the approach control of São Paulo. In a cross-sectional survey, a voice self-evaluation adapted from to self-evaluation prepared by the Brazilian Ministry of Labor for teachers was administered to 76 air traffic controllers at approach control of São Paulo, Brazil. The percentage of hoarseness and vocal tract discomfort was 19.7% and 38.2%, respectively. In relation to air pollution, the percentages of hoarseness and vocal tract discomfort were higher among those who consider their working environment to be intolerable than among those in a comfortable or disturbing environment. The percentage of hoarseness was higher among those who seek medical advice due to vocal complaints and among those who experience difficulty using their voice at work than among those who experience mild or no difficulty. The percentage of vocal tract discomfort was higher among those in a very tense and stressful environment than among those who consider their work environment to be mild or moderately tense and stressful. The percentage of vocal tract discomfort was higher among those who describe themselves as very tense and stressed or tense and stressed than among those who describe themselves as calm. Additionally, the percentage of vocal tract discomfort was higher among those who care about their health. Among air traffic controllers, the percentage of vocal tract discomfort was almost twice that of hoarseness. Both symptoms are prevalent among air traffic controllers who considered their workplace intolerable in terms of air pollution. Vocal tract discomfort was related to a tense and stressful environment, and hoarseness was related to difficulty using the voice at work. Copyright © 2018 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

The consequences of an increase in heavy goods vehicles for passenger car drivers' mental workload and behaviour: a simulator study.

PubMed

de Waard, Dick; Kruizinga, Anje; Brookhuis, Karel A

2008-03-01

The effects of an increase in Heavy Goods Vehicles (HGVs) on merging behaviour and on mental workload of motorists during filtering in and out of traffic were studied. Participants drove in a driving simulator in a total of 12 conditions; twice in each of two weather conditions and in three traffic conditions. The weather conditions were clear weather and foggy weather. The traffic conditions were without HGVs (i.e. only private cars), the current mix of HGVs and private cars, and a condition with a 70% increase of HGVs leading to an HGV column in the slow lane. The focus of the study was on assessing effects on behaviour and mental workload during filtering into traffic, and during exiting from the motorway. During the experiment driving performance was registered, behaviour was observed, self reports were collected, and the participant's heart rate was recorded. The results showed that directly after filtering into traffic the variation in driving speed increased and the minimum time headway decreased with an increase in the proportion of HGVs. Joining motorway traffic was considered to involve greater effort and risk in the condition with a column of HGVs. The effects of the conditions on heart rate are less clear, although the moment when the participants joined the traffic is clearly visible. The effects of weather conditions were limited, drivers adapting their driving behaviour in adverse weather by reducing speed. To exit the motorway is not a difficult manoeuvre. For that reason the lane change from the left hand to the right hand lane that preceded the exit was analysed. Although increased mental effort was reported and the lane change was visible in the heart rate record, no critical changes as a result of increase in proportion of HGVs were found for this manoeuvre. However, in the condition with a column of HGVs, the exit that had to be taken was most frequently missed as HGVs obstructed the view of the exit signs. It is concluded that an increase in HGVs will make merging into traffic more mentally demanding and will decrease safety margins.