Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

NASA Astrophysics Data System (ADS)

Li, Ziyu; Bi, Jun; Li, Zhiyin

2017-12-01

Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

Using temporal detrending to observe the spatial correlation of traffic.

PubMed

Ermagun, Alireza; Chatterjee, Snigdhansu; Levinson, David

2017-01-01

This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis-St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models.

Using temporal detrending to observe the spatial correlation of traffic

PubMed Central

2017-01-01

This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis—St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models. PMID:28472093

North Carolina forecasts for truck traffic

DOT National Transportation Integrated Search

2006-07-01

North Carolina has experienced significant increases in truck traffic on many of its highways. Yet, current NCDOT : project-level highway traffic forecasts do not appropriately capture anticipated truck traffic growth. NCDOT : methods forecast total ...

Traffic flow forecasting using approximate nearest neighbor nonparametric regression

DOT National Transportation Integrated Search

2000-12-01

The purpose of this research is to enhance nonparametric regression (NPR) for use in real-time systems by first reducing execution time using advanced data structures and imprecise computations and then developing a methodology for applying NPR. Due ...

Traffic forecasting report : 2007.

DOT National Transportation Integrated Search

2008-05-01

This is the sixth edition of the Traffic Forecasting Report (TFR). This edition of the TFR contains the latest (predominantly 2007) forecasting/modeling data as follows: : Functional class average traffic volume growth rates and trends : Vehi...

An investigation into incident duration forecasting for FleetForward

DOT National Transportation Integrated Search

2000-08-01

Traffic condition forecasting is the process of estimating future traffic conditions based on current and archived data. Real-time forecasting is becoming an important tool in Intelligent Transportation Systems (ITS). This type of forecasting allows ...

A retrospective evaluation of traffic forecasting techniques.

DOT National Transportation Integrated Search

2016-08-01

Traffic forecasting techniquessuch as extrapolation of previous years traffic volumes, regional travel demand models, or : local trip generation rateshelp planners determine needed transportation improvements. Thus, knowing the accuracy of t...

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

Studies of air traffic forecasts, airspace load and the effect of ADS-B via satellites on flight times

NASA Astrophysics Data System (ADS)

Zhong, Z. W.; Ridhwan Salleh, Saiful; Chow, W. X.; Ong, Z. M.

2016-10-01

Air traffic forecasting is important as it helps stakeholders to plan their budgets and facilities. Thus, three most commonly used forecasting models were compared to see which model suited the air passenger traffic the best. General forecasting equations were also created to forecast the passenger traffic. The equations could forecast around 6.0% growth from 2015 onwards. Another study sought to provide an initial work for determining a theoretical airspace load with relevant calculations. The air traffic was simulated to investigate the current airspace load. Logical and reasonable results were obtained from the modelling and simulations. The current utilization percentages for airspace load per hour and the static airspace load in the interested airspace were found to be 6.64% and 11.21% respectively. Our research also studied how ADS-B would affect the time taken for aircraft to travel. 6000 flights departing from and landing at the airport were studied. New flight plans were simulated with improved flight paths due to the implementation of ADS-B, and flight times of all studied flights could be improved.

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

NASA Technical Reports Server (NTRS)

Peters, Mark; Boisvert, Ben; Escala, Diego

2009-01-01

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Future Air Traffic Growth and Schedule Model, Supplement

NASA Technical Reports Server (NTRS)

Kimmel, William M. (Technical Monitor); Smith, Jeremy C.; Dollyhigh, Samuel M.

2004-01-01

The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

Techniques for Forecasting Air Passenger Traffic

NASA Technical Reports Server (NTRS)

Taneja, N.

1972-01-01

The basic techniques of forecasting the air passenger traffic are outlined. These techniques can be broadly classified into four categories: judgmental, time-series analysis, market analysis and analytical. The differences between these methods exist, in part, due to the degree of formalization of the forecasting procedure. Emphasis is placed on describing the analytical method.

Integrated risk/cost planning models for the US Air Traffic system

NASA Technical Reports Server (NTRS)

Mulvey, J. M.; Zenios, S. A.

1985-01-01

A prototype network planning model for the U.S. Air Traffic control system is described. The model encompasses the dual objectives of managing collision risks and transportation costs where traffic flows can be related to these objectives. The underlying structure is a network graph with nonseparable convex costs; the model is solved efficiently by capitalizing on its intrinsic characteristics. Two specialized algorithms for solving the resulting problems are described: (1) truncated Newton, and (2) simplicial decomposition. The feasibility of the approach is demonstrated using data collected from a control center in the Midwest. Computational results with different computer systems are presented, including a vector supercomputer (CRAY-XMP). The risk/cost model has two primary uses: (1) as a strategic planning tool using aggregate flight information, and (2) as an integrated operational system for forecasting congestion and monitoring (controlling) flow throughout the U.S. In the latter case, access to a supercomputer is required due to the model's enormous size.

Application of Artificial Neural Networks and Singular-Spectral Analysis in Forecasting the Daily Traffic in the Moscow Metro

NASA Astrophysics Data System (ADS)

Ivanov, Victor; Osetrov, Evgenii

2018-02-01

In this paper, we investigate the possibility of applying various approaches to solving the problem of medium-term forecasting of daily passenger traffic volumes in the Moscow metro (MM): 1) on the basis of artificial neural networks (ANN); 2) using the singular-spectral analysis implemented in the package "Caterpillar"-SSA; 3) sharing the ANN and the "Caterpillar"-SSA approach. We demonstrate that the developed methods and algorithms allow us to conduct medium-term forecasting of passenger traffic in the MM with reasonable accuracy.

Airfreight forecasting methodology and results

NASA Technical Reports Server (NTRS)

1978-01-01

A series of econometric behavioral equations was developed to explain and forecast the evolution of airfreight traffic demand for the total U.S. domestic airfreight system, the total U.S. international airfreight system, and the total scheduled international cargo traffic carried by the top 44 foreign airlines. The basic explanatory variables used in these macromodels were the real gross national products of the countries involved and a measure of relative transportation costs. The results of the econometric analysis reveal that the models explain more than 99 percent of the historical evolution of freight traffic. The long term traffic forecasts generated with these models are based on scenarios of the likely economic outlook in the United States and 31 major foreign countries.

Future Air Traffic Growth and Schedule Model User's Guide

NASA Technical Reports Server (NTRS)

Kimmel, William M. (Technical Monitor); Smith, Jeremy C.; Dollyhigh, Samuel M.

2004-01-01

The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

Forecasting short-term data center network traffic load with convolutional neural networks.

PubMed

Mozo, Alberto; Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution.

Forecasting short-term data center network traffic load with convolutional neural networks

PubMed Central

Ordozgoiti, Bruno; Gómez-Canaval, Sandra

2018-01-01

Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution. PMID:29408936

Guidelines for project-level traffic forecasting for Hawaii Department of Transportation.

DOT National Transportation Integrated Search

2015-12-01

These guidelines describe both best practice and acceptable practice for performing project-level traffic : forecasts for the State of Hawaii. The guidelines describe a number of techniques and options that are all : acceptable within their intended ...

Forecasting the daily electricity consumption in the Moscow region using artificial neural networks

NASA Astrophysics Data System (ADS)

Ivanov, V. V.; Kryanev, A. V.; Osetrov, E. S.

2017-07-01

In [1] we demonstrated the possibility in principle for short-term forecasting of daily volumes of passenger traffic in the Moscow metro with the help of artificial neural networks. During training and predicting, a set of the factors that affect the daily passenger traffic in the subway is passed to the input of the neural network. One of these factors is the daily power consumption in the Moscow region. Therefore, to predict the volume of the passenger traffic in the subway, we must first to solve the problem of forecasting the daily energy consumption in the Moscow region.

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.

Urban pavement surface temperature. Comparison of numerical and statistical approach

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Use of the Box and Jenkins time series technique in traffic forecasting

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

Nihan, N.L.; Holmesland, K.O.

The use of recently developed time series techniques for short-term traffic volume forecasting is examined. A data set containing monthly volumes on a freeway segment for 1968-76 is used to fit a time series model. The resultant model is used to forecast volumes for 1977. The forecast volumes are then compared with actual volumes in 1977. Time series techniques can be used to develop highly accurate and inexpensive short-term forecasts. The feasibility of using these models to evaluate the effects of policy changes or other outside impacts is considered. (1 diagram, 1 map, 14 references,2 tables)

Cloud-based large-scale air traffic flow optimization

NASA Astrophysics Data System (ADS)

Cao, Yi

The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model that can be used for both offline historical traffic data analysis and online traffic flow optimization. It provides an efficient and robust platform for easy deployment and implementation. A small cloud consisting of five workstations was configured and used to demonstrate the advantages of cloud computing in dealing with large-scale parallelizable traffic problems.

Forecasting new product diffusion using both patent citation and web search traffic.

PubMed

Lee, Won Sang; Choi, Hyo Shin; Sohn, So Young

2018-01-01

Accurate demand forecasting for new technology products is a key factor in the success of a business. We propose a way to forecasting a new product's diffusion through technology diffusion and interest diffusion. Technology diffusion and interest diffusion are measured by the volume of patent citations and web search traffic, respectively. We apply the proposed method to forecast the sales of hybrid cars and industrial robots in the US market. The results show that that technology diffusion, as represented by patent citations, can explain long-term sales for hybrid cars and industrial robots. On the other hand, interest diffusion, as represented by web search traffic, can help to improve the predictability of market sales of hybrid cars in the short-term. However, interest diffusion is difficult to explain the sales of industrial robots due to the different market characteristics. Finding indicates our proposed model can relatively well explain the diffusion of consumer goods.

Traffic operational evaluation of traffic impact analysis (TIA) case sites.

DOT National Transportation Integrated Search

2010-09-22

This report summarizes traffic operational evaluation of six select traffic impact analysis (TIA) case sites and the effectiveness of forecasting methods used in TIA studies. Six TIA case sites comprising 15 signalized intersections and 2 unsignalize...

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

An Enhanced Convective Forecast (ECF) for the New York TRACON Area

NASA Technical Reports Server (NTRS)

Wheeler, Mark; Stobie, James; Gillen, Robert; Jedlovec, Gary; Sims, Danny

2008-01-01

In an effort to relieve summer-time congestion in the NY Terminal Radar Approach Control (TRACON) area, the FAA is testing an enhanced convective forecast (ECF) product. The test began in June 2008 and is scheduled to run through early September. The ECF is updated every two hours, right before the Air Traffic Control System Command Center (ATCSCC) national planning telcon. It is intended to be used by traffic managers throughout the National Airspace System (NAS) and airlines dispatchers to supplement information from the Collaborative Convective Forecast Product (CCFP) and the Corridor Integrated Weather System (CIWS). The ECF begins where the current CIWS forecast ends at 2 hours and extends out to 12 hours. Unlike the CCFP it is a detailed deterministic forecast with no aerial coverage limits. It is created by an ENSCO forecaster using a variety of guidance products including, the Weather Research and Forecast (WRF) model. This is the same version of the WRF that ENSCO runs over the Florida peninsula in support of launch operations at the Kennedy Space Center. For this project, the WRF model domain has been shifted to the Northeastern US. Several products from the NASA SPoRT group are also used by the ENSCO forecaster. In this paper we will provide examples of the ECF products and discuss individual cases of traffic management actions using ECF guidance.

GIS and Transportation Planning

DOT National Transportation Integrated Search

1998-09-16

Two main objectives of transportation planning are to simulate the current : traffic volume and to forecast the future traffic volume on a transportation : network. Traffic demand modeling typically consists of the following : tasks (1)defining traff...

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...

Information Requirements for Supervisory Air Traffic Controllers in Support of a Wake Vortex Departure System

NASA Technical Reports Server (NTRS)

Lohr, Gary W.; Williams, Daniel M.; Trujillo, Anna C.

2008-01-01

Closely Space Parallel Runway (CSPR) configurations are capacity limited for departures due to the requirement to apply wake vortex separation standards from traffic departing on the adjacent parallel runway. To mitigate the effects of this constraint, a concept focusing on wind dependent departure operations has been developed, known as the Wake Turbulence Mitigation for Departures (WTMD). This concept takes advantage of the fact that crosswinds of sufficient velocity blow wakes generated by aircraft departing from the downwind runway away from the upwind runway. Consequently, under certain conditions, wake separations on the upwind runway would not be required based on wakes generated by aircraft on the downwind runway, as is currently the case. It follows that information requirements, and sources for this information, would need to be determined for airport traffic control tower (ATCT) supervisory personnel who would be charged with decisions regarding use of the procedure. To determine the information requirements, data were collected from ATCT supervisors and controller-in-charge qualified individuals at Lambert-St. Louis International Airport (STL) and George Bush Houston Intercontinental Airport (IAH). STL and IAH were chosen as data collection sites based on the implementation of a WTMD prototype system, operating in shadow mode, at these locations. The 17 total subjects (STL: 5, IAH: 12) represented a broad-base of air traffic experience. Results indicated that the following information was required to support the conduct of WTMD operations: current and forecast weather information, current and forecast traffic demand and traffic flow restrictions, and WTMD System status information and alerting. Subjects further indicated that the requisite information is currently available in the tower cab with the exception of the WTMD status and alerting. Subjects were given a demonstration of a display supporting the prototype systems and unanimously stated that the WTMD status information they felt important was represented. Overwhelmingly, subjects felt that approving, monitoring and terminating the WTMD procedure could be integrated into their supervisory workload.

Forecasting new product diffusion using both patent citation and web search traffic

PubMed Central

Lee, Won Sang; Choi, Hyo Shin

2018-01-01

Accurate demand forecasting for new technology products is a key factor in the success of a business. We propose a way to forecasting a new product’s diffusion through technology diffusion and interest diffusion. Technology diffusion and interest diffusion are measured by the volume of patent citations and web search traffic, respectively. We apply the proposed method to forecast the sales of hybrid cars and industrial robots in the US market. The results show that that technology diffusion, as represented by patent citations, can explain long-term sales for hybrid cars and industrial robots. On the other hand, interest diffusion, as represented by web search traffic, can help to improve the predictability of market sales of hybrid cars in the short-term. However, interest diffusion is difficult to explain the sales of industrial robots due to the different market characteristics. Finding indicates our proposed model can relatively well explain the diffusion of consumer goods. PMID:29630616

Satellite provided customer premise services: A forecast of potential domestic demand through the year 2000. Volume 3: Appendices

NASA Technical Reports Server (NTRS)

Kratochvil, D.; Bowyer, J.; Bhushan, C.; Steinnagel, K.; Kaushal, D.; Al-Kinani, G.

1983-01-01

Voice applications, data applications, video applications, impacted baseline forecasts, market distribution, potential CPS (customers premises services) user classes, net long haul forecasts, CPS cost analysis, overall satellite forecast, CPS satellite market, Ka-band CPS satellite forecast, nationwide traffic distribution model, and intra-urban topology are discussed.

Satellite provided customer premise services: A forecast of potential domestic demand through the year 2000. Volume 3: Appendices

NASA Astrophysics Data System (ADS)

Kratochvil, D.; Bowyer, J.; Bhushan, C.; Steinnagel, K.; Kaushal, D.; Al-Kinani, G.

1983-08-01

Voice applications, data applications, video applications, impacted baseline forecasts, market distribution, potential CPS (customers premises services) user classes, net long haul forecasts, CPS cost analysis, overall satellite forecast, CPS satellite market, Ka-band CPS satellite forecast, nationwide traffic distribution model, and intra-urban topology are discussed.

A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality

PubMed Central

Yousefzadeh-Chabok, Shahrokh; Ranjbar-Taklimie, Fatemeh; Malekpouri, Reza; Razzaghi, Alireza

2016-01-01

Background Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. Objectives This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. Materials and Methods In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. Results The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. Conclusions There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents. PMID:27800467

A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality.

PubMed

Yousefzadeh-Chabok, Shahrokh; Ranjbar-Taklimie, Fatemeh; Malekpouri, Reza; Razzaghi, Alireza

2016-09-01

Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents.

Algorithms for constructing optimal paths and statistical analysis of passenger traffic

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

First Coast Guard district traffic model report

DOT National Transportation Integrated Search

1997-11-01

The purpose of this report was to describe the methodology used in developing the First Coast Guard District (CGD1) Traffic Model and to document the potential National Distress System (NDS) voice and data traffic forecasted for the year 2001. The ND...

Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model.

PubMed

Zhang, Xujun; Pang, Yuanyuan; Cui, Mengjing; Stallones, Lorann; Xiang, Huiyun

2015-02-01

Road traffic injuries have become a major public health problem in China. This study aimed to develop statistical models for predicting road traffic deaths and to analyze seasonality of deaths in China. A seasonal autoregressive integrated moving average (SARIMA) model was used to fit the data from 2000 to 2011. Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were used to evaluate the constructed models. Autocorrelation function and partial autocorrelation function of residuals and Ljung-Box test were used to compare the goodness-of-fit between the different models. The SARIMA model was used to forecast monthly road traffic deaths in 2012. The seasonal pattern of road traffic mortality data was statistically significant in China. SARIMA (1, 1, 1) (0, 1, 1)12 model was the best fitting model among various candidate models; the Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were -483.679, -475.053, and 4.937, respectively. Goodness-of-fit testing showed nonautocorrelations in the residuals of the model (Ljung-Box test, Q = 4.86, P = .993). The fitted deaths using the SARIMA (1, 1, 1) (0, 1, 1)12 model for years 2000 to 2011 closely followed the observed number of road traffic deaths for the same years. The predicted and observed deaths were also very close for 2012. This study suggests that accurate forecasting of road traffic death incidence is possible using SARIMA model. The SARIMA model applied to historical road traffic deaths data could provide important evidence of burden of road traffic injuries in China. Copyright © 2015 Elsevier Inc. All rights reserved.

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.

PubMed

Barba, Lida; Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT.

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain

PubMed Central

Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT. PMID:28261267

Analysis and Classification of Traffic in Wireless Sensor Network

DTIC Science & Technology

2007-03-01

34 1. Hurst Parameter ................................................................................35 2. Self-Similarity...traffic is self-similar, buffer size can be better designed from the forecasted traffic workload. 1. Hurst Parameter To determine the extent of self...similarity in WSN traffic, the Hurst parameter, H, is used. H also calculates the length of the long range dependence of a stochastic process. If H

Convective Weather Avoidance with Uncertain Weather Forecasts

NASA Technical Reports Server (NTRS)

Karahan, Sinan; Windhorst, Robert D.

2009-01-01

Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

High-Speed Civil Transport Forecast: Simulated Airlines Scenarios for Mach 1.6, Mach 2.0, and Mach 2.4 Configurations for Year 2015

NASA Technical Reports Server (NTRS)

Metwally, Munir

1996-01-01

The report describes the development of a database of fuel burn and emissions from projected High Speed Civil Transport (HSCT) fleets that reflect actual airlines' networks, operational requirement, and traffic flow as operated by simulated world wide airlines for Mach 1.6, 2.0, and 2.4 HSCT configurations. For the year 2015, McDonnell Douglas Corporation created two supersonic commercial air traffic networks consisting of origin-destination city pair routes and associated traffic levels. The first scenario represented a manufacturing upper limit producible HSCT fleet availability by year 2015. The fleet projection of the Mach 2.4 configuration for this scenario was 1059 units with a traffic capture of 70 percent. The second scenario focused on the number of units that can minimally be produced by the year 2015. Using realistic production rates, the HSCT fleet projection amounts to 565 units. The traffic capture associated with this fleet was estimated at 40 percent. The airlines network was extracted from the actual networks of 21 major world airlines. All the routes were screened for suitability for HSCT operations. The route selection criteria included great circle distance, difference between flight path distance and great circle distance to avoid overland operations, and potential flight frequency.

Air Traffic Forecasting at the Port Authority of New York and New Jersey

NASA Technical Reports Server (NTRS)

Augustine, J. G.

1972-01-01

Procedures for conducting air traffic forecasts with specific application to the Port Authority of New York and New Jersey are discussed. The procedure relates air travel growth to detailed socio-economic and demographic characteristics of the U.S. population rather than to aggregate economic data such as Gross National Product, personal income, and industrial production. Charts are presented to show the relationship between various selected characteristics and the use of air transportation facilities.

[Development of forecasting models for fatal road traffic injuries].

PubMed

Tan, Aichun; Tian, Danping; Huang, Yuanxiu; Gao, Lin; Deng, Xin; Li, Li; He, Qiong; Chen, Tianmu; Hu, Guoqing; Wu, Jing

2014-02-01

To develop the forecasting models for fatal road traffic injuries and to provide evidence for predicting the future trends on road traffic injuries. Data on the mortality of road traffic injury including factors as gender and age in different countries, were obtained from the World Health Organization Mortality Database. Other information on GDP per capita, urbanization, motorization and education were collected from online resources of World Bank, WHO, the United Nations Population Division and other agencies. We fitted logarithmic models of road traffic injury mortality by gender and age group, including predictors of GDP per capita, urbanization, motorization and education. Sex- and age-specific forecasting models developed by WHO that including GDP per capita, education and time etc. were also fitted. Coefficient of determination(R(2)) was used to compare the performance between our modes and WHO models. 2 626 sets of data were collected from 153 countries/regions for both genders, between 1965 and 2010. The forecasting models of road traffic injury mortality based on GDP per capita, motorization, urbanization and education appeared to be statistically significant(P < 0.001), and the coefficients of determination for males at the age groups of 0-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65+ were 22.7% , 31.1%, 51.8%, 52.3%, 44.9%, 41.8%, 40.1%, 25.5%, respectively while the coefficients for these age groups in women were 22.9%, 32.6%, 51.1%, 49.3%, 41.3%, 35.9%, 30.7%, 20.1%, respectively. The WHO models that were based on the GDP per capita, education and time variables were statistically significant (P < 0.001)and the coefficients of determination were 14.9% , 22.0%, 31.5%, 33.1% , 30.7%, 28.5%, 27.7% and 17.8% for males, but 14.1%, 20.6%, 30.4%, 31.8%, 26.7%, 24.3%, 17.3% and 8.8% for females, respectively. The forecasting models that we developed seemed to be better than those developed by WHO.

Socioeconomic Forecasting : [Technical Summary

DOT National Transportation Integrated Search

2012-01-01

Because the traffic forecasts produced by the Indiana : Statewide Travel Demand Model (ISTDM) are driven by : the demographic and socioeconomic inputs to the model, : particular attention must be given to obtaining the most : accurate demographic and...

Vehicular Traffic Flow Theory and Tunnel Traffic Flow Measurements

DOT National Transportation Integrated Search

1971-06-01

Vehicular traffic flow has been investigated theoretically and experimentally in order that peak hour collective traffic flow dynamics can be understood and that the peak hour flow through the Callahan Tunnel can be improved by means of traffic flow ...

Prediction of Weather Impacted Airport Capacity using Ensemble Learning

NASA Technical Reports Server (NTRS)

Wang, Yao Xun

2011-01-01

Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.

Air Traffic Demand Estimates for 1995

DOT National Transportation Integrated Search

1975-04-01

The forecasts provide a range of reasonable 1995 activity levels for analyzing and comparing cost and performance characteristics of future air traffic management system concept alternatives. High and low estimates of the various demand measures are ...

Defining the drivers for accepting decision making automation in air traffic management.

PubMed

Bekier, Marek; Molesworth, Brett R C; Williamson, Ann

2011-04-01

Air Traffic Management (ATM) operators are under increasing pressure to improve the efficiency of their operation to cater for forecasted increases in air traffic movements. One solution involves increasing the utilisation of automation within the ATM system. The success of this approach is contingent on Air Traffic Control Operators' (ATCOs) willingness to accept increased levels of automation. The main aim of the present research was to examine the drivers underpinning ATCOs' willingness to accept increased utilisation of automation within their role. Two fictitious scenarios involving the application of two new automated decision-making tools were created. The results of an online survey revealed traditional predictors of automation acceptance such as age, trust and job satisfaction explain between 4 and 7% of the variance. Furthermore, these predictors varied depending on the purpose in which the automation was to be employed. These results are discussed from an applied and theoretical perspective. STATEMENT OF RELEVANCE: Efficiency improvements in ATM are required to cater for forecasted increases in air traffic movements. One solution is to increase the utilisation of automation within Air Traffic Control. The present research examines the drivers underpinning air traffic controllers' willingness to accept increased levels of automation in their role.

Interaction of Airspace Partitions and Traffic Flow Management Delay

NASA Technical Reports Server (NTRS)

Palopo, Kee; Chatterji, Gano B.; Lee, Hak-Tae

2010-01-01

To ensure that air traffic demand does not exceed airport and airspace capacities, traffic management restrictions, such as delaying aircraft on the ground, assigning them different routes and metering them in the airspace, are implemented. To reduce the delays resulting from these restrictions, revising the partitioning of airspace has been proposed to distribute capacity to yield a more efficient airspace configuration. The capacity of an airspace partition, commonly referred to as a sector, is limited by the number of flights that an air traffic controller can safely manage within the sector. Where viable, re-partitioning of the airspace distributes the flights over more efficient sectors and reduces individual sector demand. This increases the overall airspace efficiency, but requires additional resources in some sectors in terms of controllers and equipment, which is undesirable. This study examines the tradeoff of the number of sectors designed for a specified amount of traffic in a clear-weather day and the delays needed for accommodating the traffic demand. Results show that most of the delays are caused by airport arrival and departure capacity constraints. Some delays caused by airspace capacity constraints can be eliminated by re-partitioning the airspace. Analyses show that about 360 high-altitude sectors, which are approximately today s operational number of sectors of 373, are adequate for delays to be driven solely by airport capacity constraints for the current daily air traffic demand. For a marginal increase of 15 seconds of average delay, the number of sectors can be reduced to 283. In addition, simulations of traffic growths of 15% and 20% with forecasted airport capacities in the years 2018 and 2025 show that delays will continue to be governed by airport capacities. In clear-weather days, for small increases in traffic demand, increasing sector capacities will have almost no effect on delays.

FAA aviation forecasts : fiscal years 1997-2008

DOT National Transportation Integrated Search

1997-03-01

This report contains the Fiscal Years 1997-2008 Federal Aviation Administration (FAA) forecasts of aviation activity at FAA facilities. These include airports with both FAA and contract control towers, air route traffic control centers, and flight se...

Impacts of moving bottlenecks on traffic flow

NASA Astrophysics Data System (ADS)

Ou, Hui; Tang, Tie-Qiao

2018-06-01

Bottleneck (especially the moving bottleneck) widely exists in the urban traffic system. However, little effort has been made to study the impacts of the moving bottleneck on traffic flow (especially the evolution and propagation of traffic flow). In this article, we introduce the speed of a moving bottleneck into a traffic flow model, then propose an extended macro traffic flow with a moving bottleneck, and finally use the proposed model to study the effects of a moving bottleneck on the evolution and propagation of traffic flow under uniform flow and a small perturbation. The numerical results indicate that the moving bottleneck has prominent influences on the evolution of traffic flow under the two typical traffic situations and that the impacts are dependent on the initial density.

Research notes : best practices for traffic impact studies.

DOT National Transportation Integrated Search

2006-11-01

Traffic Impact Studies (TISs) are used by the Oregon Department of Transportation (ODOT) and staff of other transportation agencies to forecast future system effects from proposed development projects and to predict the useful life of a transportatio...

Planning Inmarsat's second generation of spacecraft

NASA Astrophysics Data System (ADS)

Williams, W. P.

1982-09-01

The next generation of studies of the Inmarsat service are outlined, such as traffic forecasting studies, communications capacity estimates, space segment design, cost estimates, and financial analysis. Traffic forecasting will require future demand estimates, and a computer model has been developed which estimates demand over the Atlantic, Pacific, and Indian ocean regions. Communications estimates are based on traffic estimates, as a model converts traffic demand into a required capacity figure for a given area. The Erlang formula is used, requiring additional data such as peak hour ratios and distribution estimates. Basic space segment technical requirements are outlined (communications payload, transponder arrangements, etc), and further design studies involve such areas as space segment configuration, launcher and spacecraft studies, transmission planning, and earth segment configurations. Cost estimates of proposed design parameters will be performed, but options must be reduced to make construction feasible. Finally, a financial analysis will be carried out in order to calculate financial returns.

Forecast and capacity planning for Nogales' ports of entry : [summary].

DOT National Transportation Integrated Search

2009-12-01

This document provides the final report of the activities performed under the project : Nogales POEs Traffic Study: Forecast and Capacity Planning for Nogales Ports of Entry : sponsored by the Arizona Department of Transportation (ADOT) under Gran...

A model to forecast peak spreading.

DOT National Transportation Integrated Search

2012-04-01

As traffic congestion increases, the K-factor, defined as the proportion of the 24-hour traffic volume that occurs during the peak hour, may decrease. This behavioral response is known as peak spreading: as congestion grows during the peak travel tim...

Holiday effect on traffic fatalities

DOT National Transportation Integrated Search

1987-04-01

The report identifies those holidays that show an increase in traffic fatalities and estimates the size of the increase for each national holiday. A procedure is presented that can be used to forecast the expected fatality count for each upcoming hol...

Evaluation of origin-destination matrix estimation techniques to support aspects of traffic modeling.

DOT National Transportation Integrated Search

2014-05-01

Travel demand forecasting models are used to predict future traffic volumes to evaluate : roadway improvement alternatives. Each of the metropolitan planning organizations (MPO) in : Alabama maintains a travel demand model to support planning efforts...

Seismic vulnerability analysis of bridges in mountainous states.

DOT National Transportation Integrated Search

2013-09-01

Depending on the location, highway bridges can often support considerable amounts of traffic. Due to the limitations on current earthquake forecasting techniques, a normal amount of traffic will also typically remain on a bridge when an earthquake oc...

Traffic-load forecasting using weigh-in-motion data

DOT National Transportation Integrated Search

1997-03-01

Vehicular traffic loading is a crucial consideration for the design and maintenance of pavements. With the help of weigh-in-motion (WIM) systems, the information about date, time, speed, lane of travel, lateral lane position, axle spacing, and wheel ...

Understanding urban travel demand : problems, solutions, and the role of forecasting

DOT National Transportation Integrated Search

1999-08-01

This report is a general examination and critique of transportation policy making, focusing on the role of traffic and land use forecasting. There are four major components: (1) Current, historical, and projected travel behavior in the Twin Cities; (...

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.

Evaluation of TxDOT'S traffic data collection and load forecasting process

DOT National Transportation Integrated Search

2001-01-01

This study had two primary objectives: (1) compare current Texas Department of Transportation (TxDOT) procedures and protocols with the state-of-the-practice and the needs of its data customers; and (2) develop enhanced traffic collection, archival, ...

Next generation air transportation system : issues associated with midterm implementation of capabilities and full system transformation.

DOT National Transportation Integrated Search

2009-03-01

To prepare for forecasted air traffic : growth, the Federal Aviation : Administration (FAA), including its : Joint Planning and Development : Office (JPDO) and Air Traffic : Organization (ATO), is planning for : and implementing the Next : Generation...

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.

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.

Origin destination disaggregation using fratar biproportional least squares estimation for truck forecasting.

DOT National Transportation Integrated Search

2009-02-01

This working paper describes a group of techniques for disaggregating origin-destination tables : for truck forecasting that makes explicit use of observed traffic on a network. Six models within : the group are presented, each of which uses nonlinea...

Developing long range traffic projection models for Illinois : final report.

DOT National Transportation Integrated Search

2004-06-01

The project objective was to develop a PC-based tool to assist Illinois Department of Transportation (IDOT) traffic forecasters : to meet FHWA reporting requirements for 2,400 HPMS sections and 27,000 structures in the State of Illinois, and to produ...

Next generation air transportation system : status of transformation and issues associated with midterm implementation of capabilities.

DOT National Transportation Integrated Search

2009-03-01

"To prepare for forecasted air traffic growth, the Federal Aviation Administration (FAA), including its Joint Planning and Development Office (JPDO) and Air Traffic Organization (ATO), is planning for and implementing the Next Generation Air Transpor...

Safety and Convergence Analysis of Intersecting Aircraft Flows Under Decentralized Collision Avoidance

NASA Astrophysics Data System (ADS)

Dallal, Ahmed H.

Safety is an essential requirement for air traffic management and control systems. Aircraft are not allowed to get closer to each other than a specified safety distance, to avoid any conflicts and collisions between aircraft. Forecast analysis predicts a tremendous increase in the number of flights. Subsequently, automated tools are needed to help air traffic controllers resolve air born conflicts. In this dissertation, we consider the problem of conflict resolution of aircraft flows with the assumption that aircraft are flowing through a fixed specified control volume at a constant speed. In this regard, several centralized and decentralized resolution rules have been proposed for path planning and conflict avoidance. For the case of two intersecting flows, we introduce the concept of conflict touches, and a collaborative decentralized conflict resolution rule is then proposed and analyzed for two intersecting flows. The proposed rule is also able to resolved airborne conflicts that resulted from resolving another conflict via the domino effect. We study the safety conditions under the proposed conflict resolution and collision avoidance rule. Then, we use Lyapunov analysis to analytically prove the convergence of conflict resolution dynamics under the proposed rule. The analysis show that, under the proposed conflict resolution rule, the system of intersecting aircraft flows is guaranteed to converge to safe, conflict free, trajectories within a bounded time. Simulations are provided to verify the analytically derived conclusions and study the convergence of the conflict resolution dynamics at different encounter angles. Simulation results show that lateral deviations taken by aircraft in each flow, to resolve conflicts, are bounded, and aircraft converged to safe and conflict free trajectories, within a finite time.

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.

Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

NASA Technical Reports Server (NTRS)

Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan

2000-01-01

The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

Telecommunication service markets through the year 2000 in relation to millimeter wave satellite systems

NASA Technical Reports Server (NTRS)

Stevenson, S. M.

1979-01-01

NASA is currently conducting a series of millimeter wave satellite system market studies to develop 30/20 GHz satellite system concepts that have commercial potential. Four contractual efforts were undertaken: two parallel and independent system studies and two parallel and independent market studies. The marketing efforts are focused on forecasting the total domestic demand for long haul telecommunications services for the 1980-2000 period. Work completed to date and reported in this paper include projections of: geographical distribution of traffic; traffic volume as a function of urban area size; and user identification and forecasted demand.

Forecast and capacity planning for Nogales' ports of entry.

DOT National Transportation Integrated Search

2009-12-01

This report documents the findings and the activities performed under ADOT grant JPA 08024T. The overall purpose of this study was to forecast the number of border crossings by mode of traffic at the NogalesMariposa and DeConcini Ports of Entry...

Design/build vs traditional construction user delay modeling : an evaluation of the cost effectiveness of innovative construction methods for new construction. Part 2 : VISUM Online for Salt Lake, Davis, and Utah Counties

DOT National Transportation Integrated Search

2007-05-01

VISUM Online is a traffic management system for processing online traffic data. The system implements both a road network model and a traffic demand model. VISUM Online uses all available real-time and historic data to calculate current and forecaste...

National Waterways Study. Traffic Forecasting Methodology.

DTIC Science & Technology

1981-08-01

non-ferrous). In general , the demand for domestic waterborne metallic ore transportation is projected to grow somewhat faster than iron ore...steady growth in imported tonnages. Industrial chemicals generally exhibit upward trends ranging from 2.5% per year to 4.6% per year for a broad mix...completion of Colonial pipeline system expansions in 1981. Internal traffic generally ex- hibts flat to 1% per year traffic increases, with growth

CG Vessel Traffic Service Program.

DTIC Science & Technology

1980-06-01

Corps of Engineers and the Maritime Administration have forecast that total commercial cargo transported through U.S. ports and waterways will increase... electronic navigation and surveillance equipment since the early 1960’s to evaluate various concepts by which vessel traffic safety could be enhanced...relatively complete data base on vessel traffic. On the other hand, the addition of radar and other electronic surveillance should: --Prevent vessel

Synchronized flow in oversaturated city traffic.

PubMed

Kerner, Boris S; Klenov, Sergey L; Hermanns, Gerhard; Hemmerle, Peter; Rehborn, Hubert; Schreckenberg, Michael

2013-11-01

Based on numerical simulations with a stochastic three-phase traffic flow model, we reveal that moving queues (moving jams) in oversaturated city traffic dissolve at some distance upstream of the traffic signal while transforming into synchronized flow. It is found that, as in highway traffic [Kerner, Phys. Rev. E 85, 036110 (2012)], such a jam-absorption effect in city traffic is explained by a strong driver's speed adaptation: Time headways (space gaps) between vehicles increase upstream of a moving queue (moving jam), resulting in moving queue dissolution. It turns out that at given traffic signal parameters, the stronger the speed adaptation effect, the shorter the mean distance between the signal location and the road location at which moving queues dissolve fully and oversaturated traffic consists of synchronized flow only. A comparison of the synchronized flow in city traffic found in this Brief Report with synchronized flow in highway traffic is made.

Synchronized flow in oversaturated city traffic

NASA Astrophysics Data System (ADS)

Kerner, Boris S.; Klenov, Sergey L.; Hermanns, Gerhard; Hemmerle, Peter; Rehborn, Hubert; Schreckenberg, Michael

2013-11-01

Based on numerical simulations with a stochastic three-phase traffic flow model, we reveal that moving queues (moving jams) in oversaturated city traffic dissolve at some distance upstream of the traffic signal while transforming into synchronized flow. It is found that, as in highway traffic [Kerner, Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.85.036110 85, 036110 (2012)], such a jam-absorption effect in city traffic is explained by a strong driver's speed adaptation: Time headways (space gaps) between vehicles increase upstream of a moving queue (moving jam), resulting in moving queue dissolution. It turns out that at given traffic signal parameters, the stronger the speed adaptation effect, the shorter the mean distance between the signal location and the road location at which moving queues dissolve fully and oversaturated traffic consists of synchronized flow only. A comparison of the synchronized flow in city traffic found in this Brief Report with synchronized flow in highway traffic is made.

A Small Aircraft Transportation System (SATS) Demand Model

NASA Technical Reports Server (NTRS)

Long, Dou; Lee, David; Johnson, Jesse; Kostiuk, Peter; Yackovetsky, Robert (Technical Monitor)

2001-01-01

The Small Aircraft Transportation System (SATS) demand modeling is a tool that will be useful for decision-makers to analyze SATS demands in both airport and airspace. We constructed a series of models following the general top-down, modular principles in systems engineering. There are three principal models, SATS Airport Demand Model (SATS-ADM), SATS Flight Demand Model (SATS-FDM), and LMINET-SATS. SATS-ADM models SATS operations, by aircraft type, from the forecasts in fleet, configuration and performance, utilization, and traffic mixture. Given the SATS airport operations such as the ones generated by SATS-ADM, SATS-FDM constructs the SATS origin and destination (O&D) traffic flow based on the solution of the gravity model, from which it then generates SATS flights using the Monte Carlo simulation based on the departure time-of-day profile. LMINET-SATS, an extension of LMINET, models SATS demands at airspace and airport by all aircraft operations in US The models use parameters to provide the user with flexibility and ease of use to generate SATS demand for different scenarios. Several case studies are included to illustrate the use of the models, which are useful to identify the need for a new air traffic management system to cope with SATS.

An open-terrain line source model coupled with street-canyon effects to forecast carbon monoxide at traffic roundabout.

PubMed

Pandian, Suresh; Gokhale, Sharad; Ghoshal, Aloke Kumar

2011-02-15

A double-lane four-arm roundabout, where traffic movement is continuous in opposite directions and at different speeds, produces a zone responsible for recirculation of emissions within a road section creating canyon-type effect. In this zone, an effect of thermally induced turbulence together with vehicle wake dominates over wind driven turbulence causing pollutant emission to flow within, resulting into more or less equal amount of pollutants upwind and downwind particularly during low winds. Beyond this region, however, the effect of winds becomes stronger, causing downwind movement of pollutants. Pollutant dispersion caused by such phenomenon cannot be described accurately by open-terrain line source model alone. This is demonstrated by estimating one-minute average carbon monoxide concentration by coupling an open-terrain line source model with a street canyon model which captures the combine effect to describe the dispersion at non-signalized roundabout. The results of the modeling matched well with the measurements compared with the line source model alone and the prediction error reduced by about 50%. The study further demonstrated this with traffic emissions calculated by field and semi-empirical methods. Copyright © 2010 Elsevier B.V. All rights reserved.

Analysis and Prediction of Weather Impacted Ground Stop Operations

NASA Technical Reports Server (NTRS)

Wang, Yao Xun

2014-01-01

When the air traffic demand is expected to exceed the available airport's capacity for a short period of time, Ground Stop (GS) operations are implemented by Federal Aviation Administration (FAA) Traffic Flow Management (TFM). The GS requires departing aircraft meeting specific criteria to remain on the ground to achieve reduced demands at the constrained destination airport until the end of the GS. This paper provides a high-level overview of the statistical distributions as well as causal factors for the GSs at the major airports in the United States. The GS's character, the weather impact on GSs, GS variations with delays, and the interaction between GSs and Ground Delay Programs (GDPs) at Newark Liberty International Airport (EWR) are investigated. The machine learning methods are used to generate classification models that map the historical airport weather forecast, schedule traffic, and other airport conditions to implemented GS/GDP operations and the models are evaluated using the cross-validations. This modeling approach produced promising results as it yielded an 85% overall classification accuracy to distinguish the implemented GS days from the normal days without GS and GDP operations and a 71% accuracy to differentiate the GS and GDP implemented days from the GDP only days.

Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

NASA Technical Reports Server (NTRS)

Bilimoria, Karl; Hayashi, Miwa; Sheth, Kapil S.

2017-01-01

Traffic flow management seeks to balance the demand for National Airspace System (NAS) flight resources, such as airspace and airports, with the available supply. When forecasted weather blocks nominal air traffic routes, traffic managers must re-route affected flights for weather avoidance. Depending on the nature and scope of the weather, traffic managers may use pre-coordinated re-routes such as Playbook Routes or Coded Departure Routes, or may design ad hoc local re-routes. The routes of affected flights are modified accordingly. These weather avoidance routes will, of course, be less efficient than the nominal routes due to increased flight time and fuel burn. In current traffic management operations, the transition into a weather avoidance re-routing initiative is typically implemented more aggressively than the transition out of that initiative after the weather has dissipated or moved away. For example, strategic large-scale Playbook re-routes are sometimes left in place (as initially implemented) for many hours before being lifted entirely when the weather dissipates. There is an opportunity to periodically modify the re-routing plan as weather evolves, thereby attenuating its adverse impact on flight time and fuel consumption; this is called delay recovery. Multi-Flight Common Routes (MFCR) is a NASA-developed operational concept and associated decision support tool for delay recovery, designed to assist traffic managers to efficiently update weather avoidance traffic routes after the original re-routes have become stale due to subsequent evolution of the convective weather system. MFCR groups multiple flights to reduce the number of advisories that the traffic manager needs to evaluate, and also merges these flights on a common route segment to provide an orderly flow of re-routed traffic. The advisory is presented to the appropriate traffic manager who evaluates it and has the option to modify it using MFCRs graphical user interface. If the traffic manager finds the advisory to be operationally appropriate, he or she would coordinate with the Area Supervisor(s) of the sectors that currently control the flights in the advisory. When the traffic manager accepts the MFCR advisory via the user interface, the corresponding flight plan amendments would be sent to the displays of the appropriate sector controllers, using the Airborne Re-Routing (ABRR) capability which is scheduled for nationwide operation in 2017. The sector controllers would then offer this time-saving route modification to the pilots of the affected flights via datalink (or voice), and implement the corresponding flight plan amendment if the pilots accept it. MFCR is implemented as an application in the software environment of the Future Air traffic management Concepts Evaluation Tool (FACET). This paper focuses on an initial subject matter expert (SME) evaluation of MFCR. The evaluation covers MFCRs operational concept, algorithm, and user interface.

Analysis of vehicular traffic flow in the major areas of Kuala Lumpur utilizing open-traffic

NASA Astrophysics Data System (ADS)

Manogaran, Saargunawathy; Ali, Muhammad; Yusof, Kamaludin Mohamad; Suhaili, Ramdhan

2017-09-01

Vehicular traffic congestion occurs when a large number of drivers are overcrowded on the road and the traffic flow does not run smoothly. Traffic congestion causes chaos on the road and interruption to daily activities of users. Time consumed on road give lots of negative effects on productivity, social behavior, environmental and cost to economy. Congestion is worsens and leads to havoc during the emergency such as flood, accidents, road maintenance and etc., where behavior of traffic flow is always unpredictable and uncontrollable. Real-time and historical traffic data are critical inputs for most traffic flow analysis applications. Researcher attempt to predict traffic using simulations as there is no exact model of traffic flow exists due to its high complexity. Open Traffic is an open source platform available for traffic data analysis linked to Open Street Map (OSM). This research is aimed to study and understand the Open Traffic platform. The real-time traffic flow pattern in Kuala Lumpur area was successfully been extracted and analyzed using Open Traffic. It was observed that the congestion occurs on every major road in Kuala Lumpur and most of it owes to the offices and the economic and commercial centers during rush hours. At some roads the congestion occurs at night due to the tourism activities.

Traffic Flow Theory - A State-of-the-Art Report: Revised Monograph on Traffic Flow Theory

DOT National Transportation Integrated Search

2002-04-13

This publication is an update and expansion of the Transportation Research Board (TRB) Special Report 165, "Traffic Flow Theory," published in 1975. This updating was undertaken on recommendation of the TRB's Committee on Traffic Flow Theory and Char...

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

PubMed

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

2007-07-01

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

Time Relevance of Convective Weather Forecast for Air Traffic Automation

NASA Technical Reports Server (NTRS)

Chan, William N.

2006-01-01

The Federal Aviation Administration (FAA) is handling nearly 120,000 flights a day through its Air Traffic Management (ATM) system and air traffic congestion is expected to increse substantially over the next 20 years. Weather-induced impacts to throughput and efficiency are the leading cause of flight delays accounting for 70% of all delays with convective weather accounting for 60% of all weather related delays. To support the Next Generation Air Traffic System goal of operating at 3X current capacity in the NAS, ATC decision support tools are being developed to create advisories to assist controllers in all weather constraints. Initial development of these decision support tools did not integrate information regarding weather constraints such as thunderstorms and relied on an additional system to provide that information. Future Decision Support Tools should move towards an integrated system where weather constraints are factored into the advisory of a Decision Support Tool (DST). Several groups such at NASA-Ames, Lincoln Laboratories, and MITRE are integrating convective weather data with DSTs. A survey of current convective weather forecast and observation data show they span a wide range of temporal and spatial resolutions. Short range convective observations can be obtained every 5 mins with longer range forecasts out to several days updated every 6 hrs. Today, the short range forecasts of less than 2 hours have a temporal resolution of 5 mins. Beyond 2 hours, forecasts have much lower temporal. resolution of typically 1 hour. Spatial resolutions vary from 1km for short range to 40km for longer range forecasts. Improving the accuracy of long range convective forecasts is a major challenge. A report published by the National Research Council states improvements for convective forecasts for the 2 to 6 hour time frame will only be achieved for a limited set of convective phenomena in the next 5 to 10 years. Improved longer range forecasts will be probabilistic as opposed to the deterministic shorter range forecasts. Despite the known low level of confidence with respect to long range convective forecasts, these data are still useful to a DST routing algorithm. It is better to develop an aircraft route using the best information available than no information. The temporally coarse long range forecast data needs to be interpolated to be useful to a DST. A DST uses aircraft trajectory predictions that need to be evaluated for impacts by convective storms. Each time-step of a trajectory prediction n&s to be checked against weather data. For the case of coarse temporal data, there needs to be a method fill in weather data where there is none. Simply using the coarse weather data without any interpolation can result in DST routes that are impacted by regions of strong convection. Increasing the temporal resolution of these data can be achieved but result in a large dataset that may prove to be an operational challenge in transmission and loading by a DST. Currently, it takes about 7mins retrieve a 7mb RUC2 forecast file from NOAA at NASA-Ames Research Center. A prototype NCWF6 1 hour forecast is about 3mb in size. A Six hour NCWFG forecast with a 1hr forecast time-step will be about l8mb (6 x 3mb). A 6 hour NCWF6 forecast with a l5min forecast time-step will be about 7mb (24 x 3mb). Based on the time it takes to retrieve a 7mb RUC2 forecast, it will take approximately 70mins to retrieve a 6 hour NCWF forecast with 15min time steps. Until those issues are addressed, there is a need to develop an algorithm that interpolates between these temporally coarse long range forecasts. This paper describes a method of how to use low temporal resolution probabilistic weather forecasts in a DST. The beginning of this paper is a description of some convective weather forecast and observation products followed by an example of how weather data are used by a DST. The subsequent sections will describe probabilistic forecasts followed by a descrtion of a method to use low temporal resolution probabilistic weather forecasts by providing a relevance value to these data outside of their valid times.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Precipitation forecasts for rainfall runoff predictions. A case study in poorly gauged Ribb and Gumara catchments, upper Blue Nile, Ethiopia

NASA Astrophysics Data System (ADS)

Seyoum, Mesgana; van Andel, Schalk Jan; Xuan, Yunqing; Amare, Kibreab

Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5 forecasts with a spatial resolution of 2 km; the Maximum, Mean and Minimum members (MaxEPS, MeanEPS and MinEPS where EPS stands for Ensemble Prediction System) of the fixed, low resolution (2.5 by 2.5 degrees) National Oceanic and Atmospheric Administration Global Forecast System (NOAA GFS) ensemble forecasts were used. Both the MM5 and the EPS were not calibrated (bias correction, downscaling (for EPS), etc.). In addition, zero forecasts assuming no rainfall in the coming days, and monthly average forecasts assuming average monthly rainfall in the coming days, were used. These rainfall forecasts were then used to drive the Hydrologic Engineering Center’s-Hydrologic Modeling System, HEC-HMS, hydrologic model for flow predictions. The results show that flow predictions using MaxEPS and MM5 precipitation forecasts over-predicted the peak flow for most of the seven events analyzed, whereas under-predicted peak flow was found using zero- and monthly average rainfall. The comparison of observed and predicted flow hydrographs shows that MM5, MaxEPS and MeanEPS precipitation forecasts were able to capture the rainfall signal that caused peak flows. Flow predictions based on MaxEPS and MeanEPS gave results that were quantitatively close to the observed flow for most events, whereas flow predictions based on MM5 resulted in large overestimations for some events. In follow-up research for this particular case study, calibration of the MM5 model will be performed. The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available.

A national-scale seasonal hydrological forecast system: development and evaluation over Britain

NASA Astrophysics Data System (ADS)

Bell, Victoria A.; Davies, Helen N.; Kay, Alison L.; Brookshaw, Anca; Scaife, Adam A.

2017-09-01

Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better) rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts) from the GloSea5 model (1996 to 2009) are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean) rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region). Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 %) in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows), whereas for the 3-month ahead lead time, GloSea5 forecasts account for ˜ 70 % of the forecast skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe.

Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors.

PubMed

Bao, Xu; Li, Haijian; Xu, Dongwei; Jia, Limin; Ran, Bin; Rong, Jian

2016-11-06

The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a "tailgating effect" between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments.

Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors

PubMed Central

Bao, Xu; Li, Haijian; Xu, Dongwei; Jia, Limin; Ran, Bin; Rong, Jian

2016-01-01

The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a “tailgating effect” between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments. PMID:27827974

Cellular automata model for traffic flow at intersections in internet of vehicles

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

TrafficGen Architecture Document

DTIC Science & Technology

2016-01-01

sequence diagram ....................................................5 Fig. 5 TrafficGen traffic flows viewed in SDT3D...Scripts contain commands to have the network node listen on specific ports and flows describing the start time, stop time, and specific traffic ...arranged vertically and time presented horizontally. Individual traffic flows are represented by horizontal bars indicating the start time, stop time

Smoothing strategies combined with ARIMA and neural networks to improve the forecasting of traffic accidents.

PubMed

Barba, Lida; Rodríguez, Nibaldo; Montt, Cecilia

2014-01-01

Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0:26%, followed by MA-ARIMA with a MAPE of 1:12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15:51%.

High-resolution numerical approximation of traffic flow problems with variable lanes and free-flow velocities.

PubMed

Zhang, Peng; Liu, Ru-Xun; Wong, S C

2005-05-01

This paper develops macroscopic traffic flow models for a highway section with variable lanes and free-flow velocities, that involve spatially varying flux functions. To address this complex physical property, we develop a Riemann solver that derives the exact flux values at the interface of the Riemann problem. Based on this solver, we formulate Godunov-type numerical schemes to solve the traffic flow models. Numerical examples that simulate the traffic flow around a bottleneck that arises from a drop in traffic capacity on the highway section are given to illustrate the efficiency of these schemes.

Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model

NASA Astrophysics Data System (ADS)

Zhu, Wen-Xing; Zhang, H. M.

2018-04-01

We investigated the mixed traffic flow with human-driving and autonomous cars. A new mathematical model with adjustable sensitivity and smooth factor was proposed to describe the autonomous car's moving behavior in which smooth factor is used to balance the front and back headway in a flow. A lemma and a theorem were proved to support the stability criteria in traffic flow. A series of simulations were carried out to analyze the mixed traffic flow. The fundamental diagrams were obtained from the numerical simulation results. The varying sensitivity and smooth factor of autonomous cars affect traffic flux, which exhibits opposite varying tendency with increasing parameters before and after the critical density. Moreover, the sensitivity of sensors and smooth factors play an important role in stabilizing the mixed traffic flow and suppressing the traffic jam.

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 ...

Traffic Flow Estimates.

ERIC Educational Resources Information Center

Hart, Vincent G.

1981-01-01

Two examples are given of ways traffic engineers estimate traffic flow. The first, Floating Car Method, involves some basic ideas and the notion of relative velocity. The second, Maximum Traffic Flow, is viewed to involve simple applications of calculus. The material provides insight into specialized applications of mathematics. (MP)

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Percolation transition in dynamical traffic network with evolving critical bottlenecks.

PubMed

Li, Daqing; Fu, Bowen; Wang, Yunpeng; Lu, Guangquan; Berezin, Yehiel; Stanley, H Eugene; Havlin, Shlomo

2015-01-20

A critical phenomenon is an intrinsic feature of traffic dynamics, during which transition between isolated local flows and global flows occurs. However, very little attention has been given to the question of how the local flows in the roads are organized collectively into a global city flow. Here we characterize this organization process of traffic as "traffic percolation," where the giant cluster of local flows disintegrates when the second largest cluster reaches its maximum. We find in real-time data of city road traffic that global traffic is dynamically composed of clusters of local flows, which are connected by bottleneck links. This organization evolves during a day with different bottleneck links appearing in different hours, but similar in the same hours in different days. A small improvement of critical bottleneck roads is found to benefit significantly the global traffic, providing a method to improve city traffic with low cost. Our results may provide insights on the relation between traffic dynamics and percolation, which can be useful for efficient transportation, epidemic control, and emergency evacuation.

Analysis of energy consumption and emission of the heterogeneous traffic flow consisting of traditional vehicles and electric vehicles

NASA Astrophysics Data System (ADS)

Xiao, Hong; Huang, Hai-Jun; Tang, Tie-Qiao

2017-12-01

Electric vehicle (EV) has become a potential traffic tool, which has attracted researchers to explore various traffic phenomena caused by EV (e.g. congestion, electricity consumption, etc.). In this paper, we study the energy consumption (including the fuel consumption and the electricity consumption) and emissions of heterogeneous traffic flow (that consists of the traditional vehicle (TV) and EV) under three traffic situations (i.e. uniform flow, shock and rarefaction waves, and a small perturbation) from the perspective of macro traffic flow. The numerical results show that the proportion of electric vehicular flow has great effects on the TV’s fuel consumption and emissions and the EV’s electricity consumption, i.e. the fuel consumption and emissions decrease while the electricity consumption increases with the increase of the proportion of electric vehicular flow. The results can help us better understand the energy consumption and emissions of the heterogeneous traffic flow consisting of TV and EV.

Contrail Tracking and ARM Data Product Development

NASA Technical Reports Server (NTRS)

Duda, David P.; Russell, James, III

2005-01-01

A contrail tracking system was developed to help in the assessment of the effect of commercial jet contrails on the Earth's radiative budget. The tracking system was built by combining meteorological data from the Rapid Update Cycle (RUC) numerical weather prediction model with commercial air traffic flight track data and satellite imagery. A statistical contrail-forecasting model was created a combination of surface-based contrail observations and numerical weather analyses and forecasts. This model allows predictions of widespread contrail occurrences for contrail research on either a real-time basis or for long-term time scales. Satellite-derived cirrus cloud properties in polluted and unpolluted regions were compared to determine the impact of air traffic on cirrus.

Forecasting the short-term passenger flow on high-speed railway with neural networks.

PubMed

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway.

Road traffic accidents prediction modelling: An analysis of Anambra State, Nigeria.

PubMed

Ihueze, Chukwutoo C; Onwurah, Uchendu O

2018-03-01

One of the major problems in the world today is the rate of road traffic crashes and deaths on our roads. Majority of these deaths occur in low-and-middle income countries including Nigeria. This study analyzed road traffic crashes in Anambra State, Nigeria with the intention of developing accurate predictive models for forecasting crash frequency in the State using autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average with explanatory variables (ARIMAX) modelling techniques. The result showed that ARIMAX model outperformed the ARIMA (1,1,1) model generated when their performances were compared using the lower Bayesian information criterion, mean absolute percentage error, root mean square error; and higher coefficient of determination (R-Squared) as accuracy measures. The findings of this study reveal that incorporating human, vehicle and environmental related factors in time series analysis of crash dataset produces a more robust predictive model than solely using aggregated crash count. This study contributes to the body of knowledge on road traffic safety and provides an approach to forecasting using many human, vehicle and environmental factors. The recommendations made in this study if applied will help in reducing the number of road traffic crashes in Nigeria. Copyright © 2017 Elsevier Ltd. All rights reserved.

Benefit Opportunities for Integrated Surface and Airspace Departure Scheduling: A Study of Operations at Charlotte-Douglas International Airport

NASA Technical Reports Server (NTRS)

Coppenbarger, Rich; Jung, Yoon; Kozon, Tom; Farrahi, Amir; Malik, Wakar; Lee, Hanbong; Chevalley, Eric; Kistler, Matt

2016-01-01

NASA is collaborating with the FAA and aviation industry to develop and demonstrate new capabilities that integrate arrival, departure, and surface air-traffic operations. The concept relies on trajectory-based departure scheduling and collaborative decision making to reduce delays and uncertainties in taxi and climb operations. The paper describes the concept and benefit mechanisms aimed at improving flight efficiency and predictability while maintaining or improving operational throughput. The potential impact of the technology is studied and discussed through a quantitative analysis of relevant shortfalls at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport. Results from trajectory analysis indicate substantial opportunity to reduce taxi delays for both departures and arrivals by metering departures at the gate in a manner that maximizes throughput while adhering to takeoff restrictions due mostly to airspace constraints. Substantial taxi-out delay reduction is shown for flights subject to departure restrictions stemming from traffic flow management initiatives. Opportunities to improve the predictability of taxi, takeoff, and climb operations are examined and their potential impact on airline scheduling decisions and air-traffic forecasting is discussed. In addition, the potential to improve throughput with departure scheduling that maximizes use of available runway and airspace capacity is analyzed.

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.

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.

48 CFR 232.072-3 - Cash flow forecasts.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false Cash flow forecasts. 232..., DEPARTMENT OF DEFENSE GENERAL CONTRACTING REQUIREMENTS CONTRACT FINANCING 232.072-3 Cash flow forecasts. (a) A contractor must be able to sustain a sufficient cash flow to perform the contract. When there is...

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

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.

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.

Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system

NASA Astrophysics Data System (ADS)

Liu, Mianfang; Xiong, Shengwu; Li, Bixiang

2016-05-01

With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.

Construction and simulation of a novel continuous traffic flow model

NASA Astrophysics Data System (ADS)

Hwang, Yao-Hsin; Yu, Jui-Ling

2017-12-01

In this paper, we aim to propose a novel mathematical model for traffic flow and apply a newly developed characteristic particle method to solve the associate governing equations. As compared with the existing non-equilibrium higher-order traffic flow models, the present one is put forward to satisfy the following three conditions: Preserve the equilibrium state in the smooth region. Yield an anisotropic propagation of traffic flow information. Expressed with a conservation law form for traffic momentum. These conditions will ensure a more practical simulation in traffic flow physics: The current traffic will not be influenced by the condition in the behind and result in unambiguous condition across a traffic shock. Through analyses of characteristics, stability condition and steady-state solution adherent to the equation system, it is shown that the proposed model actually conform to these conditions. Furthermore, this model can be cast into its characteristic form which, incorporated with the Rankine-Hugoniot relation, is appropriate to be simulated by the characteristic particle method to obtain accurate computational results.

Realistic Data-Driven Traffic Flow Animation Using Texture Synthesis.

PubMed

Chao, Qianwen; Deng, Zhigang; Ren, Jiaping; Ye, Qianqian; Jin, Xiaogang

2018-02-01

We present a novel data-driven approach to populate virtual road networks with realistic traffic flows. Specifically, given a limited set of vehicle trajectories as the input samples, our approach first synthesizes a large set of vehicle trajectories. By taking the spatio-temporal information of traffic flows as a 2D texture, the generation of new traffic flows can be formulated as a texture synthesis process, which is solved by minimizing a newly developed traffic texture energy. The synthesized output captures the spatio-temporal dynamics of the input traffic flows, and the vehicle interactions in it strictly follow traffic rules. After that, we position the synthesized vehicle trajectory data to virtual road networks using a cage-based registration scheme, where a few traffic-specific constraints are enforced to maintain each vehicle's original spatial location and synchronize its motion in concert with its neighboring vehicles. Our approach is intuitive to control and scalable to the complexity of virtual road networks. We validated our approach through many experiments and paired comparison user studies.

Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach

NASA Astrophysics Data System (ADS)

Ngoduy, D.

2013-10-01

This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.

The role of the airline transportation network in the prediction and predictability of global epidemics.

PubMed

Colizza, Vittoria; Barrat, Alain; Barthélemy, Marc; Vespignani, Alessandro

2006-02-14

The systematic study of large-scale networks has unveiled the ubiquitous presence of connectivity patterns characterized by large-scale heterogeneities and unbounded statistical fluctuations. These features affect dramatically the behavior of the diffusion processes occurring on networks, determining the ensuing statistical properties of their evolution pattern and dynamics. In this article, we present a stochastic computational framework for the forecast of global epidemics that considers the complete worldwide air travel infrastructure complemented with census population data. We address two basic issues in global epidemic modeling: (i) we study the role of the large scale properties of the airline transportation network in determining the global diffusion pattern of emerging diseases; and (ii) we evaluate the reliability of forecasts and outbreak scenarios with respect to the intrinsic stochasticity of disease transmission and traffic flows. To address these issues we define a set of quantitative measures able to characterize the level of heterogeneity and predictability of the epidemic pattern. These measures may be used for the analysis of containment policies and epidemic risk assessment.

Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents

PubMed Central

Rodríguez, Nibaldo

2014-01-01

Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0 : 26%, followed by MA-ARIMA with a MAPE of 1 : 12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15 : 51%. PMID:25243200

Forecasting the Short-Term Passenger Flow on High-Speed Railway with Neural Networks

PubMed Central

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway. PMID:25544838

The Influence of Individual Driver Characteristics on Congestion Formation

NASA Astrophysics Data System (ADS)

Wang, Lanjun; Zhang, Hao; Meng, Huadong; Wang, Xiqin

Previous works have pointed out that one of the reasons for the formation of traffic congestion is instability in traffic flow. In this study, we investigate theoretically how the characteristics of individual drivers influence the instability of traffic flow. The discussions are based on the optimal velocity model, which has three parameters related to individual driver characteristics. We specify the mappings between the model parameters and driver characteristics in this study. With linear stability analysis, we obtain a condition for when instability occurs and a constraint about how the model parameters influence the unstable traffic flow. Meanwhile, we also determine how the region of unstable flow densities depends on these parameters. Additionally, the Langevin approach theoretically validates that under the constraint, the macroscopic characteristics of the unstable traffic flow becomes a mixture of free flows and congestions. All of these results imply that both overly aggressive and overly conservative drivers are capable of triggering traffic congestion.

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

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

Wave dynamics in an extended macroscopic traffic flow model with periodic boundaries

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Chu, Xing-Jian; Zhou, Chao-Fan; Yan, Bo-Wen; Jia, Bin; Fang, Chen-Hao

2018-06-01

Motivated by the previous traffic flow model considering the real-time traffic state, a modified macroscopic traffic flow model is established. The periodic boundary condition is applied to the car-following model. Besides, the traffic state factor R is defined in order to correct the real traffic conditions in a more reasonable way. It is a key step that we introduce the relaxation time as a density-dependent function and provide corresponding evolvement of traffic flow. Three different typical initial densities, namely the high density, the medium one and the low one, are intensively investigated. It can be found that the hysteresis loop exists in the proposed periodic-boundary system. Furthermore, the linear and nonlinear stability analyses are performed in order to test the robustness of the system.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: A Realistic Cellular Automaton Model for Synchronized Traffic Flow

NASA Astrophysics Data System (ADS)

Zhao, Bo-Han; Hu, Mao-Bin; Jiang, Rui; Wu, Qing-Song

2009-11-01

A cellular automaton model is proposed to consider the anticipation effect in drivers' behavior. It is shown that the anticipation effect can be one of the origins of synchronized traffic flow. With anticipation effect, the congested traffic flow simulated by the model exhibits the features of synchronized flow. The spatiotemporal patterns induced by an on-ramp are also consistent with the three-phase traffic theory. Since the origin of synchronized flow is still controversial, our work can shed some light on the mechanism of synchronized flow.

Traffic flow simulation for an urban freeway corridor

DOT National Transportation Integrated Search

1998-01-01

The objective of this paper is to develop a realistic and operational macroscopic traffic flow simulation model which requires relatively less data collection efforts. Such a model should be capable of delineating the dynamics of traffic flow created...

Traffic flow characteristic and capacity in intelligent work zones.

DOT National Transportation Integrated Search

2009-10-15

Intellgent transportation system (ITS) technologies are utilized to manage traffic flow and safety in : highway work zones. Traffic management plans for work zones require queuing analyses to determine : the anticipated traffic backups, but the predi...

Traffic experiment reveals the nature of car-following.

PubMed

Jiang, Rui; Hu, Mao-Bin; Zhang, H M; Gao, Zi-You; Jia, Bin; Wu, Qing-Song; Wang, Bing; Yang, Ming

2014-01-01

As a typical self-driven many-particle system far from equilibrium, traffic flow exhibits diverse fascinating non-equilibrium phenomena, most of which are closely related to traffic flow stability and specifically the growth/dissipation pattern of disturbances. However, the traffic theories have been controversial due to a lack of precise traffic data. We have studied traffic flow from a new perspective by carrying out large-scale car-following experiment on an open road section, which overcomes the intrinsic deficiency of empirical observations. The experiment has shown clearly the nature of car-following, which runs against the traditional traffic flow theory. Simulations show that by removing the fundamental notion in the traditional car-following models and allowing the traffic state to span a two-dimensional region in velocity-spacing plane, the growth pattern of disturbances has changed qualitatively and becomes qualitatively or even quantitatively in consistent with that observed in the experiment.

Traffic Experiment Reveals the Nature of Car-Following

PubMed Central

Jiang, Rui; Hu, Mao-Bin; Zhang, H. M.; Gao, Zi-You; Jia, Bin; Wu, Qing-Song; Wang, Bing; Yang, Ming

2014-01-01

As a typical self-driven many-particle system far from equilibrium, traffic flow exhibits diverse fascinating non-equilibrium phenomena, most of which are closely related to traffic flow stability and specifically the growth/dissipation pattern of disturbances. However, the traffic theories have been controversial due to a lack of precise traffic data. We have studied traffic flow from a new perspective by carrying out large-scale car-following experiment on an open road section, which overcomes the intrinsic deficiency of empirical observations. The experiment has shown clearly the nature of car-following, which runs against the traditional traffic flow theory. Simulations show that by removing the fundamental notion in the traditional car-following models and allowing the traffic state to span a two-dimensional region in velocity-spacing plane, the growth pattern of disturbances has changed qualitatively and becomes qualitatively or even quantitatively in consistent with that observed in the experiment. PMID:24740284

A quantitative analysis of inter-island telephony traffic in the Pacific Basin Region (PBR)

NASA Technical Reports Server (NTRS)

Evans, D. D.; Arth, C. H.

1980-01-01

As part of NASA's continuing assessment of future communication satellite requirements, a study was conducted to quantitatively scope current and future telecommunication traffic demand in the South Pacific Archipelagos. This demand was then converted to equivalent satellite transponder capacities. Only inter-island telephony traffic for the Pacific Basin Region was included. The results show that if all this traffic were carried by a satellite system, one-third of a satellite transponder would be needed to satisfy the base-year (1976-1977) requirement and about two-thirds of a satellite transponder would be needed to satisfy the forecasted 1985 requirement.

Intelligent driving in traffic systems with partial lane discipline

NASA Astrophysics Data System (ADS)

Assadi, Hamid; Emmerich, Heike

2013-04-01

It is a most common notion in traffic theory that driving in lanes and keeping lane changes to a minimum leads to smooth and laminar traffic flow, and hence to increased traffic capacity. On the other hand, there exist persistent vehicular traffic systems that are characterised by habitual disregarding of lane markings, and partial or complete loss of laminar traffic flow. Here, we explore the stability of such systems through a microscopic traffic flow model, where the degree of lane-discipline is taken as a variable, represented by the fraction of drivers that disregard lane markings completely. The results show that lane-free traffic may win over completely ordered traffic at high densities, and that partially ordered traffic leads to the poorest overall flow, while not considering the crash probability. Partial order in a lane-free system is similar to partial disorder in a lane-disciplined system in that both lead to decreased traffic capacity. This could explain the reason why standard enforcement methods, which rely on continuous increase of order, often fail to incur order to lane-free traffic systems. The results also provide an insight into the cooperative phenomena in open systems with self-driven particles.

Ramp metering : procedure manual.

DOT National Transportation Integrated Search

2002-11-01

Ramp metering is a traffic management tool used to increase the efficiency and safety of the : traffic operations on freeways. It is one of the most cost effective ways of managing traffic flow. : It improves traffic flow on congested freeways and of...

Finite size scaling analysis on Nagel-Schreckenberg model for traffic flow

NASA Astrophysics Data System (ADS)

Balouchi, Ashkan; Browne, Dana

2015-03-01

The traffic flow problem as a many-particle non-equilibrium system has caught the interest of physicists for decades. Understanding the traffic flow properties and though obtaining the ability to control the transition from the free-flow phase to the jammed phase plays a critical role in the future world of urging self-driven cars technology. We have studied phase transitions in one-lane traffic flow through the mean velocity, distributions of car spacing, dynamic susceptibility and jam persistence -as candidates for an order parameter- using the Nagel-Schreckenberg model to simulate traffic flow. The length dependent transition has been observed for a range of maximum velocities greater than a certain value. Finite size scaling analysis indicates power-law scaling of these quantities at the onset of the jammed phase.

A review and update of the Virginia Department of Transportation's cash flow forecasting model : interim report.

DOT National Transportation Integrated Search

1995-01-01

The Virginia Department of Transportation uses a cash flow forecasting model to predict operations expenditures by month. Components of this general forecasting model estimate line items in the VDOT budget. The cash flow model was developed in the ea...

A novel downlink scheduling strategy for traffic communication system based on TD-LTE technology.

PubMed

Chen, Ting; Zhao, Xiangmo; Gao, Tao; Zhang, Licheng

2016-01-01

There are many existing classical scheduling algorithms which can obtain better system throughput and user equality, however, they are not designed for traffic transportation environment, which cannot consider whether the transmission performance of various information flows could meet comprehensive requirements of traffic safety and delay tolerance. This paper proposes a novel downlink scheduling strategy for traffic communication system based on TD-LTE technology, which can perform two classification mappings for various information flows in the eNodeB: firstly, associate every information flow packet with traffic safety importance weight according to its relevance to the traffic safety; secondly, associate every traffic information flow with service type importance weight according to its quality of service (QoS) requirements. Once the connection is established, at every scheduling moment, scheduler would decide the scheduling order of all buffers' head of line packets periodically according to the instant value of scheduling importance weight function, which calculated by the proposed algorithm. From different scenario simulations, it can be verified that the proposed algorithm can provide superior differentiated transmission service and reliable QoS guarantee to information flows with different traffic safety levels and service types, which is more suitable for traffic transportation environment compared with the existing popularity PF algorithm. With the limited wireless resource, information flow closed related to traffic safety will always obtain priority scheduling right timely, which can help the passengers' journey more safe. Moreover, the proposed algorithm cannot only obtain good flow throughput and user fairness which are almost equal to those of the PF algorithm without significant differences, but also provide better realtime transmission guarantee to realtime information flow.

Hierarchical and coupling model of factors influencing vessel traffic flow.

PubMed

Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

Hierarchical and coupling model of factors influencing vessel traffic flow

PubMed Central

Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system. PMID:28414747

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

A two-lane cellular automaton traffic flow model with the influence of driver, vehicle and road

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Nie, Cen; Li, Jing-Ru; Wei, Yu-Ao

2016-07-01

On the basis of one-lane comfortable driving model, this paper established a two-lane traffic cellular automata model, which improves the slow randomization effected by brake light. Considering the driver psychological characteristics and mixed traffic, we studied the lateral influence between vehicles on adjacent lanes. Through computer simulation, the space-time diagram and the fundamental figure under different conditions are obtained. The study found that aggressive driver makes a slight congestion in low-density traffic and improves the capacity of high-density traffic, when the density exceeds 20pcu/km the more aggressive drivers the greater the flow, when the density below 40pcu/km driver character makes an effect, the more cautious driver, the lower the flow. The ratio of big cars has the same effect as the ratio of aggressive drivers. Brake lights have the greatest impact on traffic flow and when the density exceeds 10pcu/km the traffic flow fluctuates. Under periodic boundary conditions, the disturbance of road length on traffic is minimal. The lateral influence only play a limited role in the medium-density conditions, and only affect the average speed of traffic at low density.

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.

Congestion and communication in confined ant traffic

NASA Astrophysics Data System (ADS)

Gravish, Nick; Gold, Gregory; Zangwill, Andrew; Goodisman, Michael A. D.; Goldman, Daniel I.

2014-03-01

Many social animals move and communicate within confined spaces. In subterranean fire ants Solenopsis invicta, mobility within crowded nest tunnels is important for resource and information transport. Within confined tunnels, communication and traffic flow are at odds: trafficking ants communicate through tactile interactions while stopped, yet ants that stop to communicate impose physical obstacles on the traffic. We monitor the bi-directional flow of fire ant workers in laboratory tunnels of varied diameter D. The persistence time of communicating ant aggregations, τ, increases approximately linearly with the number of participating ants, n. The sensitivity of traffic flow increases as D decreases and diverges at a minimum diameter, Dc. A cellular automata model incorporating minimal traffic features--excluded volume and communication duration--reproduces features of the experiment. From the model we identify a competition between information transfer and the need to maintain jam-free traffic flow. We show that by balancing information transfer and traffic flow demands, an optimum group strategy exists which maximizes information throughput. We acknowledge funding from NSF PoLS #0957659 and #PHY-1205878.

Probabilistic physical characteristics of phase transitions at highway bottlenecks: incommensurability of three-phase and two-phase traffic-flow theories.

PubMed

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

2014-05-01

Physical features of induced phase transitions in a metastable free flow at an on-ramp bottleneck in three-phase and two-phase cellular automaton (CA) traffic-flow models have been revealed. It turns out that at given flow rates at the bottleneck, to induce a moving jam (F → J transition) in the metastable free flow through the application of a time-limited on-ramp inflow impulse, in both two-phase and three-phase CA models the same critical amplitude of the impulse is required. If a smaller impulse than this critical one is applied, neither F → J transition nor other phase transitions can occur in the two-phase CA model. We have found that in contrast with the two-phase CA model, in the three-phase CA model, if the same smaller impulse is applied, then a phase transition from free flow to synchronized flow (F → S transition) can be induced at the bottleneck. This explains why rather than the F → J transition, in the three-phase theory traffic breakdown at a highway bottleneck is governed by an F → S transition, as observed in real measured traffic data. None of two-phase traffic-flow theories incorporates an F → S transition in a metastable free flow at the bottleneck that is the main feature of the three-phase theory. On the one hand, this shows the incommensurability of three-phase and two-phase traffic-flow theories. On the other hand, this clarifies why none of the two-phase traffic-flow theories can explain the set of fundamental empirical features of traffic breakdown at highway bottlenecks.

Traffic flow collection wireless sensor network node for intersection light control

NASA Astrophysics Data System (ADS)

Li, Xu; Li, Xue

2011-10-01

Wireless sensor network (WSN) is expected to be deployed in intersection to monitor the traffic flow continuously, and the monitoring datum can be used as the foundation of traffic light control. In this paper, a WSN based on ZigBee protocol for monitoring traffic flow is proposed. Structure, hardware and work flow of WSN nodes are designed. CC2431 from Texas Instrument is chosen as the main computational and transmission unit, and CC2591 as the amplification unit. The stability experiment and the actual environment experiment are carried out in the last of the paper. The results of experiments show that WSN has the ability to collect traffic flow information quickly and transmit the datum to the processing center in real time.

Spontaneous phase transition from free flow to synchronized flow in traffic on a single-lane highway.

PubMed

Jin, Cheng-Jie; Wang, Wei; Jiang, Rui; Zhang, H M; Wang, Hao

2013-01-01

Traffic flow complexity comes from the car-following and lane-changing behavior. Based on empirical data for individual vehicle speeds and time headways measured on a single-lane highway section, we have studied the traffic flow properties induced by pure car-following behavior. We have found that a spontaneous sudden drop in velocity could happen in a platoon of vehicles when the velocity of the leading vehicle is quite high (~70 km/h). In contrast, when the velocity of the leading vehicle in a platoon slows down, such a spontaneous sudden drop of velocity has not been observed. Our finding indicates that traffic breakdown on a single-lane road might be a phase transition from free flow to synchronized flow (F→S transition). We have found that the flow rate within the emergent synchronized flow can be either smaller or larger than the flow rate in the free flow within which the synchronized flow propagates. Our empirical findings support Kerner's three-phase theory in which traffic breakdown is associated with an F→S transition.

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

PubMed

Thaker, Prashant; Gokhale, Sharad

2016-01-01

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

46 CFR 185.304 - Navigation underway.

Code of Federal Regulations, 2013 CFR

2013-10-01

... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

46 CFR 185.304 - Navigation underway.

Code of Federal Regulations, 2012 CFR

2012-10-01

... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

46 CFR 185.304 - Navigation underway.

Code of Federal Regulations, 2014 CFR

2014-10-01

... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

46 CFR 185.304 - Navigation underway.

Code of Federal Regulations, 2011 CFR

2011-10-01

... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

Research on three-phase traffic flow modeling based on interaction range

NASA Astrophysics Data System (ADS)

Zeng, Jun-Wei; Yang, Xu-Gang; Qian, Yong-Sheng; Wei, Xu-Ting

2017-12-01

On the basis of the multiple velocity difference effect (MVDE) model and under short-range interaction, a new three-phase traffic flow model (S-MVDE) is proposed through careful consideration of the influence of the relationship between the speeds of the two adjacent cars on the running state of the rear car. The random slowing rule in the MVDE model is modified in order to emphasize the influence of vehicle interaction between two vehicles on the probability of vehicles’ deceleration. A single-lane model which without bottleneck structure under periodic boundary conditions is simulated, and it is proved that the traffic flow simulated by S-MVDE model will generate the synchronous flow of three-phase traffic theory. Under the open boundary, the model is expanded by adding an on-ramp, the congestion pattern caused by the bottleneck is simulated at different main road flow rates and on-ramp flow rates, which is compared with the traffic congestion pattern observed by Kerner et al. and it is found that the results are consistent with the congestion characteristics in the three-phase traffic flow theory.

48 CFR 232.072-3 - Cash flow forecasts.

Code of Federal Regulations, 2013 CFR

2013-10-01

... forecasts is a strong indicator of serious managerial deficiencies or potential contract cost or performance... the causes of any differences. (d) Cash flow forecasts must— (1) Show the origin and use of all...

48 CFR 232.072-3 - Cash flow forecasts.

Code of Federal Regulations, 2011 CFR

2011-10-01

... forecasts is a strong indicator of serious managerial deficiencies or potential contract cost or performance... the causes of any differences. (d) Cash flow forecasts must— (1) Show the origin and use of all...

48 CFR 232.072-3 - Cash flow forecasts.

Code of Federal Regulations, 2014 CFR

2014-10-01

... forecasts is a strong indicator of serious managerial deficiencies or potential contract cost or performance... the causes of any differences. (d) Cash flow forecasts must— (1) Show the origin and use of all...

48 CFR 232.072-3 - Cash flow forecasts.

Code of Federal Regulations, 2012 CFR

2012-10-01

... forecasts is a strong indicator of serious managerial deficiencies or potential contract cost or performance... the causes of any differences. (d) Cash flow forecasts must— (1) Show the origin and use of all...

A GLM Post-processor to Adjust Ensemble Forecast Traces

NASA Astrophysics Data System (ADS)

Thiemann, M.; Day, G. N.; Schaake, J. C.; Draijer, S.; Wang, L.

2011-12-01

The skill of hydrologic ensemble forecasts has improved in the last years through a better understanding of climate variability, better climate forecasts and new data assimilation techniques. Having been extensively utilized for probabilistic water supply forecasting, interest is developing to utilize these forecasts in operational decision making. Hydrologic ensemble forecast members typically have inherent biases in flow timing and volume caused by (1) structural errors in the models used, (2) systematic errors in the data used to calibrate those models, (3) uncertain initial hydrologic conditions, and (4) uncertainties in the forcing datasets. Furthermore, hydrologic models have often not been developed for operational decision points and ensemble forecasts are thus not always available where needed. A statistical post-processor can be used to address these issues. The post-processor should (1) correct for systematic biases in flow timing and volume, (2) preserve the skill of the available raw forecasts, (3) preserve spatial and temporal correlation as well as the uncertainty in the forecasted flow data, (4) produce adjusted forecast ensembles that represent the variability of the observed hydrograph to be predicted, and (5) preserve individual forecast traces as equally likely. The post-processor should also allow for the translation of available ensemble forecasts to hydrologically similar locations where forecasts are not available. This paper introduces an ensemble post-processor (EPP) developed in support of New York City water supply operations. The EPP employs a general linear model (GLM) to (1) adjust available ensemble forecast traces and (2) create new ensembles for (nearby) locations where only historic flow observations are available. The EPP is calibrated by developing daily and aggregated statistical relationships form historical flow observations and model simulations. These are then used in operation to obtain the conditional probability density function (PDF) of the observations to be predicted, thus jointly adjusting individual ensemble members. These steps are executed in a normalized transformed space ('z'-space) to account for the strong non-linearity in the flow observations involved. A data window centered on each calibration date is used to minimize impacts from sampling errors and data noise. Testing on datasets from California and New York suggests that the EPP can successfully minimize biases in ensemble forecasts, while preserving the raw forecast skill in a 'days to weeks' forecast horizon and reproducing the variability of climatology for 'weeks to years' forecast horizons.

Predicting Information Flows in Network Traffic.

ERIC Educational Resources Information Center

Hinich, Melvin J.; Molyneux, Robert E.

2003-01-01

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

A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

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

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr; Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr

2015-03-10

We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap schememore » is introduced to numerically approximate the model’s flow equations.« less

46 CFR 122.304 - Navigation underway.

Code of Federal Regulations, 2014 CFR

2014-10-01

...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

46 CFR 122.304 - Navigation underway.

Code of Federal Regulations, 2013 CFR

2013-10-01

...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

46 CFR 122.304 - Navigation underway.

Code of Federal Regulations, 2011 CFR

2011-10-01

...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

46 CFR 122.304 - Navigation underway.

Code of Federal Regulations, 2012 CFR

2012-10-01

...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

Objective Lightning Probability Forecasts for East-Central Florida Airports

NASA Technical Reports Server (NTRS)

Crawford, Winfred C.

2013-01-01

The forecasters at the National Weather Service in Melbourne, FL, (NWS MLB) identified a need to make more accurate lightning forecasts to help alleviate delays due to thunderstorms in the vicinity of several commercial airports in central Florida at which they are responsible for issuing terminal aerodrome forecasts. Such forecasts would also provide safer ground operations around terminals, and would be of value to Center Weather Service Units serving air traffic controllers in Florida. To improve the forecast, the AMU was tasked to develop an objective lightning probability forecast tool for the airports using data from the National Lightning Detection Network (NLDN). The resulting forecast tool is similar to that developed by the AMU to support space launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) for use by the 45th Weather Squadron (45 WS) in previous tasks (Lambert and Wheeler 2005, Lambert 2007). The lightning probability forecasts are valid for the time periods and areas needed by the NWS MLB forecasters in the warm season months, defined in this task as May-September.

The impact of iterated games on traffic flow at noncontrolled intersections

NASA Astrophysics Data System (ADS)

Zhao, Chao; Jia, Ning

2015-05-01

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

Complex traffic flow that allows as well as hampers lane-changing intrinsically contains social-dilemma structures

NASA Astrophysics Data System (ADS)

Iwamura, Yoshiro; Tanimoto, Jun

2018-02-01

To investigate an interesting question as to whether or not social dilemma structures can be found in a realistic traffic flow reproduced by a model, we built a new microscopic model in which an intentional driver may try lane-changing to go in front of other vehicles and may hamper others’ lane-changes. Our model consists of twofold parts; cellular automaton emulating a real traffic flow and evolutionary game theory to implement a driver’s decision making-process. Numerical results reveal that a social dilemma like the multi-player chicken game or prisoner’s dilemma game emerges depending on the traffic phase. This finding implies that a social dilemma, which has been investigated by applied mathematics so far, hides behind a traffic flow, which has been explored by fluid dynamics. Highlight - Complex system of traffic flow with consideration of driver’s decision making process is concerned. - A new model dovetailing cellular automaton with game theory is established. - Statistical result from numerical simulations reveals a social dilemma structure underlying traffic flow. - The social dilemma is triggered by a driver’s egocentric actions of lane-changing and hampering other’s lane-change.

A cellular automaton model for ship traffic flow in waterways

NASA Astrophysics Data System (ADS)

Qi, Le; Zheng, Zhongyi; Gang, Longhui

2017-04-01

With the development of marine traffic, waterways become congested and more complicated traffic phenomena in ship traffic flow are observed. It is important and necessary to build a ship traffic flow model based on cellular automata (CAs) to study the phenomena and improve marine transportation efficiency and safety. Spatial discretization rules for waterways and update rules for ship movement are two important issues that are very different from vehicle traffic. To solve these issues, a CA model for ship traffic flow, called a spatial-logical mapping (SLM) model, is presented. In this model, the spatial discretization rules are improved by adding a mapping rule. And the dynamic ship domain model is considered in the update rules to describe ships' interaction more exactly. Take the ship traffic flow in the Singapore Strait for example, some simulations were carried out and compared. The simulations show that the SLM model could avoid ship pseudo lane-change efficiently, which is caused by traditional spatial discretization rules. The ship velocity change in the SLM model is consistent with the measured data. At finally, from the fundamental diagram, the relationship between traffic ability and the lengths of ships is explored. The number of ships in the waterway declines when the proportion of large ships increases.

Impact of multi-resolution analysis of artificial intelligence models inputs on multi-step ahead river flow forecasting

NASA Astrophysics Data System (ADS)

Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.

2013-12-01

Discrete wavelet transform was applied to decomposed ANN and ANFIS inputs.Novel approach of WNF with subtractive clustering applied for flow forecasting.Forecasting was performed in 1-5 step ahead, using multi-variate inputs.Forecasting accuracy of peak values and longer lead-time significantly improved.

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.

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.

Long-term flow forecasts based on climate and hydrologic modeling: Uruguay River basin

NASA Astrophysics Data System (ADS)

Tucci, Carlos Eduardo Morelli; Clarke, Robin Thomas; Collischonn, Walter; da Silva Dias, Pedro Leite; de Oliveira, Gilvan Sampaio

2003-07-01

This paper describes a procedure for predicting seasonal flow in the Rio Uruguay drainage basin (area 75,000 km2, lying in Brazilian territory), using sequences of future daily rainfall given by the global climate model (GCM) of the Brazilian agency for climate prediction (Centro de Previsão de Tempo e Clima, or CPTEC). Sequences of future daily rainfall given by this model were used as input to a rainfall-runoff model appropriate for large drainage basins. Forecasts of flow in the Rio Uruguay were made for the period 1995-2001 of the full record, which began in 1940. Analysis showed that GCM forecasts underestimated rainfall over almost all the basin, particularly in winter, although interannual variability in regional rainfall was reproduced relatively well. A statistical procedure was used to correct for the underestimation of rainfall. When the corrected rainfall sequences were transformed to flow by the hydrologic model, forecasts of flow in the Rio Uruguay basin were better than forecasts based on historic mean or median flows by 37% for monthly flows and by 54% for 3-monthly flows.

Empirical synchronized flow in oversaturated city traffic.

PubMed

Kerner, Boris S; Hemmerle, Peter; Koller, Micha; Hermanns, Gerhard; Klenov, Sergey L; Rehborn, Hubert; Schreckenberg, Michael

2014-09-01

Based on a study of anonymized GPS probe vehicle traces measured by personal navigation devices in vehicles randomly distributed in city traffic, empirical synchronized flow in oversaturated city traffic has been revealed. It turns out that real oversaturated city traffic resulting from speed breakdown in a city in most cases can be considered random spatiotemporal alternations between sequences of moving queues and synchronized flow patterns in which the moving queues do not occur.

Hybrid Stochastic Forecasting Model for Management of Large Open Water Reservoir with Storage Function

NASA Astrophysics Data System (ADS)

Kozel, Tomas; Stary, Milos

2017-12-01

The main advantage of stochastic forecasting is fan of possible value whose deterministic method of forecasting could not give us. Future development of random process is described better by stochastic then deterministic forecasting. Discharge in measurement profile could be categorized as random process. Content of article is construction and application of forecasting model for managed large open water reservoir with supply function. Model is based on neural networks (NS) and zone models, which forecasting values of average monthly flow from inputs values of average monthly flow, learned neural network and random numbers. Part of data was sorted to one moving zone. The zone is created around last measurement average monthly flow. Matrix of correlation was assembled only from data belonging to zone. The model was compiled for forecast of 1 to 12 month with using backward month flows (NS inputs) from 2 to 11 months for model construction. Data was got ridded of asymmetry with help of Box-Cox rule (Box, Cox, 1964), value r was found by optimization. In next step were data transform to standard normal distribution. The data were with monthly step and forecast is not recurring. 90 years long real flow series was used for compile of the model. First 75 years were used for calibration of model (matrix input-output relationship), last 15 years were used only for validation. Outputs of model were compared with real flow series. For comparison between real flow series (100% successfully of forecast) and forecasts, was used application to management of artificially made reservoir. Course of water reservoir management using Genetic algorithm (GE) + real flow series was compared with Fuzzy model (Fuzzy) + forecast made by Moving zone model. During evaluation process was founding the best size of zone. Results show that the highest number of input did not give the best results and ideal size of zone is in interval from 25 to 35, when course of management was almost same for all numbers from interval. Resulted course of management was compared with course, which was obtained from using GE + real flow series. Comparing results showed that fuzzy model with forecasted values has been able to manage main malfunction and artificially disorders made by model were founded essential, after values of water volume during management were evaluated. Forecasting model in combination with fuzzy model provide very good results in management of water reservoir with storage function and can be recommended for this purpose.

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.

A Sarsa(λ)-based control model for real-time traffic light coordination.

PubMed

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Development of a real-time crash risk prediction model incorporating the various crash mechanisms across different traffic states.

PubMed

Xu, Chengcheng; Wang, Wei; Liu, Pan; Zhang, Fangwei

2015-01-01

This study aimed to identify the traffic flow variables contributing to crash risks under different traffic states and to develop a real-time crash risk model incorporating the varying crash mechanisms across different traffic states. The crash, traffic, and geometric data were collected on the I-880N freeway in California in 2008 and 2009. This study considered 4 different traffic states in Wu's 4-phase traffic theory. They are free fluid traffic, bunched fluid traffic, bunched congested traffic, and standing congested traffic. Several different statistical methods were used to accomplish the research objective. The preliminary analysis showed that traffic states significantly affected crash likelihood, collision type, and injury severity. Nonlinear canonical correlation analysis (NLCCA) was conducted to identify the underlying phenomena that made certain traffic states more hazardous than others. The results suggested that different traffic states were associated with various collision types and injury severities. The matching of traffic flow characteristics and crash characteristics in NLCCA revealed how traffic states affected traffic safety. The logistic regression analyses showed that the factors contributing to crash risks were quite different across various traffic states. To incorporate the varying crash mechanisms across different traffic states, random parameters logistic regression was used to develop a real-time crash risk model. Bayesian inference based on Markov chain Monte Carlo simulations was used for model estimation. The parameters of traffic flow variables in the model were allowed to vary across different traffic states. Compared with the standard logistic regression model, the proposed model significantly improved the goodness-of-fit and predictive performance. These results can promote a better understanding of the relationship between traffic flow characteristics and crash risks, which is valuable knowledge in the pursuit of improving traffic safety on freeways through the use of dynamic safety management systems.

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin

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

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.

2011-08-15

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatialmore » scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.« less

Microscopic modeling of multi-lane highway traffic flow

NASA Astrophysics Data System (ADS)

Hodas, Nathan O.; Jagota, Anand

2003-12-01

We discuss a microscopic model for the study of multi-lane highway traffic flow dynamics. Each car experiences a force resulting from a combination of the desire of the driver to attain a certain velocity, aerodynamic drag, and change of the force due to car-car interactions. The model also includes multi-lane simulation capability and the ability to add and remove obstructions. We implement the model via a Java applet, which is used to simulate traffic jam formation, the effect of bottlenecks on traffic flow, and the existence of light, medium, and heavy traffic flow. The simulations also provide insight into how the properties of individual cars result in macroscopic behavior. Because the investigation of emergent characteristics is so common in physics, the study of traffic in this manner sheds new light on how the micro-to-macro transition works in general.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

An extended car-following model considering the appearing probability of truck and driver's characteristics

NASA Astrophysics Data System (ADS)

Rong, Ying; Wen, Huiying

2018-05-01

In this paper, the appearing probability of truck is introduced and an extended car-following model is presented to analyze the traffic flow based on the consideration of driver's characteristics, under honk environment. The stability condition of this proposed model is obtained through linear stability analysis. In order to study the evolution properties of traffic wave near the critical point, the mKdV equation is derived by the reductive perturbation method. The results show that the traffic flow will become more disorder for the larger appearing probability of truck. Besides, the appearance of leading truck affects not only the stability of traffic flow, but also the effect of other aspects on traffic flow, such as: driver's reaction and honk effect. The effects of them on traffic flow are closely correlated with the appearing probability of truck. Finally, the numerical simulations under the periodic boundary condition are carried out to verify the proposed model. And they are consistent with the theoretical findings.

Lattice hydrodynamic model based traffic control: A transportation cyber-physical system approach

NASA Astrophysics Data System (ADS)

Liu, Hui; Sun, Dihua; Liu, Weining

2016-11-01

Lattice hydrodynamic model is a typical continuum traffic flow model, which describes the jamming transition of traffic flow properly. Previous studies in lattice hydrodynamic model have shown that the use of control method has the potential to improve traffic conditions. In this paper, a new control method is applied in lattice hydrodynamic model from a transportation cyber-physical system approach, in which only one lattice site needs to be controlled in this control scheme. The simulation verifies the feasibility and validity of this method, which can ensure the efficient and smooth operation of the traffic flow.

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.

Traffic jam dynamics in stochastic cellular automata

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

Nagel, K.; Schreckenberg, M.

1995-09-01

Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA)more » and in NRW (Germany) for large scale microsimulations of network traffic.« less

Impact of traffic composition on accessibility as indicator of transport sustainability

NASA Astrophysics Data System (ADS)

Nahdalina; Hadiwardoyo, S. P.; Nahry

2017-05-01

Sustainable transport is closely related to quality of life in the community at present and in the future. Some indicators of transport sustainability are accessibility measurement of origin/destination, the operating costs of transport (vehicle operating cost or VOC) and external transportation costs (emission cost). The indicators could be combined into accessibility measurement model. In other case, almost traffic congestion occurred on the condition of mixed traffic. This paper aimed to analyse the indicator of transport sustainability through simulation under condition of various traffic composition. Various composition of truck to total traffic flow are 0%, 10% and 20%. Speed and V/C are calculated from traffic flow to estimate the VOC and emission cost. 5 VOC components and 3 types of emission cost (CO2, CH4 and N2O) are counted to be a travel cost. Accessibility measurement was calculated using travel cost and gravity model approaches. Result of the research shows that the total traffic flow has indirect impact on accessibility measurement if using travel cost approach. Meanwhile, the composition of traffic flow has an affect on accessibility measurement if using gravity model approach.

Virtualized Traffic: reconstructing traffic flows from discrete spatiotemporal data.

PubMed

Sewall, Jason; van den Berg, Jur; Lin, Ming C; Manocha, Dinesh

2011-01-01

We present a novel concept, Virtualized Traffic, to reconstruct and visualize continuous traffic flows from discrete spatiotemporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the positions of each car at two recorded locations on a highway and the corresponding time instances, our approach can reconstruct the traffic flows (i.e., the dynamic motions of multiple cars over time) between the two locations along the highway for immersive visualization of virtual cities or other environments. Our algorithm is applicable to high-density traffic on highways with an arbitrary number of lanes and takes into account the geometric, kinematic, and dynamic constraints on the cars. Our method reconstructs the car motion that automatically minimizes the number of lane changes, respects safety distance to other cars, and computes the acceleration necessary to obtain a smooth traffic flow subject to the given constraints. Furthermore, our framework can process a continuous stream of input data in real time, enabling the users to view virtualized traffic events in a virtual world as they occur. We demonstrate our reconstruction technique with both synthetic and real-world input. © 2011 IEEE Published by the IEEE Computer Society

Impact of Reservoir Operation to the Inflow Flood - a Case Study of Xinfengjiang Reservoir

NASA Astrophysics Data System (ADS)

Chen, L.

2017-12-01

Building of reservoir shall impact the runoff production and routing characteristics, and changes the flood formation. This impact, called as reservoir flood effect, could be divided into three parts, including routing effect, volume effect and peak flow effect, and must be evaluated in a whole by using hydrological model. After analyzing the reservoir flood formation, the Liuxihe Model for reservoir flood forecasting is proposed. The Xinfengjiang Reservoir is studied as a case. Results show that the routing effect makes peak flow appear 4 to 6 hours in advance, volume effect is bigger for large flood than small one, and when rainfall focus on the reservoir area, this effect also increases peak flow largely, peak flow effect makes peak flow increase 6.63% to 8.95%. Reservoir flood effect is obvious, which have significant impact to reservoir flood. If this effect is not considered in the flood forecasting model, the flood could not be forecasted accurately, particularly the peak flow. Liuxihe Model proposed for Xinfengjiang Reservoir flood forecasting has a good performance, and could be used for real-time flood forecasting of Xinfengjiang Reservoir.Key words: Reservoir flood effect, reservoir flood forecasting, physically based distributed hydrological model, Liuxihe Model, parameter optimization

Vehicle exhaust exposure in an incident case-control study of adult asthma.

PubMed

Modig, L; Järvholm, B; Rönnmark, E; Nyström, L; Lundbäck, B; Andersson, C; Forsberg, B

2006-07-01

The objective of this case-control study was to evaluate whether traffic-related air pollution exposure at home increases the risk of asthma in adults and to compare two commonly used exposure variables and differences between urban and rural living. Incident cases of asthma and matched controls of subjects aged 20-60 yrs were recruited in Luleå, Sweden. In total 203 cases and 203 controls were enrolled in the study. Exposure was estimated by traffic flow and measured levels of outdoor nitrogen dioxide (NO2) in the surrounding environment of each home, respectively. The relationship between measured levels of NO2 and traffic flow was studied using linear regression. The results indicated a nonsignificant tendency between living in a home close to a high traffic flow and an increased risk of asthma. The association between asthma and measured NO2 was weak and not significant, but the skin-prick test result acted as an effect modifier with a borderline significant association among positives. The correlation between traffic flow and outdoor NO2 was low. The results suggest that living close to high traffic flows might increase the asthma incidence in adults, while the tendency for nitrogen dioxide was only seen among atopics. Traffic flow and nitrogen dioxide had a lower than expected correlation.

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.

Satellite Altimetry based River Forecasting of Transboundary Flow

NASA Astrophysics Data System (ADS)

Hossain, F.; Siddique-E-Akbor, A.; Lee, H.; Shum, C.; Biancamaria, S.

2012-12-01

Forecasting of this transboundary flow in downstream nations however remains notoriously difficult due to the lack of basin-wide in-situ hydrologic measurements or its real-time sharing among nations. In addition, human regulation of upstream flow through diversion projects and dams, make hydrologic models less effective for forecasting on their own. Using the Ganges-Brahmaputra (GB) basin as an example, this study assesses the feasibility of using JASON-2 satellite altimetry for forecasting such transboundary flow at locations further inside the downstream nation of Bangladesh by propagating forecasts derived from upstream (Indian) locations through a hydrodynamic river model. The 5-day forecast of river levels at upstream boundary points inside Bangladesh are used to initialize daily simulation of the hydrodynamic river model and yield the 5-day forecast river level further downstream inside Bangladesh. The forecast river levels are then compared with the 5-day-later "now cast" simulation by the river model based on in-situ river level at the upstream boundary points in Bangladesh. Future directions for satellite-based forecasting of flow are also briefly overviewed.round tracks or virtual stations of JASON-2 (J2) altimeter over the GB basin shown in yellow lines. The locations where the track crosses a river and used for deriving forecasting rating curves is shown with a circle and station number (magenta- Brahmaputra basin; blue - Ganges basin). Circles without a station number represent the broader view of sampling by JASON-2 if all the ground tracks on main stem rivers and neighboring tributaries of Ganges and Brahmaputra are considered.

En route air traffic flow simulation.

DOT National Transportation Integrated Search

1971-01-01

The report covers the conception, design, development, and initial implementation of an advanced simulation technique applied to a study of national air traffic flow and its control by En Route Air Route Traffic Control Centers (ARTCC). It is intende...

Complexity of spatiotemporal traffic phenomena in flow of identical drivers: Explanation based on fundamental hypothesis of three-phase theory

NASA Astrophysics Data System (ADS)

Kerner, Boris S.

2012-03-01

Based on numerical simulations of a stochastic three-phase traffic flow model, we reveal the physics of the fundamental hypothesis of three-phase theory that, in contrast with a fundamental diagram of classical traffic flow theories, postulates the existence of a two-dimensional (2D) region of steady states of synchronized flow where a driver makes an arbitrary choice of a space gap (time headway) to the preceding vehicle. We find that macroscopic and microscopic spatiotemporal effects of the entire complexity of traffic congestion observed up to now in real measured traffic data can be explained by simulations of traffic flow consisting of identical drivers and vehicles, if a microscopic model used in these simulations incorporates the fundamental hypothesis of three-phase theory. It is shown that the driver's choice of space gaps within the 2D region of synchronized flow associated with the fundamental hypothesis of three-phase theory can qualitatively change types of congested patterns that can emerge at a highway bottleneck. In particular, if drivers choose long enough spaces gaps associated with the fundamental hypothesis, then general patterns, which consist of synchronized flow and wide moving jams, do not emerge independent of the flow rates and bottleneck characteristics: Even at a heavy bottleneck leading to a very low speed within congested patterns, only synchronized flow patterns occur in which no wide moving jams emerge spontaneously.

Complexity of spatiotemporal traffic phenomena in flow of identical drivers: explanation based on fundamental hypothesis of three-phase theory.

PubMed

Kerner, Boris S

2012-03-01

Based on numerical simulations of a stochastic three-phase traffic flow model, we reveal the physics of the fundamental hypothesis of three-phase theory that, in contrast with a fundamental diagram of classical traffic flow theories, postulates the existence of a two-dimensional (2D) region of steady states of synchronized flow where a driver makes an arbitrary choice of a space gap (time headway) to the preceding vehicle. We find that macroscopic and microscopic spatiotemporal effects of the entire complexity of traffic congestion observed up to now in real measured traffic data can be explained by simulations of traffic flow consisting of identical drivers and vehicles, if a microscopic model used in these simulations incorporates the fundamental hypothesis of three-phase theory. It is shown that the driver's choice of space gaps within the 2D region of synchronized flow associated with the fundamental hypothesis of three-phase theory can qualitatively change types of congested patterns that can emerge at a highway bottleneck. In particular, if drivers choose long enough spaces gaps associated with the fundamental hypothesis, then general patterns, which consist of synchronized flow and wide moving jams, do not emerge independent of the flow rates and bottleneck characteristics: Even at a heavy bottleneck leading to a very low speed within congested patterns, only synchronized flow patterns occur in which no wide moving jams emerge spontaneously.

A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination

PubMed Central

Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183

Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

NASA Technical Reports Server (NTRS)

Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

2013-01-01

Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

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.

New full velocity difference model considering the driver’s heterogeneity of the disturbance risk preference for car-following theory

NASA Astrophysics Data System (ADS)

Zeng, You-Zhi; Zhang, Ning

2016-12-01

This paper proposes a new full velocity difference model considering the driver’s heterogeneity of the disturbance risk preference for car-following theory to investigate the effects of the driver’s heterogeneity of the disturbance risk preference on traffic flow instability when the driver reacts to the relative velocity. We obtain traffic flow instability condition and the calculation method of the unstable region headway range and the probability of traffic congestion caused by a small disturbance. The analysis shows that has important effects the driver’s heterogeneity of the disturbance risk preference on traffic flow instability: (1) traffic flow instability is independent of the absolute size of the driver’s disturbance risk preference coefficient and depends on the ratio of the preceding vehicle driver’s disturbance risk preference coefficient to the following vehicle driver’s disturbance risk preference coefficient; (2) the smaller the ratio of the preceding vehicle driver’s disturbance risk preference coefficient to the following vehicle driver’s disturbance risk preference coefficient, the smaller traffic flow instability and vice versa. It provides some viable ideas to suppress traffic congestion.

Analysis of the effect of older drivers’ driving behaviors on traffic flow based on a modified CA model

NASA Astrophysics Data System (ADS)

Jian, Mei-Ying; Shi, Jing; Liu, Yang

2016-09-01

As the global population ages, there are more and more older drivers on the road. The decline in driving performance of older drivers may influence the properties of traffic flow and safety. The purpose of this paper is to investigate the effect of older drivers’ driving behaviors on traffic flow. A modified cellular automaton (CA) model which takes driving behaviors of older drivers into account is proposed. The simulation results indicate that older drivers’ driving behaviors induce a reduction in traffic flow especially when the density is higher than 15 vehicles per km per lane and an increase in Lane-changing frequency. The analysis of stability shows that a number of disturbances could frequently emerge, be propagated and eventually dissipate in this modified model. The results also reflect that with the increase of older drivers on the road, the probability of the occurrence of rear-end collisions increases greatly and obviously. Furthermore, the value of acceleration influences the traffic flow and safety significantly. These results provide the theoretical basis and reference for the traffic management departments to develop traffic management measure in the aging society.

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...

Physics of traffic gridlock in a city.

PubMed

Kerner, Boris S

2011-10-01

Based on simulations of stochastic three-phase and two-phase traffic flow models, we reveal that at a signalized city intersection under small link inflow rates at which a vehicle queue developed during the red phase of the light signal dissolves fully during the green phase, i.e., no traffic gridlock should be expected, nevertheless, spontaneous traffic breakdown with subsequent city gridlock occurs with some probability after a random time delay. In most cases, this traffic breakdown is initiated by a phase transition from free flow to a synchronized flow occurring upstream of the queue at the light signal. The probability of traffic breakdown at the light signal is an increasing function of the link inflow rate and duration of the red phase of the light signal.

Phase transitions in traffic flow on multilane roads.

PubMed

Kerner, Boris S; Klenov, Sergey L

2009-11-01

Based on empirical and numerical analyses of vehicular traffic, the physics of spatiotemporal phase transitions in traffic flow on multilane roads is revealed. The complex dynamics of moving jams observed in single vehicle data measured by video cameras on American highways is explained by the nucleation-interruption effect in synchronized flow, i.e., the spontaneous nucleation of a narrow moving jam with the subsequent jam dissolution. We find that (i) lane changing, vehicle merging from on-ramps, and vehicle leaving to off-ramps result in different traffic phases-free flow, synchronized flow, and wide moving jams-occurring and coexisting in different road lanes as well as in diverse phase transitions between the traffic phases; (ii) in synchronized flow, the phase transitions are responsible for a non-regular moving jam dynamics that explains measured single vehicle data: moving jams emerge and dissolve randomly at various road locations in different lanes; (iii) the phase transitions result also in diverse expanded general congested patterns occurring at closely located bottlenecks.

Capacity-constrained traffic assignment in networks with residual queues

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

Lam, W.H.K.; Zhang, Y.

2000-04-01

This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less

Hysteresis phenomena of the intelligent driver model for traffic flow

NASA Astrophysics Data System (ADS)

Dahui, Wang; Ziqiang, Wei; Ying, Fan

2007-07-01

We present hysteresis phenomena of the intelligent driver model for traffic flow in a circular one-lane roadway. We show that the microscopic structure of traffic flow is dependent on its initial state by plotting the fraction of congested vehicles over the density, which shows a typical hysteresis loop, and by investigating the trajectories of vehicles on the velocity-over-headway plane. We find that the trajectories of vehicles on the velocity-over-headway plane, which usually show a hysteresis loop, include multiple loops. We also point out the relations between these hysteresis loops and the congested jams or high-density clusters in traffic flow.

A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

PubMed

Shang, Qiang; Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

2016-01-01

Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine

PubMed Central

Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

2016-01-01

Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust. PMID:27551829

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 ...

Traffic Flow Management Using Aggregate Flow Models and the Development of Disaggregation Methods

NASA Technical Reports Server (NTRS)

Sun, Dengfeng; Sridhar, Banavar; Grabbe, Shon

2010-01-01

A linear time-varying aggregate traffic flow model can be used to develop Traffic Flow Management (tfm) strategies based on optimization algorithms. However, there are no methods available in the literature to translate these aggregate solutions into actions involving individual aircraft. This paper describes and implements a computationally efficient disaggregation algorithm, which converts an aggregate (flow-based) solution to a flight-specific control action. Numerical results generated by the optimization method and the disaggregation algorithm are presented and illustrated by applying them to generate TFM schedules for a typical day in the U.S. National Airspace System. The results show that the disaggregation algorithm generates control actions for individual flights while keeping the air traffic behavior very close to the optimal solution.

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

PubMed

Torija, Antonio J; Ruiz, Diego P

2012-10-01

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

The Impact of Large Urban Structural Elements on Traffic Flow   a Case Study of Danwei and Xiaoqu in Shanghai

NASA Astrophysics Data System (ADS)

Lyu, H.; Ding, L.; Fan, H.; Meng, L.

2017-09-01

Danwei (working unit) and Xiaoqu (residential community) are two typical and unique structural urban elements in China. The interior roads of Danwei and Xiaoqu are usually not accessible for the public. Recently, there is a call for opening these interior roads to the public to improve road network structure and optimize traffic flow. In this paper we investigate the impact of Danwei and Xiaoqu on their neighbouring traffic quantitatively. By taking into consideration of origins and destinations (ODs) distributions and route selection behaviours (e.g., shortest paths), we propose an extended betweenness centrality to investigate the traffic flow in two scenarios 1) the interior roads of Danwei and Xiaoqu are excluded from urban road network, 2) the interior roads are integrated into road network. A Danwei and a Xiaoqu in Shanghai are used as the study area. The preliminary results show the feasibility of our extended betweenness centrality in investigating the traffic flow patterns and reveal the quantitative changes of the traffic flow after opening interior roads.

TRANPLAN and GIS support for agencies in Alabama

DOT National Transportation Integrated Search

2001-08-06

Travel demand models are computerized programs intended to forecast future roadway traffic volumes for a community based on selected socioeconomic variables and travel behavior algorithms. Software to operate these travel demand models is currently a...

Advanced Flow Control as a Management Tool in the National Airspace System

NASA Technical Reports Server (NTRS)

Wugalter, S.

1974-01-01

Advanced Flow Control is closely related to Air Traffic Control. Air Traffic Control is the business of the Federal Aviation Administration. To formulate an understanding of advanced flow control and its use as a management tool in the National Airspace System, it becomes necessary to speak somewhat of air traffic control, the role of FAA, and their relationship to advanced flow control. Also, this should dispell forever, any notion that advanced flow control is the inspirational master valve scheme to be used on the Alaskan Oil Pipeline.

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.

Verification of Ensemble Forecasts for the New York City Operations Support Tool

NASA Astrophysics Data System (ADS)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

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.

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.

FAA Aviation Forecasts Fiscal Years 1988-1999.

DTIC Science & Technology

1988-02-01

in the 48 contiguous States, Hawaii, Puerto Rico, and the U.S. Virgin Islands. Excluded fromn the data base is activity in Alaska, other U.S...passengerl miles increased b%-’"’. 17.2 percent. Traffic in Hawaii, Puerto Rico, and the U.S. Virgin Islands, ., Ihio wevr, haid slower growth with passenger...trip length for Hawaii/Puerto Rico/ Virgin Islands is expected to remain constant at 98.0 miles over the forecast period. The average industry load

The Loss of Efficiency Caused by Agents’ Uncoordinated Routing in Transport Networks

PubMed Central

Wang, Junjie; Wang, Pu

2014-01-01

Large-scale daily commuting data were combined with detailed geographical information system (GIS) data to analyze the loss of transport efficiency caused by drivers’ uncoordinated routing in urban road networks. We used Price of Anarchy (POA) to quantify the loss of transport efficiency and found that both volume and distribution of human mobility demand determine the POA. In order to reduce POA, a small number of highways require considerable decreases in traffic, and their neighboring arterial roads need to attract more traffic. The magnitude of the adjustment in traffic flow can be estimated using the fundamental measure traffic flow only, which is widely available and easy to collect. Surprisingly, the most congested roads or the roads with largest traffic flow were not those requiring the most reduction of traffic. This study can offer guidance for the optimal control of urban traffic and facilitate improvements in the efficiency of transport networks. PMID:25349995

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.

Super Ensemble-based Aviation Turbulence Guidance (SEATG) for Air Traffic Management (ATM)

NASA Astrophysics Data System (ADS)

Kim, Jung-Hoon; Chan, William; Sridhar, Banavar; Sharman, Robert

2014-05-01

Super Ensemble (ensemble of ten turbulence metrics from time-lagged ensemble members of weather forecast data)-based Aviation Turbulence Guidance (SEATG) is developed using Weather Research and Forecasting (WRF) model and in-situ eddy dissipation rate (EDR) observations equipped on commercial aircraft over the contiguous United States. SEATG is a sequence of five procedures including weather modeling, calculating turbulence metrics, mapping EDR-scale, evaluating metrics, and producing final SEATG forecast. This uses similar methodology to the operational Graphic Turbulence Guidance (GTG) with three major improvements. First, SEATG use a higher resolution (3-km) WRF model to capture cloud-resolving scale phenomena. Second, SEATG computes turbulence metrics for multiple forecasts that are combined at the same valid time resulting in an time-lagged ensemble of multiple turbulence metrics. Third, SEATG provides both deterministic and probabilistic turbulence forecasts to take into account weather uncertainties and user demands. It is found that the SEATG forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on 7-8 Sep 2012. And, overall performance skill of deterministic SEATG against the observed EDR data during this period is superior to any single turbulence metrics. Finally, probabilistic SEATG is used as an example application of turbulence forecast for air-traffic management. In this study, a simple Wind-Optimal Route (WOR) passing through the potential areas of probabilistic SEATG and Lateral Turbulence Avoidance Route (LTAR) taking into account the SEATG are calculated at z = 35000 ft (z = 12 km) from Los Angeles to John F. Kennedy international airports. As a result, WOR takes total of 239 minutes with 16 minutes of SEATG areas for 40% of moderate turbulence potential, while LTAR takes total of 252 minutes travel time that 5% of fuel would be additionally consumed to entirely avoid the moderate SEATG regions.

Post-processing of a low-flow forecasting system in the Thur basin (Switzerland)

NASA Astrophysics Data System (ADS)

Bogner, Konrad; Joerg-Hess, Stefanie; Bernhard, Luzi; Zappa, Massimiliano

2015-04-01

Low-flows and droughts are natural hazards with potentially severe impacts and economic loss or damage in a number of environmental and socio-economic sectors. As droughts develop slowly there is time to prepare and pre-empt some of these impacts. Real-time information and forecasting of a drought situation can therefore be an effective component of drought management. Although Switzerland has traditionally been more concerned with problems related to floods, in recent years some unprecedented low-flow situations have been experienced. Driven by the climate change debate a drought information platform has been developed to guide water resources management during situations where water resources drop below critical low-flow levels characterised by the indices duration (time between onset and offset), severity (cumulative water deficit) and magnitude (severity/duration). However to gain maximum benefit from such an information system it is essential to remove the bias from the meteorological forecast, to derive optimal estimates of the initial conditions, and to post-process the stream-flow forecasts. Quantile mapping methods for pre-processing the meteorological forecasts and improved data assimilation methods of snow measurements, which accounts for much of the seasonal stream-flow predictability for the majority of the basins in Switzerland, have been tested previously. The objective of this study is the testing of post-processing methods in order to remove bias and dispersion errors and to derive the predictive uncertainty of a calibrated low-flow forecast system. Therefore various stream-flow error correction methods with different degrees of complexity have been applied and combined with the Hydrological Uncertainty Processor (HUP) in order to minimise the differences between the observations and model predictions and to derive posterior probabilities. The complexity of the analysed error correction methods ranges from simple AR(1) models to methods including wavelet transformations and support vector machines. These methods have been combined with forecasts driven by Numerical Weather Prediction (NWP) systems with different temporal and spatial resolutions, lead-times and different numbers of ensembles covering short to medium to extended range forecasts (COSMO-LEPS, 10-15 days, monthly and seasonal ENS) as well as climatological forecasts. Additionally the suitability of various skill scores and efficiency measures regarding low-flow predictions will be tested. Amongst others the novel 2afc (2 alternatives forced choices) score and the quantile skill score and its decompositions will be applied to evaluate the probabilistic forecasts and the effects of post-processing. First results of the performance of the low-flow predictions of the hydrological model PREVAH initialised with different NWP's will be shown.

A system for forecasting and monitoring cash flow : phase I : forecasting payments on construction contracts.

DOT National Transportation Integrated Search

1983-01-01

The research on which this paper is based was performed as part of a study to develop a system for generating a one-to-two year forecast of monthly cash flows for the Virginia Department of Highways and Transportation. It revealed that presently used...

Non-urban mobile radio market demand forecast

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Cooper, J.

1982-01-01

A national nonmetropolitan land mobile traffic model for 1990-2000 addresses user classes, density classes, traffic mix statistics, distance distribution, geographic distribution, price elasticity, and service quality elasticity. Traffic demands for business, special industrial, and police were determined on the basis of surveys in 73 randomly selected nonurban counties. The selected services represent 69% of total demand. The results were extrapolated to all services in the non-SMSA areas of the contiguous United States. Radiotelephone services were considered separately. Total non-SMSA mobile radio demand (one way) estimates are given. General functional requirements include: hand portability, privacy, reduction of blind spots, two way data transmission, position location, slow scan imagery.

Seasonal forecasting of discharge for the Raccoon River, Iowa

NASA Astrophysics Data System (ADS)

Slater, Louise; Villarini, Gabriele; Bradley, Allen; Vecchi, Gabriel

2016-04-01

The state of Iowa (central United States) is regularly afflicted by severe natural hazards such as the 2008/2013 floods and the 2012 drought. To improve preparedness for these catastrophic events and allow Iowans to make more informed decisions about the most suitable water management strategies, we have developed a framework for medium to long range probabilistic seasonal streamflow forecasting for the Raccoon River at Van Meter, a 8900-km2 catchment located in central-western Iowa. Our flow forecasts use statistical models to predict seasonal discharge for low to high flows, with lead forecasting times ranging from one to ten months. Historical measurements of daily discharge are obtained from the U.S. Geological Survey (USGS) at the Van Meter stream gage, and used to compute quantile time series from minimum to maximum seasonal flow. The model is forced with basin-averaged total seasonal precipitation records from the PRISM Climate Group and annual row crop production acreage from the U.S. Department of Agriculture's National Agricultural Statistics Services database. For the forecasts, we use corn and soybean production from the previous year (persistence forecast) as a proxy for the impacts of agricultural practices on streamflow. The monthly precipitation forecasts are provided by eight Global Climate Models (GCMs) from the North American Multi-Model Ensemble (NMME), with lead times ranging from 0.5 to 11.5 months, and a resolution of 1 decimal degree. Additionally, precipitation from the month preceding each season is used to characterize antecedent soil moisture conditions. The accuracy of our modelled (1927-2015) and forecasted (2001-2015) discharge values is assessed by comparison with the observed USGS data. We explore the sensitivity of forecast skill over the full range of lead times, flow quantiles, forecast seasons, and with each GCM. Forecast skill is also examined using different formulations of the statistical models, as well as NMME forecast weighting procedures based on the computed potential skill (historical forecast accuracy) of the different GCMs. We find that the models describe the year-to-year variability in streamflow accurately, as well as the overall tendency towards increasing (and more variable) discharge over time. Surprisingly, forecast skill does not decrease markedly with lead time, and high flows tend to be well predicted, suggesting that these forecasts may have considerable practical applications. Further, the seasonal flow forecast accuracy is substantially improved by weighting the contribution of individual GCMs to the forecasts, and also by the inclusion of antecedent precipitation. Our results can provide critical information for adaptation strategies aiming to mitigate the costs and disruptions arising from flood and drought conditions, and allow us to determine how far in advance skillful forecasts can be issued. The availability of these discharge forecasts would have major societal and economic benefits for hydrology and water resources management, agriculture, disaster forecasts and prevention, energy, finance and insurance, food security, policy-making and public authorities, and transportation.

Microscopic theory of traffic-flow instability governing traffic breakdown at highway bottlenecks: Growing wave of increase in speed in synchronized flow.

PubMed

Kerner, Boris S

2015-12-01

We have revealed a growing local speed wave of increase in speed that can randomly occur in synchronized flow (S) at a highway bottleneck. The development of such a traffic flow instability leads to free flow (F) at the bottleneck; therefore, we call this instability an S→F instability. Whereas the S→F instability leads to a local increase in speed (growing acceleration wave), in contrast, the classical traffic flow instability introduced in the 1950s-1960s and incorporated later in a huge number of traffic flow models leads to a growing wave of a local decrease in speed (growing deceleration wave). We have found that the S→F instability can occur only if there is a finite time delay in driver overacceleration. The initial speed disturbance of increase in speed (called "speed peak") that initiates the S→F instability occurs usually at the downstream front of synchronized flow at the bottleneck. There can be many speed peaks with random amplitudes that occur randomly over time. It has been found that the S→F instability exhibits a nucleation nature: Only when a speed peak amplitude is large enough can the S→F instability occur; in contrast, speed peaks of smaller amplitudes cause dissolving speed waves of a local increase in speed (dissolving acceleration waves) in synchronized flow. We have found that the S→F instability governs traffic breakdown-a phase transition from free flow to synchronized flow (F→S transition) at the bottleneck: The nucleation nature of the S→F instability explains the metastability of free flow with respect to an F→S transition at the bottleneck.

Microscopic theory of traffic-flow instability governing traffic breakdown at highway bottlenecks: Growing wave of increase in speed in synchronized flow

NASA Astrophysics Data System (ADS)

Kerner, Boris S.

2015-12-01

We have revealed a growing local speed wave of increase in speed that can randomly occur in synchronized flow (S) at a highway bottleneck. The development of such a traffic flow instability leads to free flow (F) at the bottleneck; therefore, we call this instability an S →F instability. Whereas the S →F instability leads to a local increase in speed (growing acceleration wave), in contrast, the classical traffic flow instability introduced in the 1950s-1960s and incorporated later in a huge number of traffic flow models leads to a growing wave of a local decrease in speed (growing deceleration wave). We have found that the S →F instability can occur only if there is a finite time delay in driver overacceleration. The initial speed disturbance of increase in speed (called "speed peak") that initiates the S →F instability occurs usually at the downstream front of synchronized flow at the bottleneck. There can be many speed peaks with random amplitudes that occur randomly over time. It has been found that the S →F instability exhibits a nucleation nature: Only when a speed peak amplitude is large enough can the S →F instability occur; in contrast, speed peaks of smaller amplitudes cause dissolving speed waves of a local increase in speed (dissolving acceleration waves) in synchronized flow. We have found that the S →F instability governs traffic breakdown—a phase transition from free flow to synchronized flow (F →S transition) at the bottleneck: The nucleation nature of the S →F instability explains the metastability of free flow with respect to an F →S transition at the bottleneck.

Macroscopic modeling of freeway traffic using an artificial neural network

DOT National Transportation Integrated Search

1997-01-01

Traffic flow on freeways is a complex process that often is described by a set of highly nonlinear, dynamic equations in the form of a macroscopic traffic flow model. However, some of the existing macroscopic models have been found to exhibit instabi...

Fast and optimized methodology to generate road traffic emission inventories and their uncertainties

NASA Astrophysics Data System (ADS)

Blond, N.; Ho, B. Q.; Clappier, A.

2012-04-01

Road traffic emissions are one of the main sources of air pollution in the cities. They are also the main sources of uncertainties in the air quality numerical models used to forecast and define abatement strategies. Until now, the available models for generating road traffic emission always required a big effort, money and time. This inhibits decisions to preserve air quality, especially in developing countries where road traffic emissions are changing very fast. In this research, we developed a new model designed to fast produce road traffic emission inventories. This model, called EMISENS, combines the well-known top-down and bottom-up approaches to force them to be coherent. A Monte Carlo methodology is included for computing emission uncertainties and the uncertainty rate due to each input parameters. This paper presents the EMISENS model and a demonstration of its capabilities through an application over Strasbourg region (Alsace), France. Same input data as collected for Circul'air model (using bottom-up approach) which has been applied for many years to forecast and study air pollution by the Alsatian air quality agency, ASPA, are used to evaluate the impact of several simplifications that a user could operate . These experiments give the possibility to review older methodologies and evaluate EMISENS results when few input data are available to produce emission inventories, as in developing countries and assumptions need to be done. We show that same average fraction of mileage driven with a cold engine can be used for all the cells of the study domain and one emission factor could replace both cold and hot emission factors.

An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

PubMed

Bongiorno, Christian; Miccichè, Salvatore; Mantegna, Rosario N

2017-01-01

We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast.

An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management

PubMed Central

Bongiorno, Christian; Mantegna, Rosario N.

2017-01-01

We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers’ operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast. PMID:28419160

Cyber Capability Development Centre (CCDC) Private Cloud Design

DTIC Science & Technology

2014-11-01

68 8.4 Shared Services Canada (SSC) Controlled Firewall .......................................................... 69 9 Cloud...opposed to east-west traffic (VM to VM). With North-South traffic, Shared Services Canada will want to ensure that the lab environment is contained. One...way traffic flow into the lab should be acceptable, Shared Services Canada will need to ensure that traffic doesn’t flow north or out of the CCDC

Enhanced Framework for Modeling Urban Truck Trips

DOT National Transportation Integrated Search

1998-09-16

Recently there has been renewed interest in modeling urban truck movements. : This is potentially important for improving traffic forecasts as well as for a : host of other applications including ITS. There are unique aspects of urban : freight movem...

Small city synthesis of transportation planning and economic development : user's guide

DOT National Transportation Integrated Search

1999-10-01

Using Alice, Texas, as a model, a template has been developed to increase the cooperation and communication between transportation planning and economic development groups. The template establishes a foundation for coordinating traffic forecasts with...

Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model

PubMed Central

Dou, Fei; Jia, Limin; Wang, Li; Xu, Jie; Huang, Yakun

2014-01-01

Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models. PMID:25431586

Air pollution forecasting in Ankara, Turkey using air pollution index and its relation to assimilative capacity of the atmosphere.

PubMed

Genc, D Deniz; Yesilyurt, Canan; Tuncel, Gurdal

2010-07-01

Spatial and temporal variations in concentrations of CO, NO, NO(2), SO(2), and PM(10), measured between 1999 and 2000, at traffic-impacted and residential stations in Ankara were investigated. Air quality in residential areas was found to be influenced by traffic activities in the city. Pollutant ratios were proven to be reliable tracers to differentiate between different sources. Air pollution index (API) of the whole city was calculated to evaluate the level of air quality in Ankara. Multiple linear regression model was developed for forecasting API in Ankara. The correlation coefficients were found to be 0.79 and 0.63 for different time periods. The assimilative capacity of Ankara atmosphere was calculated in terms of ventilation coefficient (VC). The relation between API and VC was investigated and found that the air quality in Ankara was determined by meteorology rather than emissions.

Expanding Regional Airport Usage to Accommodate Increased Air Traffic Demand

NASA Technical Reports Server (NTRS)

Russell, Carl R.

2009-01-01

Small regional airports present an underutilized source of capacity in the national air transportation system. This study sought to determine whether a 50 percent increase in national operations could be achieved by limiting demand growth at large hub airports and instead growing traffic levels at the surrounding regional airports. This demand scenario for future air traffic in the United States was generated and used as input to a 24-hour simulation of the national airspace system. Results of the demand generation process and metrics predicting the simulation results are presented, in addition to the actual simulation results. The demand generation process showed that sufficient runway capacity exists at regional airports to offload a significant portion of traffic from hub airports. Predictive metrics forecast a large reduction of delays at most major airports when demand is shifted. The simulation results then show that offloading hub traffic can significantly reduce nationwide delays.

Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

NASA Technical Reports Server (NTRS)

Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

2016-01-01

A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

Military, Charter, Unreported Domestic Traffic and General Aviation 1976, 1984, 1992, and 2015 Emission Scenarios

NASA Technical Reports Server (NTRS)

Mortlock, Alan; VanAlstyne, Richard

1998-01-01

The report describes development of databases estimating aircraft engine exhaust emissions for the years 1976 and 1984 from global operations of Military, Charter, historic Soviet and Chinese, Unreported Domestic traffic, and General Aviation (GA). These databases were developed under the National Aeronautics and Space Administration's (NASA) Advanced Subsonic Assessment (AST). McDonnell Douglas Corporation's (MDC), now part of the Boeing Company has previously estimated engine exhaust emissions' databases for the baseline year of 1992 and a 2015 forecast year scenario. Since their original creation, (Ward, 1994 and Metwally, 1995) revised technology algorithms have been developed. Additionally, GA databases have been created and all past NIDC emission inventories have been updated to reflect the new technology algorithms. Revised data (Baughcum, 1996 and Baughcum, 1997) for the scheduled inventories have been used in this report to provide a comparison of the total aviation emission forecasts from various components. Global results of two historic years (1976 and 1984), a baseline year (1992) and a forecast year (2015) are presented. Since engine emissions are directly related to fuel usage, an overview of individual aviation annual global fuel use for each inventory component is also given in this report.

An Operational Short-Term Forecasting System for Regional Hydropower Management

NASA Astrophysics Data System (ADS)

Gronewold, A.; Labuhn, K. A.; Calappi, T. J.; MacNeil, A.

2017-12-01

The Niagara River is the natural outlet of Lake Erie and drains four of the five Great lakes. The river is used to move commerce and is home to both sport fishing and tourism industries. It also provides nearly 5 million kilowatts of hydropower for approximately 3.9 million homes. Due to a complex international treaty and the necessity of balancing water needs for an extensive tourism industry, the power entities operating on the river require detailed and accurate short-term river flow forecasts to maximize power output. A new forecast system is being evaluated that takes advantage of several previously independent components including the NOAA Lake Erie operational Forecast System (LEOFS), a previously developed HEC-RAS model, input from the New York Power Authority(NYPA) and Ontario Power Generation (OPG) and lateral flow forecasts for some of the tributaries provided by the NOAA Northeast River Forecast Center (NERFC). The Corps of Engineers updated the HEC-RAS model of the upper Niagara River to use the output forcing from LEOFS and a planned Grass Island Pool elevation provided by the power entities. The entire system has been integrated at the NERFC; it will be run multiple times per day with results provided to the Niagara River Control Center operators. The new model helps improve discharge forecasts by better accounting for dynamic conditions on Lake Erie. LEOFS captures seiche events on the lake that are often several meters of displacement from still water level. These seiche events translate into flow spikes that HEC-RAS routes downstream. Knowledge of the peak arrival time helps improve operational decisions at the Grass Island Pool. This poster will compare and contrast results from the existing operational flow forecast and the new integrated LEOFS/HEC-RAS forecast. This additional model will supply the Niagara River Control Center operators with multiple forecasts of flow to help improve forecasting under a wider variety of conditions.

Traffic management simulation development : summary.

DOT National Transportation Integrated Search

2011-01-01

Increasingly, Florida traffic is monitored electronically by components of the Intelligent Traffic System (ITS), which send data to regional traffic management centers and assist management of traffic flows and incident response using software called...

Capacity Estimation Model for Signalized Intersections under the Impact of Access Point

PubMed Central

Zhao, Jing; Li, Peng; Zhou, Xizhao

2016-01-01

Highway Capacity Manual 2010 provides various factors to adjust the base saturation flow rate for the capacity analysis of signalized intersections. No factors, however, is considered for the potential change of signalized intersections capacity caused by the access point closeing to the signalized intersection. This paper presented a theoretical model to estimate the lane group capacity at signalized intersections with the consideration of the effects of access points. Two scenarios of access point locations, upstream or downstream of the signalized intersection, and impacts of six types of access traffic flow are taken into account. The proposed capacity model was validated based on VISSIM simulation. Results of extensive numerical analysis reveal the substantial impact of access point on the capacity, which has an inverse correlation with both the number of major street lanes and the distance between the intersection and access point. Moreover, among the six types of access traffic flows, the access traffic flow 1 (right-turning traffic from major street), flow 4 (left-turning traffic from access point), and flow 5 (left-turning traffic from major street) cause a more significant effect on lane group capacity than others. Some guidance on the mitigation of the negative effect is provided for practitioners. PMID:26726998

Two-lane traffic-flow model with an exact steady-state solution.

PubMed

Kanai, Masahiro

2010-12-01

We propose a stochastic cellular-automaton model for two-lane traffic flow based on the misanthrope process in one dimension. The misanthrope process is a stochastic process allowing for an exact steady-state solution; hence, we have an exact flow-density diagram for two-lane traffic. In addition, we introduce two parameters that indicate, respectively, driver's driving-lane preference and passing-lane priority. Due to the additional parameters, the model shows a deviation of the density ratio for driving-lane use and a biased lane efficiency in flow. Then, a mean-field approach explicitly describes the asymmetric flow by the hop rates, the driving-lane preference, and the passing-lane priority. Meanwhile, the simulation results are in good agreement with an observational data, and we thus estimate these parameters. We conclude that the proposed model successfully produces two-lane traffic flow particularly with the driving-lane preference and the passing-lane priority.

Forecasting the Emergency Department Patients Flow.

PubMed

Afilal, Mohamed; Yalaoui, Farouk; Dugardin, Frédéric; Amodeo, Lionel; Laplanche, David; Blua, Philippe

2016-07-01

Emergency department (ED) have become the patient's main point of entrance in modern hospitals causing it frequent overcrowding, thus hospital managers are increasingly paying attention to the ED in order to provide better quality service for patients. One of the key elements for a good management strategy is demand forecasting. In this case, forecasting patients flow, which will help decision makers to optimize human (doctors, nurses…) and material(beds, boxs…) resources allocation. The main interest of this research is forecasting daily attendance at an emergency department. The study was conducted on the Emergency Department of Troyes city hospital center, France, in which we propose a new practical ED patients classification that consolidate the CCMU and GEMSA categories into one category and innovative time-series based models to forecast long and short term daily attendance. The models we developed for this case study shows very good performances (up to 91,24 % for the annual Total flow forecast) and robustness to epidemic periods.

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.

Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

NASA Astrophysics Data System (ADS)

Kotegawa, Tatsuya

Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high robustness is achievable only in exchange of lower passenger travel and fuel burn efficiency. However, increase in the network density can mitigate this trade-off.

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

Economic development, mobility and traffic accidents in Algeria.

PubMed

Bougueroua, M; Carnis, L

2016-07-01

The aim of this contribution is to estimate the impact of road economic conditions and mobility on traffic accidents for the case of Algeria. Using the cointegration approach and vector error correction model (VECM), we will examine simultaneously short term and long-term impacts between the number of traffic accidents, fuel consumption and gross domestic product (GDP) per capital, over the period 1970-2013. The main results of the estimation show that the number of traffic accidents in Algeria is positively influenced by the GDP per capita in the short and long term. It implies that a higher economic development worsens the road safety situation. However, the new traffic rules adopted in 2009 have an impact on the forecast trend of traffic accidents, meaning efficient public policy could improve the situation. This result calls for a strong political commitment with effective countermeasures for avoiding the further deterioration of road safety record in Algeria. Copyright © 2016 Elsevier Ltd. All rights reserved.

Research on Closed Residential Area Based on Balanced Distribution Theory

NASA Astrophysics Data System (ADS)

Lan, Si; Fang, Ni; Lin, Hai Peng; Ye, Shi Qi

2018-06-01

With the promotion of the street system, residential quarters and units of the compound gradually open. In this paper, the relationship between traffic flow and traffic flow is established for external roads, and the road resistance model is established by internal roads. We propose a balanced distribution model from the two aspects of road opening conditions and traffic flow inside and outside the district, and quantitatively analyze the impact of the opening and closing on the surrounding roads. Finally, it puts forward feasible suggestions to improve the traffic situation and optimize the network structure.

Domestic & International Air Cargo Activity: National and Selected Hub Forecasts.

DTIC Science & Technology

1979-11-01

111371 1991 1887811 2?. 768 :297968 Forecast utilizes 1972 dollar GNP from Wharton’s annual model, December 6, 1978, Post-Meeting Control Solution...mile based on 1973 revenue ton-miles reported in the DOT/CAB, Air Carrier Traffic Statistics. South America - RSA - simple average of American (Latin...9518 F (2/11) = 129.347 DW = 1.41 (b) South America (ESA) 4 = 11.8926 + 18.2908* (GDPSA.C) - 8.94307* ( RSA ) 4 (0.14) (6.08) (-0.46) R2 .8717 F (2/11

A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region

NASA Astrophysics Data System (ADS)

He, Zhibin; Wen, Xiaohu; Liu, Hu; Du, Jun

2014-02-01

Data driven models are very useful for river flow forecasting when the underlying physical relationships are not fully understand, but it is not clear whether these data driven models still have a good performance in the small river basin of semiarid mountain regions where have complicated topography. In this study, the potential of three different data driven methods, artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for forecasting river flow in the semiarid mountain region, northwestern China. The models analyzed different combinations of antecedent river flow values and the appropriate input vector has been selected based on the analysis of residuals. The performance of the ANN, ANFIS and SVM models in training and validation sets are compared with the observed data. The model which consists of three antecedent values of flow has been selected as the best fit model for river flow forecasting. To get more accurate evaluation of the results of ANN, ANFIS and SVM models, the four quantitative standard statistical performance evaluation measures, the coefficient of correlation (R), root mean squared error (RMSE), Nash-Sutcliffe efficiency coefficient (NS) and mean absolute relative error (MARE), were employed to evaluate the performances of various models developed. The results indicate that the performance obtained by ANN, ANFIS and SVM in terms of different evaluation criteria during the training and validation period does not vary substantially; the performance of the ANN, ANFIS and SVM models in river flow forecasting was satisfactory. A detailed comparison of the overall performance indicated that the SVM model performed better than ANN and ANFIS in river flow forecasting for the validation data sets. The results also suggest that ANN, ANFIS and SVM method can be successfully applied to establish river flow with complicated topography forecasting models in the semiarid mountain regions.

A microcomputer based traffic evacuation modeling system for emergency planning application

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

Rathi, A.K.

1994-12-01

Vehicular evacuation is one of the major and often preferred protective action options available for emergency management in a real or anticipated disaster. Computer simulation models of evacuation traffic flow are used to estimate the time required for the affected populations to evacuate to safer areas, to evaluate effectiveness of vehicular evacuations as a protective action option. and to develop comprehensive evacuation plans when required. Following a review of the past efforts to simulate traffic flow during emergency evacuations, an overview of the key features in Version 2.0 of the Oak Ridge Evacuation Modeling System (OREMS) are presented in thismore » paper. OREMS is a microcomputer-based model developed to simulate traffic flow during regional emergency evacuations. OREMS integrates a state-of-the-art dynamic traffic flow and simulation model with advanced data editing and output display programs operating under a MS-Windows environment.« less

An extended macro model accounting for acceleration changes with memory and numerical tests

NASA Astrophysics Data System (ADS)

Cheng, Rongjun; Ge, Hongxia; Sun, Fengxin; Wang, Jufeng

2018-09-01

Considering effect of acceleration changes with memory, an improved continuum model of traffic flow is proposed in this paper. By applying the linear stability theory, we derived the new model's linear stability condition. Through nonlinear analysis, the KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the extended traffic flow model, which explores how acceleration changes with memory affected each car's velocity, density and fuel consumption and exhaust emissions. Numerical results demonstrate that acceleration changes with memory have significant negative effect on dynamic characteristic of traffic flow. Furthermore, research results verify that the effect of acceleration changes with memory will deteriorate the stability of traffic flow and increase cars' total fuel consumptions and emissions during the whole evolution of small perturbation.

Analysis of user equilibrium for staggered shifts in a single-entry traffic corridor with no late arrivals

NASA Astrophysics Data System (ADS)

Li, Chuan-Yao; Huang, Hai-Jun; Tang, Tie-Qiao

2017-05-01

In this paper, we investigate the effects of staggered shifts on the user equilibrium (UE) state in a single-entry traffic corridor with no late arrivals from the analytical and numerical perspective. The LWR (Lighthill-Whitham-Richards) model and the Greenshields' velocity-density function are used to describe the dynamic properties of traffic flow. Propositions for the properties of flow patterns in UE, and the quasi-analytic solutions for three possible situations in UE are deduced. Numerical tests are carried out to testify the analytical results, where the three-dimensional evolution diagram of traffic flow illustrates that shock and rarefaction wave exist in UE and the space-time diagram indicates that UE solutions satisfy the propagation properties of traffic flow. In addition, the cost curves show that the UE solutions satisfy the UE trip-timing condition.

Terminal Air Flow Planning

NASA Technical Reports Server (NTRS)

Denery, Dallas G.; Erzberger, Heinz; Edwards, Thomas A. (Technical Monitor)

1998-01-01

The Center TRACON Automation System (CTAS) will be the basis for air traffic planning and control in the terminal area. The system accepts arriving traffic within an extended terminal area and optimizes the flow based on current traffic and airport conditions. The operational use of CTAS will be presented together with results from current operations.

14 CFR 93.57 - General rules: All segments.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Area shall conform to the flow of traffic depicted on the appropriate aeronautical charts. (c) Each person operating a helicopter shall operate it in a manner so as to avoid the flow of airplanes. (d...) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal Area...

14 CFR 93.57 - General rules: All segments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Area shall conform to the flow of traffic depicted on the appropriate aeronautical charts. (c) Each person operating a helicopter shall operate it in a manner so as to avoid the flow of airplanes. (d...) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal Area...

14 CFR 93.57 - General rules: All segments.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Area shall conform to the flow of traffic depicted on the appropriate aeronautical charts. (c) Each person operating a helicopter shall operate it in a manner so as to avoid the flow of airplanes. (d...) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal Area...

14 CFR 93.57 - General rules: All segments.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Area shall conform to the flow of traffic depicted on the appropriate aeronautical charts. (c) Each person operating a helicopter shall operate it in a manner so as to avoid the flow of airplanes. (d...) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal Area...

14 CFR 93.57 - General rules: All segments.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Area shall conform to the flow of traffic depicted on the appropriate aeronautical charts. (c) Each person operating a helicopter shall operate it in a manner so as to avoid the flow of airplanes. (d...) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal Area...

Understanding the topological characteristics and flow complexity of urban traffic congestion

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

32 CFR 634.26 - Traffic law enforcement principles.

Code of Federal Regulations, 2013 CFR

2013-07-01

... safely within traffic laws and regulations and maintain an effective and efficient flow of traffic... 32 National Defense 4 2013-07-01 2013-07-01 false Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic...

32 CFR 634.26 - Traffic law enforcement principles.

Code of Federal Regulations, 2012 CFR

2012-07-01

... safely within traffic laws and regulations and maintain an effective and efficient flow of traffic... 32 National Defense 4 2012-07-01 2011-07-01 true Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic...

32 CFR 634.26 - Traffic law enforcement principles.

Code of Federal Regulations, 2014 CFR

2014-07-01

... safely within traffic laws and regulations and maintain an effective and efficient flow of traffic... 32 National Defense 4 2014-07-01 2013-07-01 true Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic...

Forecasting the clearance time of freeway accidents

DOT National Transportation Integrated Search

2002-01-01

Freeway congestion is a major and costly problem in many U.S. metropolitan areas. From a traveler's perspective, congestion has costs in terms of longer travel times and lost productivity. From the traffic manager's perspective, congestion causes a f...

The 30/20 GHz fixed communications systems service demand assessment. Volume 3: Appendices

NASA Technical Reports Server (NTRS)

Gabriszeski, T.; Reiner, P.; Rogers, J.; Terbo, W.

1979-01-01

The market analysis of voice, video, and data 18/30 GHz communications systems services and satellite transmission services is discussed. Detail calculations, computer displays of traffic, survey questionnaires, and detailed service forecasts are presented.

Large-Scale Traffic Microsimulation From An MPO Perspective

DOT National Transportation Integrated Search

1997-01-01

One potential advancement of the four-step travel model process is the forecasting and simulation of individual activities and travel. A common concern with such an approach is that the data and computational requirements for a large-scale, regional ...

23 CFR 973.104 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

23 CFR 973.104 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

23 CFR 973.104 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

23 CFR 973.104 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

23 CFR 973.104 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

Freeway travel-time estimation and forecasting.

DOT National Transportation Integrated Search

2013-03-01

Real-time traffic information provided by GDOT has proven invaluable for commuters in the : Georgia freeway network. The increasing number of Variable Message Signs, addition of : services such as My-NaviGAtor, NaviGAtor-to-go etc. and the advancemen...

Geostationary platform systems concepts definition study. Volume 2A: Appendixes, book 1

NASA Technical Reports Server (NTRS)

1980-01-01

Appendixes addressing various aspects of a geostationary platform concepts definition study are given. Communication platform traffic requirements, video conferencing forecast, intersatellite link capacity requirements, link budgets, payload data, payload assignments, and platform synthesis are addressed.

Framework for multi-resolution analyses of advanced traffic management strategies.

DOT National Transportation Integrated Search

2016-11-01

Demand forecasting models and simulation models have been developed, calibrated, and used in isolation of each other. However, the advancement of transportation system technologies and strategies, the increase in the availability of data, and the unc...

Delay functions in trip assignment for transport planning process

NASA Astrophysics Data System (ADS)

Leong, Lee Vien

2017-10-01

In transportation planning process, volume-delay and turn-penalty functions are the functions needed in traffic assignment to determine travel time on road network links. Volume-delay function is the delay function describing speed-flow relationship while turn-penalty function is the delay function associated to making a turn at intersection. The volume-delay function used in this study is the revised Bureau of Public Roads (BPR) function with the constant parameters, α and β values of 0.8298 and 3.361 while the turn-penalty functions for signalized intersection were developed based on uniform, random and overflow delay models. Parameters such as green time, cycle time and saturation flow were used in the development of turn-penalty functions. In order to assess the accuracy of the delay functions, road network in areas of Nibong Tebal, Penang and Parit Buntar, Perak was developed and modelled using transportation demand forecasting software. In order to calibrate the models, phase times and traffic volumes at fourteen signalised intersections within the study area were collected during morning and evening peak hours. The prediction of assigned volumes using the revised BPR function and the developed turn-penalty functions show close agreement to actual recorded traffic volume with the lowest percentage of accuracy, 80.08% and the highest, 93.04% for the morning peak model. As for the evening peak model, they were 75.59% and 95.33% respectively for lowest and highest percentage of accuracy. As for the yield left-turn lanes, the lowest percentage of accuracy obtained for the morning and evening peak models were 60.94% and 69.74% respectively while the highest percentage of accuracy obtained for both models were 100%. Therefore, can be concluded that the development and utilisation of delay functions based on local road conditions are important as localised delay functions can produce better estimate of link travel times and hence better planning for future scenarios.

Predicting Average Vehicle Speed in Two Lane Highways Considering Weather Condition and Traffic Characteristics

NASA Astrophysics Data System (ADS)

Mirbaha, Babak; Saffarzadeh, Mahmoud; AmirHossein Beheshty, Seyed; Aniran, MirMoosa; Yazdani, Mirbahador; Shirini, Bahram

2017-10-01

Analysis of vehicle speed with different weather condition and traffic characteristics is very effective in traffic planning. Since the weather condition and traffic characteristics vary every day, the prediction of average speed can be useful in traffic management plans. In this study, traffic and weather data for a two-lane highway located in Northwest of Iran were selected for analysis. After merging traffic and weather data, the linear regression model was calibrated for speed prediction using STATA12.1 Statistical and Data Analysis software. Variables like vehicle flow, percentage of heavy vehicles, vehicle flow in opposing lane, percentage of heavy vehicles in opposing lane, rainfall (mm), snowfall and maximum daily wind speed more than 13m/s were found to be significant variables in the model. Results showed that variables of vehicle flow and heavy vehicle percent acquired the positive coefficient that shows, by increasing these variables the average vehicle speed in every weather condition will also increase. Vehicle flow in opposing lane, percentage of heavy vehicle in opposing lane, rainfall amount (mm), snowfall and maximum daily wind speed more than 13m/s acquired the negative coefficient that shows by increasing these variables, the average vehicle speed will decrease.

High-order computational fluid dynamics tools for aircraft design

PubMed Central

Wang, Z. J.

2014-01-01

Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items. PMID:25024419

3D Markov Process for Traffic Flow Prediction in Real-Time.

PubMed

Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi

2016-01-25

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further.

3D Markov Process for Traffic Flow Prediction in Real-Time

PubMed Central

Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi

2016-01-01

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further. PMID:26821025

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.

Comparative Analysis of River Flow Modelling by Using Supervised Learning Technique

NASA Astrophysics Data System (ADS)

Ismail, Shuhaida; Mohamad Pandiahi, Siraj; Shabri, Ani; Mustapha, Aida

2018-04-01

The goal of this research is to investigate the efficiency of three supervised learning algorithms for forecasting monthly river flow of the Indus River in Pakistan, spread over 550 square miles or 1800 square kilometres. The algorithms include the Least Square Support Vector Machine (LSSVM), Artificial Neural Network (ANN) and Wavelet Regression (WR). The forecasting models predict the monthly river flow obtained from the three models individually for river flow data and the accuracy of the all models were then compared against each other. The monthly river flow of the said river has been forecasted using these three models. The obtained results were compared and statistically analysed. Then, the results of this analytical comparison showed that LSSVM model is more precise in the monthly river flow forecasting. It was found that LSSVM has he higher r with the value of 0.934 compared to other models. This indicate that LSSVM is more accurate and efficient as compared to the ANN and WR model.

Advancing Traffic Flow Theory Using Empirical Microscopic Data

DOT National Transportation Integrated Search

2015-01-01

As reviewed in Section 1.1, much of traffic flow theory depends a fundamental relationship (FR) between flow, density, and space mean speed; either explicitly, e.g., hydrodynamic models such as LWR (Lighthill and Whitham, 1955, and Richards, 1956) or...

An entropy-based analysis of lane changing behavior: An interactive approach.

PubMed

Kosun, Caglar; Ozdemir, Serhan

2017-05-19

As a novelty, this article proposes the nonadditive entropy framework for the description of driver behaviors during lane changing. The authors also state that this entropy framework governs the lane changing behavior in traffic flow in accordance with the long-range vehicular interactions and traffic safety. The nonadditive entropy framework is the new generalized theory of thermostatistical mechanics. Vehicular interactions during lane changing are considered within this framework. The interactive approach for the lane changing behavior of the drivers is presented in the traffic flow scenarios presented in the article. According to the traffic flow scenarios, 4 categories of traffic flow and driver behaviors are obtained. Through the scenarios, comparative analyses of nonadditive and additive entropy domains are also provided. Two quadrants of the categories belong to the nonadditive entropy; the rest are involved in the additive entropy domain. Driving behaviors are extracted and the scenarios depict that nonadditivity matches safe driving well, whereas additivity corresponds to unsafe driving. Furthermore, the cooperative traffic system is considered in nonadditivity where the long-range interactions are present. However, the uncooperative traffic system falls into the additivity domain. The analyses also state that there would be possible traffic flow transitions among the quadrants. This article shows that lane changing behavior could be generalized as nonadditive, with additivity as a special case, based on the given traffic conditions. The nearest and close neighbor models are well within the conventional additive entropy framework. In this article, both the long-range vehicular interactions and safe driving behavior in traffic are handled in the nonadditive entropy domain. It is also inferred that the Tsallis entropy region would correspond to mandatory lane changing behavior, whereas additive and either the extensive or nonextensive entropy region would match discretionary lane changing behavior. This article states that driver behaviors would be in the nonadditive entropy domain to provide a safe traffic stream and hence with vehicle accident prevention in mind.

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.

Mobile phones in a traffic flow: a geographical perspective to evening rush hour traffic analysis using call detail records.

PubMed

Järv, Olle; Ahas, Rein; Saluveer, Erki; Derudder, Ben; Witlox, Frank

2012-01-01

Excessive land use and suburbanisation around densely populated urban areas has gone hand in hand with a growth in overall transportation and discussions about causality of traffic congestions. The objective of this paper is to gain new insight regarding the composition of traffic flows, and to reveal how and to what extent suburbanites' travelling affects rush hour traffic. We put forward an alternative methodological approach using call detail records of mobile phones to assess the composition of traffic flows during the evening rush hour in Tallinn, Estonia. We found that daily commuting and suburbanites influence transportation demand by amplifying the evening rush hour traffic, although daily commuting trips comprises only 31% of all movement at that time. The geography of the Friday evening rush hour is distinctive from other working days, presumably in connection with domestic tourism and leisure time activities. This suggests that the rise of the overall mobility of individuals due to societal changes may play a greater role in evening rush hour traffic conditions than does the impact of suburbanisation.

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

Mobile Phones in a Traffic Flow: A Geographical Perspective to Evening Rush Hour Traffic Analysis Using Call Detail Records

PubMed Central

Järv, Olle; Ahas, Rein; Saluveer, Erki; Derudder, Ben; Witlox, Frank

2012-01-01

Excessive land use and suburbanisation around densely populated urban areas has gone hand in hand with a growth in overall transportation and discussions about causality of traffic congestions. The objective of this paper is to gain new insight regarding the composition of traffic flows, and to reveal how and to what extent suburbanites’ travelling affects rush hour traffic. We put forward an alternative methodological approach using call detail records of mobile phones to assess the composition of traffic flows during the evening rush hour in Tallinn, Estonia. We found that daily commuting and suburbanites influence transportation demand by amplifying the evening rush hour traffic, although daily commuting trips comprises only 31% of all movement at that time. The geography of the Friday evening rush hour is distinctive from other working days, presumably in connection with domestic tourism and leisure time activities. This suggests that the rise of the overall mobility of individuals due to societal changes may play a greater role in evening rush hour traffic conditions than does the impact of suburbanisation. PMID:23155461

A system for forecasting and monitoring cash flow : phase II, forecasting federal and state revenues, maintenance contracts, other expenditures, and cash balances.

DOT National Transportation Integrated Search

1985-01-01

The research on which this report is based was performed as part of a study to develop an improved system for generating a two-year forecast of monthly cash flows for the Virginia Department of Highways and Transportation. It revealed that current te...

What Have we Learned about Intelligent Transportation Systems?

DOT National Transportation Integrated Search

1980-01-01

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

Navier-Stokes-like equations for traffic flow.

PubMed

Velasco, R M; Marques, W

2005-10-01

The macroscopic traffic flow equations derived from the reduced Paveri-Fontana equation are closed starting with the maximization of the informational entropy. The homogeneous steady state taken as a reference is obtained for a specific model of the desired velocity and a kind of Chapman-Enskog method is developed to calculate the traffic pressure at the Navier-Stokes level. Numerical solution of the macroscopic traffic equations is obtained and its characteristics are analyzed.

Artificial intelligence based models for stream-flow forecasting: 2000-2015

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

2015-11-01

The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

Traffic Games: Modeling Freeway Traffic with Game Theory

PubMed Central

Cortés-Berrueco, Luis E.; Gershenson, Carlos; Stephens, Christopher R.

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers’ interactions. PMID:27855176

Traffic Games: Modeling Freeway Traffic with Game Theory.

PubMed

Cortés-Berrueco, Luis E; Gershenson, Carlos; Stephens, Christopher R

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers' interactions.

Increasing accuracy of vehicle speed measurement in congested traffic over dual-loop sensors.

DOT National Transportation Integrated Search

2014-09-01

Classified vehicle counts are a critical measure for forecasting the health of the roadway infrastructure : and for planning future improvements to the transportation network. Balancing the cost of data : collection with the fidelity of the measureme...

Development of a prototype land use model for statewide transportation planning activities.

DOT National Transportation Integrated Search

2011-11-30

Future land use forecasting is an important input to transportation planning modeling. Traditionally, land use is allocated to individual : traffic analysis zones (TAZ) based on variables such as the amount of vacant land, zoning restriction, land us...

General phase transition models for vehicular traffic with point constraints on the flow

NASA Astrophysics Data System (ADS)

Dal Santo, E.; Rosini, M. D.; Dymski, N.; Benyahia, M.

2017-12-01

We generalize the phase transition model studied in [R. Colombo. Hyperbolic phase transition in traffic flow.\\ SIAM J.\\ Appl.\\ Math., 63(2):708-721, 2002], that describes the evolution of vehicular traffic along a one-lane road. Two different phases are taken into account, according to whether the traffic is low or heavy. The model is given by a scalar conservation law in the \\emph{free-flow} phase and by a system of two conservation laws in the \\emph{congested} phase. In particular, we study the resulting Riemann problems in the case a local point constraint on the flux of the solutions is enforced.

36 CFR 4.13 - Obstructing traffic.

Code of Federal Regulations, 2012 CFR

2012-07-01

... interfere with the normal flow of traffic. ... 36 Parks, Forests, and Public Property 1 2012-07-01 2012-07-01 false Obstructing traffic. 4.13... VEHICLES AND TRAFFIC SAFETY § 4.13 Obstructing traffic. The following are prohibited: (a) Stopping or...

36 CFR 4.13 - Obstructing traffic.

Code of Federal Regulations, 2014 CFR

2014-07-01

... interfere with the normal flow of traffic. ... 36 Parks, Forests, and Public Property 1 2014-07-01 2014-07-01 false Obstructing traffic. 4.13... VEHICLES AND TRAFFIC SAFETY § 4.13 Obstructing traffic. The following are prohibited: (a) Stopping or...

36 CFR 4.13 - Obstructing traffic.

Code of Federal Regulations, 2013 CFR

2013-07-01

... interfere with the normal flow of traffic. ... 36 Parks, Forests, and Public Property 1 2013-07-01 2013-07-01 false Obstructing traffic. 4.13... VEHICLES AND TRAFFIC SAFETY § 4.13 Obstructing traffic. The following are prohibited: (a) Stopping or...

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.

A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.

PubMed

Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan

2015-01-01

In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.

A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs

PubMed Central

Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan

2015-01-01

In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network. PMID:26571042

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.

Dynamic Transportation Navigation

NASA Astrophysics Data System (ADS)

Meng, Xiaofeng; Chen, Jidong

Miniaturization of computing devices, and advances in wireless communication and sensor technology are some of the forces that are propagating computing from the stationary desktop to the mobile outdoors. Some important classes of new applications that will be enabled by this revolutionary development include intelligent traffic management, location-based services, tourist services, mobile electronic commerce, and digital battlefield. Some existing application classes that will benefit from the development include transportation and air traffic control, weather forecasting, emergency response, mobile resource management, and mobile workforce. Location management, i.e., the management of transient location information, is an enabling technology for all these applications. In this chapter, we present the applications of moving objects management and their functionalities, in particular, the application of dynamic traffic navigation, which is a challenge due to the highly variable traffic state and the requirement of fast, on-line computations.

Strategic Air Traffic Planning Using Eulerian Route Based Modeling and Optimization

NASA Astrophysics Data System (ADS)

Bombelli, Alessandro

Due to a soaring air travel growth in the last decades, air traffic management has become increasingly challenging. As a consequence, planning tools are being devised to help human decision-makers achieve a better management of air traffic. Planning tools are divided into two categories, strategic and tactical. Strategic planning generally addresses a larger planning domain and is performed days to hours in advance. Tactical planning is more localized and is performed hours to minutes in advance. An aggregate route model for strategic air traffic flow management is presented. It is an Eulerian model, describing the flow between cells of unidirectional point-to-point routes. Aggregate routes are created from flight trajectory data based on similarity measures. Spatial similarity is determined using the Frechet distance. The aggregate routes approximate actual well-traveled traffic patterns. By specifying the model resolution, an appropriate balance between model accuracy and model dimension can be achieved. For a particular planning horizon, during which weather is expected to restrict the flow, a procedure for designing airborne reroutes and augmenting the traffic flow model is developed. The dynamics of the traffic flow on the resulting network take the form of a discrete-time, linear time-invariant system. The traffic flow controls are ground holding, pre-departure rerouting and airborne rerouting. Strategic planning--determining how the controls should be used to modify the future traffic flow when local capacity violations are anticipated--is posed as an integer programming problem of minimizing a weighted sum of flight delays subject to control and capacity constraints. Several tests indicate the effectiveness of the modeling and strategic planning approach. In the final, most challenging, test, strategic planning is demonstrated for the six western-most Centers of the 22-Center national airspace. The planning time horizon is four hours long, and there is weather predicted that causes significant delays to the scheduled flights. Airborne reroute options are computed and added to the route model, and it is shown that the predicted delays can be significantly reduced. The test results also indicate the computational feasibility of the approach for a planning problem of this size.

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.

Traffic Flow. USMES Teacher's Resource Book, Preliminary Edition.

ERIC Educational Resources Information Center

Education Development Center, Inc., Newton, MA.

This USMES unit challenges students to recommend and try to have a new road design or a system for rerouting traffic accepted so that cars and trucks can move safely at a reasonable speed through a busy intersection near the school. The teacher resource book for the Traffic Flow unit contains five sections. The first section describes the USMES…

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.

Dynamic analysis of pedestrian crossing behaviors on traffic flow at unsignalized mid-block crosswalks

NASA Astrophysics Data System (ADS)

Liu, Gang; He, Jing; Luo, Zhiyong; Yang, Wunian; Zhang, Xiping

2015-05-01

It is important to study the effects of pedestrian crossing behaviors on traffic flow for solving the urban traffic jam problem. Based on the Nagel-Schreckenberg (NaSch) traffic cellular automata (TCA) model, a new one-dimensional TCA model is proposed considering the uncertainty conflict behaviors between pedestrians and vehicles at unsignalized mid-block crosswalks and defining the parallel updating rules of motion states of pedestrians and vehicles. The traffic flow is simulated for different vehicle densities and behavior trigger probabilities. The fundamental diagrams show that no matter what the values of vehicle braking probability, pedestrian acceleration crossing probability, pedestrian backing probability and pedestrian generation probability, the system flow shows the "increasing-saturating-decreasing" trend with the increase of vehicle density; when the vehicle braking probability is lower, it is easy to cause an emergency brake of vehicle and result in great fluctuation of saturated flow; the saturated flow decreases slightly with the increase of the pedestrian acceleration crossing probability; when the pedestrian backing probability lies between 0.4 and 0.6, the saturated flow is unstable, which shows the hesitant behavior of pedestrians when making the decision of backing; the maximum flow is sensitive to the pedestrian generation probability and rapidly decreases with increasing the pedestrian generation probability, the maximum flow is approximately equal to zero when the probability is more than 0.5. The simulations prove that the influence of frequent crossing behavior upon vehicle flow is immense; the vehicle flow decreases and gets into serious congestion state rapidly with the increase of the pedestrian generation probability.

An extended continuum model considering optimal velocity change with memory and numerical tests

NASA Astrophysics Data System (ADS)

Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

2018-01-01

In this paper, an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory. The new model's stability condition and KdV-Burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis, respectively. Numerical simulation is carried out to study the extended continuum model, which explores how optimal velocity changes with memory affected velocity, density and energy consumption. Numerical results show that when considering the effects of optimal velocity changes with memory, the traffic jams can be suppressed efficiently. Both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently. Furthermore, numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information, which increases the stability of traffic flow on road, and so it improve the traffic flow stability and minimize cars' energy consumptions.

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.

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 ...

Market capture by 30/20 GHz satellite systems, volume 2

NASA Technical Reports Server (NTRS)

Gamble, R. B.; Saporta, L.

1981-01-01

Results of a telecommunications demand study are presented. Forecasts of demand for 30/20 GHz satellite systems, and the expected build up of traffic on these systems are given as a function of time for each of several operational scenarios.

February 11, 2009, Subcommittee on Aviation Hearing on FAA Reauthorization Act of 2009 questions for the record.

DOT National Transportation Integrated Search

2009-02-01

The next generation air transportation system (NextGen) includes the : policies, procedures, and equipment that will allow satellite-based navigation in the : national airspace system. However, this systems ability to meet forecasted traffic : vol...

MAG traffic generator study : survey data from Arizona State University

DOT National Transportation Integrated Search

1994-12-01

The Maricopa Association of Governments (MAG) is responsible for the travel demand models used to forecast multi-modal travel behavior in the Phoenix metropolitan area. The main campus of Arizona State University (ASU), located in Tempe, is one of th...

Market capture by 30/20 GHz satellite systems, volume 2

NASA Astrophysics Data System (ADS)

Gamble, R. B.; Saporta, L.

1981-04-01

Results of a telecommunications demand study are presented. Forecasts of demand for 30/20 GHz satellite systems, and the expected build up of traffic on these systems are given as a function of time for each of several operational scenarios.

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.

Joint parameter and state estimation algorithms for real-time traffic monitoring.

DOT National Transportation Integrated Search

2013-12-01

A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...

Daily River Flow Forecasting with Hybrid Support Vector Machine – Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Zaini, N.; Malek, M. A.; Yusoff, M.; Mardi, N. H.; Norhisham, S.

2018-04-01

The application of artificial intelligence techniques for river flow forecasting can further improve the management of water resources and flood prevention. This study concerns the development of support vector machine (SVM) based model and its hybridization with particle swarm optimization (PSO) to forecast short term daily river flow at Upper Bertam Catchment located in Cameron Highland, Malaysia. Ten years duration of historical rainfall, antecedent river flow data and various meteorology parameters data from 2003 to 2012 are used in this study. Four SVM based models are proposed which are SVM1, SVM2, SVM-PSO1 and SVM-PSO2 to forecast 1 to 7 day ahead of river flow. SVM1 and SVM-PSO1 are the models with historical rainfall and antecedent river flow as its input, while SVM2 and SVM-PSO2 are the models with historical rainfall, antecedent river flow data and additional meteorological parameters as input. The performances of the proposed model are measured in term of RMSE and R2 . It is found that, SVM2 outperformed SVM1 and SVM-PSO2 outperformed SVM-PSO1 which meant the additional meteorology parameters used as input to the proposed models significantly affect the model performances. Hybrid models SVM-PSO1 and SVM-PSO2 yield higher performances as compared to SVM1 and SVM2. It is found that hybrid models are more effective in forecasting river flow at 1 to 7 day ahead at the study area.

Modeling mechanical restriction differences between car and heavy truck in two-lane cellular automata traffic flow model

NASA Astrophysics Data System (ADS)

Li, Xin; Li, Xingang; Xiao, Yao; Jia, Bin

2016-06-01

Real traffic is heterogeneous with car and truck. Due to mechanical restrictions, the car and the truck have different limited deceleration capabilities, which are important factors in safety driving. This paper extends the single lane safety driving (SD) model with limited deceleration capability to two-lane SD model, in which car-truck heterogeneous traffic is considered. A car has a larger limited deceleration capability while a heavy truck has a smaller limited deceleration capability as a result of loaded goods. Then the safety driving conditions are different as the types of the following and the leading vehicles vary. In order to eliminate the well-known plug in heterogeneous two-lane traffic, it is assumed that heavy truck has active deceleration behavior when the heavy truck perceives the forming plug. The lane-changing decisions are also determined by the safety driving conditions. The fundamental diagram, spatiotemporal diagram, and lane-changing frequency were investigated to show the effect of mechanical restriction on heterogeneous traffic flow. It was shown that there would be still three traffic phases in heterogeneous traffic condition; the active deceleration of the heavy truck could well eliminate the plug; the lane-changing frequency was low in synchronized flow; the flow and velocity would decrease as the proportion of heavy truck grows or the limited deceleration capability of heavy truck drops; and the flow could be improved with lane control measures.

Assessing the skill of seasonal precipitation and streamflow forecasts in sixteen French catchments

NASA Astrophysics Data System (ADS)

Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian

2015-04-01

Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful. Streamflow forecasting is one of the many applications than can benefit from these efforts. Seasonal flow forecasts generated using seasonal ensemble precipitation forecasts as input to a hydrological model can help to take anticipatory measures for water supply reservoir operation or drought risk management. The objective of the study is to assess the skill of seasonal precipitation and streamflow forecasts in France. First, we evaluated the skill of ECMWF SYS4 seasonal precipitation forecasts for streamflow forecasting in sixteen French catchments. Daily flow forecasts were produced using raw seasonal precipitation forecasts as input to the GR6J hydrological model. Ensemble forecasts are issued every month with 15 or 51 members according to the month of the year and evaluated for up to 90 days ahead. In a second step, we applied eight variants of bias correction approaches to the precipitation forecasts prior to generating the flow forecasts. The approaches were based on the linear scaling and the distribution mapping methods. The skill of the ensemble forecasts was assessed in accuracy (MAE), reliability (PIT Diagram) and overall performance (CRPS). The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are more skilful in terms of accuracy and overall performance than a reference prediction based on historic observed precipitation and watershed initial conditions at the time of forecast. Reliability is the only attribute that is not significantly improved. The skill of the forecasts is, in general, improved when applying bias correction. Two bias correction methods showed the best performance for the studied catchments: the simple linear scaling of monthly values and the empirical distribution mapping of daily values. L. Crochemore is funded by the Interreg IVB DROP Project (Benefit of governance in DROught adaPtation).

Integrated Mode Choice, Small Aircraft Demand, and Airport Operations Model User's Guide

NASA Technical Reports Server (NTRS)

Yackovetsky, Robert E. (Technical Monitor); Dollyhigh, Samuel M.

2004-01-01

A mode choice model that generates on-demand air travel forecasts at a set of GA airports based on changes in economic characteristics, vehicle performance characteristics such as speed and cost, and demographic trends has been integrated with a model to generate itinerate aircraft operations by airplane category at a set of 3227 airports. Numerous intermediate outputs can be generated, such as the number of additional trips diverted from automobiles and schedule air by the improved performance and cost of on-demand air vehicles. The total number of transported passenger miles that are diverted is also available. From these results the number of new aircraft to service the increased demand can be calculated. Output from the models discussed is in the format to generate the origin and destination traffic flow between the 3227 airports based on solutions to a gravity model.

Human mobility: Models and applications

NASA Astrophysics Data System (ADS)

Barbosa, Hugo; Barthelemy, Marc; Ghoshal, Gourab; James, Charlotte R.; Lenormand, Maxime; Louail, Thomas; Menezes, Ronaldo; Ramasco, José J.; Simini, Filippo; Tomasini, Marcello

2018-03-01

Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.

Collective Human Mobility Pattern from Taxi Trips in Urban Area

PubMed Central

Peng, Chengbin; Jin, Xiaogang; Wong, Ka-Chun; Shi, Meixia; Liò, Pietro

2012-01-01

We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously. PMID:22529917

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

Spontaneous density fluctuations in granular flow and traffic

NASA Astrophysics Data System (ADS)

Herrmann, Hans J.

It is known that spontaneous density waves appear in granular material flowing through pipes or hoppers. A similar phenomenon is known from traffic jams on highways. Using numerical simulations we show that several types of waves exist and find that the density fluctuations follow a power law spectrum. We also investigate one-dimensional traffic models. If positions and velocities are continuous variables the model shows self-organized criticality driven by the slowest car. Lattice gas and lattice Boltzmann models reproduce the experimentally observed effects. Density waves are spontaneously generated when the viscosity has a non-linear dependence on density or shear rate as it is the case in traffic or granular flow.

A state of the art regarding urban air quality prediction models

NASA Astrophysics Data System (ADS)

Croitoru, Cristiana; Nastase, Ilinca

2018-02-01

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

Assessment of historical and projected segments of US and world civil and military rotorcraft markets, 1960 - 1990

NASA Technical Reports Server (NTRS)

Yates, W. J.

1981-01-01

The geographic climatic, political, economic and demographic environment of 75 countries was analyzed with respect to helicopter procurement history and usage. Key environmental indicators which are variables were projected into strengths and weaknesses of U.S. technology are reviewed. The civil market sensitivity to new technology is forecast with selected premises as to vehicle life, noise standards, fuel costs, GNP expansion and traffic growth. The forecast is based on a scenario of helicopter technology improvements resulting in increased size and performance.

An investigation of driver distraction near the tipping point of traffic flow stability.

PubMed

Cooper, Joel M; Vladisavljevic, Ivana; Medeiros-Ward, Nathan; Martin, Peter T; Strayer, David L

2009-04-01

The purpose of this study was to explore the interrelationship between driver distraction and characteristics of driver behavior associated with reduced highway traffic efficiency. Research on the three-phase traffic theory and on behavioral driving suggests that a number of characteristics associated with efficient traffic flow may be affected by driver distraction. Previous studies have been limited, however, by the fact that researchers typically do not allow participants to change lanes, nor do they account for the impact of varying traffic states on driving performance. Participants drove in three simulated environments with differing traffic congestion while both using and not using a cell phone. Instructed only to obey the speed limit, participants were allowed to vary driving behaviors, such as those involving forward following distance, speed, and lane-changing frequency. Both driver distraction and traffic congestion were found to significantly affect lane change frequency, mean speed, and the likelihood of remaining behind a slower-moving lead vehicle. This research suggests that the behavioral profile of "cell phone drivers," which is often described as compensatory, may have far-reaching and unexpected consequences for traffic efficiency. By considering the dynamic interplay between characteristics of traffic flow and driver behavior, this research may inform both public policy regarding in-vehicle cell phone use and future investigations of driving behavior.

Analysis of traffic growth rates

DOT National Transportation Integrated Search

2001-08-01

The primary objectives of this study were to determine patterns of traffic flow and develop traffic growth rates by traffic composition and highway type for Kentucky's system of highways. Additional subtasks included the following: 1) a literature se...

Disordered cellular automaton traffic flow model: phase separated state, density waves and self organized criticality

NASA Astrophysics Data System (ADS)

Fourrate, K.; Loulidi, M.

2006-01-01

We suggest a disordered traffic flow model that captures many features of traffic flow. It is an extension of the Nagel-Schreckenberg (NaSch) stochastic cellular automata for single line vehicular traffic model. It incorporates random acceleration and deceleration terms that may be greater than one unit. Our model leads under its intrinsic dynamics, for high values of braking probability pr, to a constant flow at intermediate densities without introducing any spatial inhomogeneities. For a system of fast drivers pr→0, the model exhibits a density wave behavior that was observed in car following models with optimal velocity. The gap of the disordered model we present exhibits, for high values of pr and random deceleration, at a critical density, a power law distribution which is a hall mark of a self organized criticality phenomena.

77 FR 35105 - Notice To Rescind the Notice of Intent To Develop the Environmental Impact Statement: Bronx...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-12

...) intended to prepare an EIS on the proposal to improve safety and traffic flow at the Bruckner Expressway (I... improve safety and traffic flow at the Bruckner Expressway (I-278) at its interchange with the Arthur V. Sheridan Expressway (I-895) and to reduce traffic, especially trucks from the local streets and to enhance...

Evolutionary Concepts for Decentralized Air Traffic Flow Management

NASA Technical Reports Server (NTRS)

Adams, Milton; Kolitz, Stephan; Milner, Joseph; Odoni, Amedeo

1997-01-01

Alternative concepts for modifying the policies and procedures under which the air traffic flow management system operates are described, and an approach to the evaluation of those concepts is discussed. Here, air traffic flow management includes all activities related to the management of the flow of aircraft and related system resources from 'block to block.' The alternative concepts represent stages in the evolution from the current system, in which air traffic management decision making is largely centralized within the FAA, to a more decentralized approach wherein the airlines and other airspace users collaborate in air traffic management decision making with the FAA. The emphasis in the discussion is on a viable medium-term partially decentralized scenario representing a phase of this evolution that is consistent with the decision-making approaches embodied in proposed Free Flight concepts for air traffic management. System-level metrics for analyzing and evaluating the various alternatives are defined, and a simulation testbed developed to generate values for those metrics is described. The fundamental issue of modeling airline behavior in decentralized environments is also raised, and an example of such a model, which deals with the preservation of flight bank integrity in hub airports, is presented.

State criminal justice telecommunications (STACOM). Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Fielding, J. E.; Frewing, H. K.; Lee, J. J.; Leflang, W. G.; Reilly, N. B.

1977-01-01

Techniques for identifying user requirements and network designs for criminal justice networks on a state wide basis are discussed. Topics covered include: methods for determining data required; data collection and survey; data organization procedures, and methods for forecasting network traffic volumes. Developed network design techniques center around a computerized topology program which enables the user to generate least cost network topologies that satisfy network traffic requirements, response time requirements and other specified functional requirements. The developed techniques were applied in Texas and Ohio, and results of these studies are presented.

Evaluation of Intersection Traffic Control Measures through Simulation

NASA Astrophysics Data System (ADS)

Asaithambi, Gowri; Sivanandan, R.

2015-12-01

Modeling traffic flow is stochastic in nature due to randomness in variables such as vehicle arrivals and speeds. Due to this and due to complex vehicular interactions and their manoeuvres, it is extremely difficult to model the traffic flow through analytical methods. To study this type of complex traffic system and vehicle interactions, simulation is considered as an effective tool. Application of homogeneous traffic models to heterogeneous traffic may not be able to capture the complex manoeuvres and interactions in such flows. Hence, a microscopic simulation model for heterogeneous traffic is developed using object oriented concepts. This simulation model acts as a tool for evaluating various control measures at signalized intersections. The present study focuses on the evaluation of Right Turn Lane (RTL) and Channelised Left Turn Lane (CLTL). A sensitivity analysis was performed to evaluate RTL and CLTL by varying the approach volumes, turn proportions and turn lane lengths. RTL is found to be advantageous only up to certain approach volumes and right-turn proportions, beyond which it is counter-productive. CLTL is found to be advantageous for lower approach volumes for all turn proportions, signifying the benefits of CLTL. It is counter-productive for higher approach volume and lower turn proportions. This study pinpoints the break-even points for various scenarios. The developed simulation model can be used as an appropriate intersection lane control tool for enhancing the efficiency of flow at intersections. This model can also be employed for scenario analysis and can be valuable to field traffic engineers in implementing vehicle-type based and lane-based traffic control measures.

Studies of vehicle overtaking dynamics and its influence on traffic flow at a bidirectional road

NASA Astrophysics Data System (ADS)

Echab, H.; Marzoug, R.; Lakouari, N.; Ez-Zahraouy, H.

For the purposes of optimizing traffic flow composed of different types of vehicles, it is important to understand the interactions between them. This paper proposes a cellular automata model to investigate a bidirectional two-lane traffic flow under the periodic boundary condition. The vehicle flux and the phase diagrams of the system in the (ρ1,ρ2) space are constructed by applying two different overtaking models (symmetric, asymmetric). The inter-lane correlation and the overtaking frequency are also studied. The simulation results show that the variation of the density of one lane has an apparent influence on the traffic of the adjacent lane. Furthermore, it is found that the phase diagram on both models is classified into several regions. Thus, for the symmetric model, as the overtaking probability increases, the traffic on the system becomes better. Likewise, the results also indicate that the asymmetric model can effectively enhance the traffic capacity and alleviate the congested state.

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.

Final research findings on traffic-load forecasting using weigh-in-motion data

DOT National Transportation Integrated Search

1998-09-01

The overall objective of Project 7-987 was to develop a long-range pavement rehabilitation plan for a segment of US 59, a four-lane divided principal arterial highway in TxDOT's Lufkin District. To identify feasible pavement : structures, test sectio...

47 CFR 32.6532 - Network administration expense.

Code of Federal Regulations, 2013 CFR

2013-10-01

... includes such activities as controlling traffic flow, administering traffic measuring and monitoring devices, assigning equipment and load balancing, collecting and summarizing traffic data, administering...

47 CFR 32.6532 - Network administration expense.

Code of Federal Regulations, 2012 CFR

2012-10-01

... includes such activities as controlling traffic flow, administering traffic measuring and monitoring devices, assigning equipment and load balancing, collecting and summarizing traffic data, administering...

47 CFR 32.6532 - Network administration expense.

Code of Federal Regulations, 2014 CFR

2014-10-01

... includes such activities as controlling traffic flow, administering traffic measuring and monitoring devices, assigning equipment and load balancing, collecting and summarizing traffic data, administering...

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

PubMed Central

Yang, Longhai; Fang, Lin

2018-01-01

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

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

PubMed

Yang, Longhai; Hu, Xiaowei; Fang, Lin

2018-01-01

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

36 CFR 1004.13 - Obstructing traffic.

Code of Federal Regulations, 2012 CFR

2012-07-01

... flow of traffic. ... 36 Parks, Forests, and Public Property 3 2012-07-01 2012-07-01 false Obstructing traffic. 1004.13 Section 1004.13 Parks, Forests, and Public Property PRESIDIO TRUST VEHICLES AND TRAFFIC SAFETY § 1004.13...

36 CFR 1004.13 - Obstructing traffic.

Code of Federal Regulations, 2014 CFR

2014-07-01

... flow of traffic. ... 36 Parks, Forests, and Public Property 3 2014-07-01 2014-07-01 false Obstructing traffic. 1004.13 Section 1004.13 Parks, Forests, and Public Property PRESIDIO TRUST VEHICLES AND TRAFFIC SAFETY § 1004.13...

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 ...

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.

Calibration of CORSIM models under saturated traffic flow conditions.

DOT National Transportation Integrated Search

2013-09-01

This study proposes a methodology to calibrate microscopic traffic flow simulation models. : The proposed methodology has the capability to calibrate simultaneously all the calibration : parameters as well as demand patterns for any network topology....

Interactive Forecasting with the National Weather Service River Forecast System

NASA Technical Reports Server (NTRS)

Smith, George F.; Page, Donna

1993-01-01

The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

The Traffic Management Advisor

NASA Technical Reports Server (NTRS)

Nedell, William; Erzberger, Heinz; Neuman, Frank

1990-01-01

The traffic management advisor (TMA) is comprised of algorithms, a graphical interface, and interactive tools for controlling the flow of air traffic into the terminal area. The primary algorithm incorporated in it is a real-time scheduler which generates efficient landing sequences and landing times for arrivals within about 200 n.m. from touchdown. A unique feature of the TMA is its graphical interface that allows the traffic manager to modify the computer-generated schedules for specific aircraft while allowing the automatic scheduler to continue generating schedules for all other aircraft. The graphical interface also provides convenient methods for monitoring the traffic flow and changing scheduling parameters during real-time operation.

Forecasting production in Liquid Rich Shale plays

NASA Astrophysics Data System (ADS)

Nikfarman, Hanieh

Production from Liquid Rich Shale (LRS) reservoirs is taking center stage in the exploration and production of unconventional reservoirs. Production from the low and ultra-low permeability LRS plays is possible only through multi-fractured horizontal wells (MFHW's). There is no existing workflow that is applicable to forecasting multi-phase production from MFHW's in LRS plays. This project presents a practical and rigorous workflow for forecasting multiphase production from MFHW's in LRS reservoirs. There has been much effort in developing workflows and methodology for forecasting in tight/shale plays in recent years. The existing workflows, however, are applicable only to single phase flow, and are primarily used in shale gas plays. These methodologies do not apply to the multi-phase flow that is inevitable in LRS plays. To account for complexities of multiphase flow in MFHW's the only available technique is dynamic modeling in compositional numerical simulators. These are time consuming and not practical when it comes to forecasting production and estimating reserves for a large number of producers. A workflow was developed, and validated by compositional numerical simulation. The workflow honors physics of flow, and is sufficiently accurate while practical so that an analyst can readily apply it to forecast production and estimate reserves in a large number of producers in a short period of time. To simplify the complex multiphase flow in MFHW, the workflow divides production periods into an initial period where large production and pressure declines are expected, and the subsequent period where production decline may converge into a common trend for a number of producers across an area of interest in the field. Initial period assumes the production is dominated by single-phase flow of oil and uses the tri-linear flow model of Erdal Ozkan to estimate the production history. Commercial software readily available can simulate flow and forecast production in this period. In the subsequent Period, dimensionless rate and dimensionless time functions are introduced that help identify transition from initial period into subsequent period. The production trends in terms of the dimensionless parameters converge for a range of rock permeability and stimulation intensity. This helps forecast production beyond transition to the end of life of well. This workflow is applicable to single fluid system.

GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale

NASA Astrophysics Data System (ADS)

Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter

2017-04-01

Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal outlook while providing useful information to users and partners. We demonstrate the first version of an operational GloFAS seasonal outlook, outlining the model set-up and presenting a first look at the seasonal forecasts that will be displayed in the GloFAS interface, and discuss the initial results of the forecast evaluation.

Traffic Flow Management and Optimization

NASA Technical Reports Server (NTRS)

Rios, Joseph Lucio

2014-01-01

This talk will present an overview of Traffic Flow Management (TFM) research at NASA Ames Research Center. Dr. Rios will focus on his work developing a large-scale, parallel approach to solving traffic flow management problems in the national airspace. In support of this talk, Dr. Rios will provide some background on operational aspects of TFM as well a discussion of some of the tools needed to perform such work including a high-fidelity airspace simulator. Current, on-going research related to TFM data services in the national airspace system and general aviation will also be presented.

Using Flow Charts to Visualize the Decision-Making Process in Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Aung, M. T. Y.; Myat, T.; Zheng, Y.; Mays, M. L.; Ngwira, C.; Damas, M. C.

2016-12-01

Our society today relies heavily on technological systems such as satellites, navigation systems, power grids and aviation. These systems are very sensitive to space weather disturbances. When Earth-directed space weather driven by the Sun arrives at the Earth, it causes changes to the Earth's radiation environment and the magnetosphere. Strong disturbances in the magnetosphere of the Earth are responsible for geomagnetic storms that can last from hours to days depending on strength of storms. Geomagnetic storms can severely impact critical infrastructure on Earth, such as the electric power grid, and Solar Energetic Particles that can endanger life in outer space. How can we lessen these adverse effects? They can be lessened through the early warning signals sent by space weather forecasters before CME or high-speed stream arrives. A space weather forecaster's duty is to send predicted notifications to high-tech industries and NASA missions so that they could take extra measures for protection. NASA space weather forecasters make prediction decisions by following certain steps and processes from the time an event occurs at the sun all the way to the impact locations. However, there has never been a tool that helps these forecasters visualize the decision process until now. A flow chart is created to help forecasters visualize the decision process. This flow chart provides basic knowledge of space weather and can be used to train future space weather forecasters. It also helps to cut down the training period and increase consistency in forecasting. The flow chart is also a great reference for people who are already familiar with space weather.

Coordinated Traffic Incident and Congestion Management (TIM-CM) : Mitigating Regional Impacts of Major Traffic Incidents in the Seattle I-5 Corridor

DOT National Transportation Integrated Search

2018-02-02

Within the Seattle metropolitan area, traffic incident management (TIM) operations provide a multi-jurisdictional and coordinated strategy to detect, respond to, and clear traffic incidents so that traffic flow can be restored quickly and safely. The...

Nonlinear analysis of an improved continuum model considering headway change with memory

NASA Astrophysics Data System (ADS)

Cheng, Rongjun; Wang, Jufeng; Ge, Hongxia; Li, Zhipeng

2018-01-01

Considering the effect of headway changes with memory, an improved continuum model of traffic flow is proposed in this paper. By means of linear stability theory, the new model’s linear stability with the effect of headway changes with memory is obtained. Through nonlinear analysis, the KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the improved traffic flow model, which explores how the headway changes with memory affected each car’s velocity, density and energy consumption. Numerical results show that when considering the effects of headway changes with memory, the traffic jams can be suppressed efficiently. Furthermore, research results demonstrate that the effect of headway changes with memory can avoid the disadvantage of historical information, which will improve the stability of traffic flow and minimize car energy consumption.

Evaluation of Flood Forecast and Warning in Elbe river basin - Impact of Forecaster's Strategy

NASA Astrophysics Data System (ADS)

Danhelka, Jan; Vlasak, Tomas

2010-05-01

Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and interpretation by forecaster. Forecast users are interested in final output without separating uncertainties of separate steps of described process. Therefore an evaluation of final operational forecasts was done for profiles within Elbe river basin produced by AquaLog forecasting system during period 2002 to 2008. Effects of uncertainties of observation, data processing and especially meteorological forecasts were not accounted separately. Forecast of flood levels exceedance (peak over the threshold) during forecasting period was the main criterion as flow increase forecast is of the highest importance. Other evaluation criteria included peak flow and volume difference. In addition Nash-Sutcliffe was computed separately for each time step (1 to 48 h) of forecasting period to identify its change with the lead time. Textual flood warnings are issued for administrative regions to initiate flood protection actions in danger of flood. Flood warning hit rate was evaluated at regions level and national level. Evaluation found significant differences of model forecast skill between forecasting profiles, particularly less skill was evaluated at small headwater basins due to domination of QPF uncertainty in these basins. The average hit rate was 0.34 (miss rate = 0.33, false alarm rate = 0.32). However its explored spatial difference is likely to be influenced also by different fit of parameters sets (due to different basin characteristics) and importantly by different impact of human factor. Results suggest that the practice of interactive model operation, experience and forecasting strategy differs between responsible forecasting offices. Warning is based on model outputs interpretation by hydrologists-forecaster. Warning hit rate reached 0.60 for threshold set to lowest flood stage of which 0.11 was underestimation of flood degree (miss 0.22, false alarm 0.28). Critical success index of model forecast was 0.34, while the same criteria for warning reached 0.55. We assume that the increase accounts not only to change of scale from single forecasting point to region for warning, but partly also to forecaster's added value. There is no official warning strategy preferred in the Czech Republic (f.e. tolerance towards higher false alarm rate). Therefore forecaster decision and personal strategy is of great importance. Results show quite successful warning for 1st flood level exceedance, over-warning for 2nd flood level, but under-warning for 3rd (highest) flood level. That suggests general forecaster's preference of medium level warning (2nd flood level is legally determined to be the start of the flood and flood protection activities). In conclusion human forecaster's experience and analysis skill increases flood warning performance notably. However society preference should be specifically addressed in the warning strategy definition to support forecaster's decision making.

Identifying crash-prone traffic conditions under different weather on freeways.

PubMed

Xu, Chengcheng; Wang, Wei; Liu, Pan

2013-09-01

Understanding the relationships between traffic flow characteristics and crash risk under adverse weather conditions will help highway agencies develop proactive safety management strategies to improve traffic safety in adverse weather conditions. The primary objective is to develop separate crash risk prediction models for different weather conditions. The crash data, weather data, and traffic data used in this study were collected on the I-880N freeway in California in 2008 and 2010. This study considered three different weather conditions: clear weather, rainy weather, and reduced visibility weather. The preliminary analysis showed that there was some heterogeneity in the risk estimates for traffic flow characteristics by weather conditions, and that the crash risk prediction model for all weather conditions cannot capture the impacts of the traffic flow variables on crash risk under adverse weather conditions. The Bayesian random intercept logistic regression models were applied to link the likelihood of crash occurrence with various traffic flow characteristics under different weather conditions. The crash risk prediction models were compared to their corresponding logistic regression model. It was found that the random intercept model improved the goodness-of-fit of the crash risk prediction models. The model estimation results showed that the traffic flow characteristics contributing to crash risk were different across different weather conditions. The speed difference between upstream and downstream stations was found to be significant in each crash risk prediction model. Speed difference between upstream and downstream stations had the largest impact on crash risk in reduced visibility weather, followed by that in rainy weather. The ROC curves were further developed to evaluate the predictive performance of the crash risk prediction models under different weather conditions. The predictive performance of the crash risk model for clear weather was better than those of the crash risk models for adverse weather conditions. The research results could promote a better understanding of the impacts of traffic flow characteristics on crash risk under adverse weather conditions, which will help transportation professionals to develop better crash prevention strategies in adverse weather. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Forecasting seasonal hydrologic response in major river basins

NASA Astrophysics Data System (ADS)

Bhuiyan, A. M.

2014-05-01

Seasonal precipitation variation due to natural climate variation influences stream flow and the apparent frequency and severity of extreme hydrological conditions such as flood and drought. To study hydrologic response and understand the occurrence of extreme hydrological events, the relevant forcing variables must be identified. This study attempts to assess and quantify the historical occurrence and context of extreme hydrologic flow events and quantify the relation between relevant climate variables. Once identified, the flow data and climate variables are evaluated to identify the primary relationship indicators of hydrologic extreme event occurrence. Existing studies focus on developing basin-scale forecasting techniques based on climate anomalies in El Nino/La Nina episodes linked to global climate. Building on earlier work, the goal of this research is to quantify variations in historical river flows at seasonal temporal-scale, and regional to continental spatial-scale. The work identifies and quantifies runoff variability of major river basins and correlates flow with environmental forcing variables such as El Nino, La Nina, sunspot cycle. These variables are expected to be the primary external natural indicators of inter-annual and inter-seasonal patterns of regional precipitation and river flow. Relations between continental-scale hydrologic flows and external climate variables are evaluated through direct correlations in a seasonal context with environmental phenomenon such as sun spot numbers (SSN), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO). Methods including stochastic time series analysis and artificial neural networks are developed to represent the seasonal variability evident in the historical records of river flows. River flows are categorized into low, average and high flow levels to evaluate and simulate flow variations under associated climate variable variations. Results demonstrated not any particular method is suited to represent scenarios leading to extreme flow conditions. For selected flow scenarios, the persistence model performance may be comparable to more complex multivariate approaches, and complex methods did not always improve flow estimation. Overall model performance indicates inclusion of river flows and forcing variables on average improve model extreme event forecasting skills. As a means to further refine the flow estimation, an ensemble forecast method is implemented to provide a likelihood-based indication of expected river flow magnitude and variability. Results indicate seasonal flow variations are well-captured in the ensemble range, therefore the ensemble approach can often prove efficient in estimating extreme river flow conditions. The discriminant prediction approach, a probabilistic measure to forecast streamflow, is also adopted to derive model performance. Results show the efficiency of the method in terms of representing uncertainties in the forecasts.

Cyber Situational Awareness through Operational Streaming Analysis

DTIC Science & Technology

2011-04-07

Our system makes use of two specific data sources from network traffic: raw packet data and NetFlow connection summary records (de- scribed below...implemented an operational prototype system using the following two data feeds. a) NetFlow Data: Our system processes the NetFlow records of all...Internet gateway traffic for a large enterprise network. It uses the standard Cisco NetFlow version 5 proto- col, which defines a flow as a

Improvement of driving safety in road traffic system

NASA Astrophysics Data System (ADS)

Li, Ke-Ping; Gao, Zi-You

2005-05-01

A road traffic system is a complex system in which humans participate directly. In this system, human factors play a very important role. In this paper, a kind of control signal is designated at a given site (i.e., signal point) of the road. Under the effect of the control signal, the drivers will decrease their velocities when their vehicles pass the signal point. Our aim is to transit the traffic flow states from disorder to order and then improve the traffic safety. We have tested this technique for the two-lane traffic model that is based on the deterministic Nagel-Schreckenberg (NaSch) traffic model. The simulation results indicate that the traffic flow states can be transited from disorder to order. Different order states can be observed in the system and these states are safer.

Impact of Distracted Driving on Safety and Traffic Flow

PubMed Central

Stavrinos, Despina; Jones, Jennifer L.; Garner, Annie A.; Griffin, Russell; Franklin, Crystal A.; Ball, David; Welburn, Sharon C.; Ball, Karlene K.; Sisiopiku, Virginia P.; Fine, Philip R.

2015-01-01

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16 to 25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted. PMID:23465745

Impact of distracted driving on safety and traffic flow.

PubMed

Stavrinos, Despina; Jones, Jennifer L; Garner, Annie A; Griffin, Russell; Franklin, Crystal A; Ball, David; Welburn, Sharon C; Ball, Karlene K; Sisiopiku, Virginia P; Fine, Philip R

2013-12-01

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16-25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) Poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted. Copyright © 2013 Elsevier Ltd. All rights reserved.

Impact of local traffic exclusion on near-road air quality: findings from the New York City "Summer Streets" campaign.

PubMed

Whitlow, Thomas H; Hall, Andrew; Zhang, K Max; Anguita, Juan

2011-01-01

We monitored curbside airborne particulate matter (PM) concentrations and its proinflammatory capacity during 3 weekends when vehicle traffic was excluded from Park. Ave., New York City. Fine PM concentration peaked in the morning regardless of traffic while ultrafine PM was 58% lower during mornings without traffic. Ultrafine PM concentration varied linearly with traffic flow, while fine PM spiked sharply in response to random traffic events that were weakly correlated with the traffic signal cycle. Ultrafine PM concentrations decayed exponentially with distance from a cross street with unrestricted traffic flow, reaching background levels within 100 m of the source. IL-6 induction was typically highest on Friday afternoons but showed no clear relationship to the presence of traffic. The coarse fraction (>2.5 μm) had the greatest intrinsic inflammatory capacity, suggesting that coarse PM still warrants attention even as the research focus is shifting to nano-particles. Copyright © 2011 Elsevier Ltd. All rights reserved.

Developing a stochastic traffic volume prediction model for public-private partnership projects

NASA Astrophysics Data System (ADS)

Phong, Nguyen Thanh; Likhitruangsilp, Veerasak; Onishi, Masamitsu

2017-11-01

Transportation projects require an enormous amount of capital investment resulting from their tremendous size, complexity, and risk. Due to the limitation of public finances, the private sector is invited to participate in transportation project development. The private sector can entirely or partially invest in transportation projects in the form of Public-Private Partnership (PPP) scheme, which has been an attractive option for several developing countries, including Vietnam. There are many factors affecting the success of PPP projects. The accurate prediction of traffic volume is considered one of the key success factors of PPP transportation projects. However, only few research works investigated how to predict traffic volume over a long period of time. Moreover, conventional traffic volume forecasting methods are usually based on deterministic models which predict a single value of traffic volume but do not consider risk and uncertainty. This knowledge gap makes it difficult for concessionaires to estimate PPP transportation project revenues accurately. The objective of this paper is to develop a probabilistic traffic volume prediction model. First, traffic volumes were estimated following the Geometric Brownian Motion (GBM) process. Monte Carlo technique is then applied to simulate different scenarios. The results show that this stochastic approach can systematically analyze variations in the traffic volume and yield more reliable estimates for PPP projects.

Reducing the impact of speed dispersion on subway corridor flow.

PubMed

Qiao, Jing; Sun, Lishan; Liu, Xiaoming; Rong, Jian

2017-11-01

The rapid increase in the volume of subway passengers in Beijing has necessitated higher requirements for the safety and efficiency of subway corridors. Speed dispersion is an important factor that affects safety and efficiency. This paper aims to analyze the management control methods for reducing pedestrian speed dispersion in subways. The characteristics of the speed dispersion of pedestrian flow were analyzed according to field videos. The control measurements which were conducted by placing traffic signs, yellow marking, and guardrail were proposed to alleviate speed dispersion. The results showed that the methods of placing traffic signs, yellow marking, and a guardrail improved safety and efficiency for all four volumes of pedestrian traffic flow, and the best-performing control measurement was guardrails. Furthermore, guardrails' optimal position and design measurements were explored. The research findings provide a rationale for subway managers in optimizing pedestrian traffic flow in subway corridors. Copyright © 2017. Published by Elsevier Ltd.

A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

NASA Astrophysics Data System (ADS)

Grasso, Raffaele; Cococcioni, Marco; Mourre, Baptiste; Chiggiato, Jacopo; Rixen, Michel

2012-03-01

The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and non-environmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS's inputs (generally due to disagreement between forecasts) are propagated through the DSS's output by using the unscented transform. In this way, the system is not only able to provide a traffic light map ( run/ not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations.

Streamflow Forecasting Using Nuero-Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Nanduri, U. V.; Swain, P. C.

2005-12-01

The prediction of flow into a reservoir is fundamental in water resources planning and management. The need for timely and accurate streamflow forecasting is widely recognized and emphasized by many in water resources fraternity. Real-time forecasts of natural inflows to reservoirs are of particular interest for operation and scheduling. The physical system of the river basin that takes the rainfall as an input and produces the runoff is highly nonlinear, complicated and very difficult to fully comprehend. The system is influenced by large number of factors and variables. The large spatial extent of the systems forces the uncertainty into the hydrologic information. A variety of methods have been proposed for forecasting reservoir inflows including conceptual (physical) and empirical (statistical) models (WMO 1994), but none of them can be considered as unique superior model (Shamseldin 1997). Owing to difficulties of formulating reasonable non-linear watershed models, recent attempts have resorted to Neural Network (NN) approach for complex hydrologic modeling. In recent years the use of soft computing in the field of hydrological forecasting is gaining ground. The relatively new soft computing technique of Adaptive Neuro-Fuzzy Inference System (ANFIS), developed by Jang (1993) is able to take care of the non-linearity, uncertainty, and vagueness embedded in the system. It is a judicious combination of the Neural Networks and fuzzy systems. It can learn and generalize highly nonlinear and uncertain phenomena due to the embedded neural network (NN). NN is efficient in learning and generalization, and the fuzzy system mimics the cognitive capability of human brain. Hence, ANFIS can learn the complicated processes involved in the basin and correlate the precipitation to the corresponding discharge. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A Neuro-Fuzzy model is developed to forecast ten-daily flows into the Hirakud reservoir on River Mahanadi in the state of Orissa in India. Correlation analysis is carried out to find out the most influential variables on the ten daily flow at Hirakud. Based on this analysis, four variables, namely, flow during the previous time period, ql1, rainfall during the previous two time periods, rl1 and rl2, and flow during the same period in previous year, qpy, are identified as the most influential variables to forecast the ten daily flow. Performance measures such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and coefficient of efficiency R2 are computed for training and testing phases of the model to evaluate its performance. The results indicate that the ten-daily forecasting model is efficient in predicting the high and medium flows with reasonable accuracy. The forecast of low flows is associated with less efficiency. REFERENCES Jang, J.S.R. (1993). "ANFIS: Adaptive - network- based fuzzy inference system." IEEE Trans. on Systems, Man and Cybernetics, 23 (3), 665-685. Shamseldin, A.Y. (1997). "Application of a neural network technique to rainfall-runoff modeling." Journal of Hydrology, 199, 272-294. World Meteorological Organization (1975). Intercomparison of conceptual models used in operational hydrological forecasting. World Meteorological Organization, Technical Report No.429, Geneva, Switzerland.

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.

The Physics of Traffic

NASA Astrophysics Data System (ADS)

Davis, L. Craig

2006-03-01

Congestion in freeway traffic is an example of self-organization in the language of complexity theory. Nonequilibrium, first-order phase transitions from free flow cause complex spatiotemporal patterns. Two distinct phases of congestion are observed in empirical traffic data--wide moving jams and synchronous flow. Wide moving jams are characterized by stopped or slowly moving vehicles within the jammed region, which widens and moves upstream at 15-20 km/h. Above a critical density of vehicles, a sudden decrease in the velocity of a lead vehicle can initiate a transition from metastable states to this phase. Human behaviors, especially delayed reactions, are implicated in the formation of jams. The synchronous flow phase results from a bottleneck such as an on-ramp. Thus, in contrast to a jam, the downstream front is pinned at a fixed location. The name of the phase comes from the equilibration (or synchronization) of speed and flow rate across all lanes caused by frequent vehicle lane changes. Synchronous flow occurs when the mainline flow and the rate of merging from an on-ramp are sufficiently large. Large-scale simulations using car-following models reproduce the physical phenomena occurring in traffic and suggest methods to improve flow and mediate congestion.

36 CFR § 1004.13 - Obstructing traffic.

Code of Federal Regulations, 2013 CFR

2013-07-01

... with the normal flow of traffic. ... 36 Parks, Forests, and Public Property 3 2013-07-01 2012-07-01 true Obstructing traffic. § 1004.13 Section § 1004.13 Parks, Forests, and Public Property PRESIDIO TRUST VEHICLES AND TRAFFIC SAFETY...

Indiana freeway traffic characteristics and dynamic prediction of freeway traffic flows

DOT National Transportation Integrated Search

1999-12-01

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

Application of color to reduce complexity in air traffic control.

DOT National Transportation Integrated Search

2002-11-01

The United States Air Traffic Control (ATC) system is designed to provide for the safe and efficient flow of air : traffic from origin to destination. The Federal Aviation Administration predicts that traffic levels will continue : increasing over th...

Traffic safety measures using multiple streams real time data : final report

DOT National Transportation Integrated Search

2017-01-04

Traffic crashes and accidents result from many complex factors, but at a basic level, they are conflicts : among vehicles and/or other road users. Roadway conditions, traffic signals, weather, traffic flow, : drivers' behavior and health of vehicles ...

Traffic flow in the operating room: an explorative and descriptive study on air quality during orthopedic trauma implant surgery.

PubMed

Andersson, Annette Erichsen; Bergh, Ingrid; Karlsson, Jón; Eriksson, Bengt I; Nilsson, Kerstin

2012-10-01

Understanding the protective potential of operating room (OR) ventilation under different conditions is crucial to optimizing the surgical environment. This study investigated the air quality, expressed as colony-forming units (CFU)/m(3), during orthopedic trauma surgery in a displacement-ventilated OR; explored how traffic flow and the number of persons present in the OR affects the air contamination rate in the vicinity of surgical wounds; and identified reasons for door openings in the OR. Data collection, consisting of active air sampling and observations, was performed during 30 orthopedic procedures. In 52 of the 91 air samples collected (57%), the CFU/m(3) values exceeded the recommended level of <10 CFU/m(3). In addition, the data showed a strongly positive correlation between the total CFU/m(3) per operation and total traffic flow per operation (r = 0.74; P = .001; n = 24), after controlling for duration of surgery. A weaker, yet still positive correlation between CFU/m(3) and the number of persons present in the OR (r = 0.22; P = .04; n = 82) was also found. Traffic flow, number of persons present, and duration of surgery explained 68% of the variance in total CFU/m(3) (P = .001). Traffic flow has a strong negative impact on the OR environment. The results of this study support interventions aimed at preventing surgical site infections by reducing traffic flow in the OR. Copyright © 2012 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.

32 CFR 634.48 - General.

Code of Federal Regulations, 2012 CFR

2012-07-01

... DLA in crime prevention, traffic safety, and the orderly flow of vehicle traffic movement. (b) The... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Impounding Privately Owned Vehicles § 634.48 General. This...

32 CFR 634.48 - General.

Code of Federal Regulations, 2011 CFR

2011-07-01

... DLA in crime prevention, traffic safety, and the orderly flow of vehicle traffic movement. (b) The... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Impounding Privately Owned Vehicles § 634.48 General. This...

32 CFR 634.48 - General.

Code of Federal Regulations, 2013 CFR

2013-07-01

... DLA in crime prevention, traffic safety, and the orderly flow of vehicle traffic movement. (b) The... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Impounding Privately Owned Vehicles § 634.48 General. This...

32 CFR 634.48 - General.

Code of Federal Regulations, 2014 CFR

2014-07-01

... DLA in crime prevention, traffic safety, and the orderly flow of vehicle traffic movement. (b) The... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Impounding Privately Owned Vehicles § 634.48 General. This...

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.

Computing Programs for Determining Traffic Flows from Roundabouts

NASA Astrophysics Data System (ADS)

Boroiu, A. A.; Tabacu, I.; Ene, A.; Neagu, E.; Boroiu, A.

2017-10-01

For modelling road traffic at the level of a road network it is necessary to specify the flows of all traffic currents at each intersection. These data can be obtained by direct measurements at the traffic light intersections, but in the case of a roundabout this is not possible directly and the literature as well as the traffic modelling software doesn’t offer ways to solve this issue. Two sets of formulas are proposed by which all traffic flows from the roundabouts with 3 or 4 arms are calculated based on the streams that can be measured. The objective of this paper is to develop computational programs to operate with these formulas. For each of the two sets of analytical relations, a computational program was developed in the Java operating language. The obtained results fully confirm the applicability of the calculation programs. The final stage for capitalizing these programs will be to make them web pages in HTML format, so that they can be accessed and used on the Internet. The achievements presented in this paper are an important step to provide a necessary tool for traffic modelling because these computational programs can be easily integrated into specialized software.

On sequential data assimilation for scalar macroscopic traffic flow models

NASA Astrophysics Data System (ADS)

Blandin, Sébastien; Couque, Adrien; Bayen, Alexandre; Work, Daniel

2012-09-01

We consider the problem of sequential data assimilation for transportation networks using optimal filtering with a scalar macroscopic traffic flow model. Properties of the distribution of the uncertainty on the true state related to the specific nonlinearity and non-differentiability inherent to macroscopic traffic flow models are investigated, derived analytically and analyzed. We show that nonlinear dynamics, by creating discontinuities in the traffic state, affect the performances of classical filters and in particular that the distribution of the uncertainty on the traffic state at shock waves is a mixture distribution. The non-differentiability of traffic dynamics around stationary shock waves is also proved and the resulting optimality loss of the estimates is quantified numerically. The properties of the estimates are explicitly studied for the Godunov scheme (and thus the Cell-Transmission Model), leading to specific conclusions about their use in the context of filtering, which is a significant contribution of this article. Analytical proofs and numerical tests are introduced to support the results presented. A Java implementation of the classical filters used in this work is available on-line at http://traffic.berkeley.edu for facilitating further efforts on this topic and fostering reproducible research.

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.

Investigation of the Link Between Macroscopic Traffic Flow Characteristics and Individual Vehicle Fuel Consumption : Tech Transfer Summary

DOT National Transportation Integrated Search

2017-10-01

The objective of this project was to investigate the impacts of several factors, including vehicle characteristics, ambient temperature, season, speed, driving behavior, and traffic flow, on individual vehicle energy consumption.

Investigation of the Link Between Macroscopic Traffic Flow Characteristics and Individual Vehicle Fuel Consumption

DOT National Transportation Integrated Search

2017-10-01

This project investigated the factors impacting individual vehicle energy consumption, including vehicle characteristics, ambient temperature, season, speed, driving behavior, and traffic flow. A fleet of 18 vehicles with a variety of ownership, size...

Modeling hurricane evacuation traffic : a mobile real-time traffic counter for monitoring hurricane evacuation traffic conditions.

DOT National Transportation Integrated Search

2006-04-01

The objective of this part of the research study was to select and acquire a mobile traffic counter capable of providing traffic flow and average speed data in intervals of time no greater than 15 minutes and transmit the data back to a central locat...

Discharge data assimilation in a distributed hydrologic model for flood forecasting purposes

NASA Astrophysics Data System (ADS)

Ercolani, G.; Castelli, F.

2017-12-01

Flood early warning systems benefit from accurate river flow forecasts, and data assimilation may improve their reliability. However, the actual enhancement that can be obtained in the operational practice should be investigated in detail and quantified. In this work we assess the benefits that the simultaneous assimilation of discharge observations at multiple locations can bring to flow forecasting through a distributed hydrologic model. The distributed model, MOBIDIC, is part of the operational flood forecasting chain of Tuscany Region in Central Italy. The assimilation system adopts a mixed variational-Monte Carlo approach to update efficiently initial river flow, soil moisture, and a parameter related to runoff production. The evaluation of the system is based on numerous hindcast experiments of real events. The events are characterized by significant rainfall that resulted in both high and relatively low flow in the river network. The area of study is the main basin of Tuscany Region, i.e. Arno river basin, which extends over about 8300 km2 and whose mean annual precipitation is around 800 mm. Arno's mainstream, with its nearly 240 km length, passes through major Tuscan cities, as Florence and Pisa, that are vulnerable to floods (e.g. flood of November 1966). The assimilation tests follow the usage of the model in the forecasting chain, employing the operational resolution in both space and time (500 m and 15 minutes respectively) and releasing new flow forecasts every 6 hours. The assimilation strategy is evaluated in respect to open loop simulations, i.e. runs that do not exploit discharge observations through data assimilation. We compare hydrographs in their entirety, as well as classical performance indexes, as error on peak flow and Nash-Sutcliffe efficiency. The dependence of performances on lead time and location is assessed. Results indicate that the operational forecasting chain can benefit from the developed assimilation system, although with a significant variability due to the specific characteristics of any single event, and with downstream locations more sensitive to observations than upstream sites.

Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Jaafar, Othman; Deo, Ravinesh C.; Kisi, Ozgur; Adamowski, Jan; Quilty, John; El-Shafie, Ahmed

2016-11-01

Monthly stream-flow forecasting can yield important information for hydrological applications including sustainable design of rural and urban water management systems, optimization of water resource allocations, water use, pricing and water quality assessment, and agriculture and irrigation operations. The motivation for exploring and developing expert predictive models is an ongoing endeavor for hydrological applications. In this study, the potential of a relatively new data-driven method, namely the extreme learning machine (ELM) method, was explored for forecasting monthly stream-flow discharge rates in the Tigris River, Iraq. The ELM algorithm is a single-layer feedforward neural network (SLFNs) which randomly selects the input weights, hidden layer biases and analytically determines the output weights of the SLFNs. Based on the partial autocorrelation functions of historical stream-flow data, a set of five input combinations with lagged stream-flow values are employed to establish the best forecasting model. A comparative investigation is conducted to evaluate the performance of the ELM compared to other data-driven models: support vector regression (SVR) and generalized regression neural network (GRNN). The forecasting metrics defined as the correlation coefficient (r), Nash-Sutcliffe efficiency (ENS), Willmott's Index (WI), root-mean-square error (RMSE) and mean absolute error (MAE) computed between the observed and forecasted stream-flow data are employed to assess the ELM model's effectiveness. The results revealed that the ELM model outperformed the SVR and the GRNN models across a number of statistical measures. In quantitative terms, superiority of ELM over SVR and GRNN models was exhibited by ENS = 0.578, 0.378 and 0.144, r = 0.799, 0.761 and 0.468 and WI = 0.853, 0.802 and 0.689, respectively and the ELM model attained lower RMSE value by approximately 21.3% (relative to SVR) and by approximately 44.7% (relative to GRNN). Based on the findings of this study, several recommendations were suggested for further exploration of the ELM model in hydrological forecasting problems.

Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China

NASA Astrophysics Data System (ADS)

Liu, Li; Gao, Chao; Xuan, Weidong; Xu, Yue-Ping

2017-11-01

Ensemble flood forecasts by hydrological models using numerical weather prediction products as forcing data are becoming more commonly used in operational flood forecasting applications. In this study, a hydrological ensemble flood forecasting system comprised of an automatically calibrated Variable Infiltration Capacity model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated. The hydrological model is optimized by the parallel programmed ε-NSGA II multi-objective algorithm. According to the solutions by ε-NSGA II, two differently parameterized models are determined to simulate daily flows and peak flows at each of the three hydrological stations. Then a simple yet effective modular approach is proposed to combine these daily and peak flows at the same station into one composite series. Five ensemble methods and various evaluation metrics are adopted. The results show that ε-NSGA II can provide an objective determination on parameter estimation, and the parallel program permits a more efficient simulation. It is also demonstrated that the forecasts from ECMWF have more favorable skill scores than other Ensemble Prediction Systems. The multimodel ensembles have advantages over all the single model ensembles and the multimodel methods weighted on members and skill scores outperform other methods. Furthermore, the overall performance at three stations can be satisfactory up to ten days, however the hydrological errors can degrade the skill score by approximately 2 days, and the influence persists until a lead time of 10 days with a weakening trend. With respect to peak flows selected by the Peaks Over Threshold approach, the ensemble means from single models or multimodels are generally underestimated, indicating that the ensemble mean can bring overall improvement in forecasting of flows. For peak values taking flood forecasts from each individual member into account is more appropriate.

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.

Assessment of a new seasonal to inter-annual operational Great Lakes water supply, water levels, and connecting channel flow forecasting system

NASA Astrophysics Data System (ADS)

Gronewold, A.; Fry, L. M.; Hunter, T.; Pei, L.; Smith, J.; Lucier, H.; Mueller, R.

2017-12-01

The U.S. Army Corps of Engineers (USACE) has recently operationalized a suite of ensemble forecasts of Net Basin Supply (NBS), water levels, and connecting channel flows that was developed through a collaboration among USACE, NOAA's Great Lakes Environmental Research Laboratory, Ontario Power Generation (OPG), New York Power Authority (NYPA), and the Niagara River Control Center (NRCC). These forecasts are meant to provide reliable projections of potential extremes in daily discharge in the Niagara and St. Lawrence Rivers over a long time horizon (5 years). The suite of forecasts includes eight configurations that vary by (a) NBS model configuration, (b) meteorological forcings, and (c) incorporation of seasonal climate projections through the use of weighting. Forecasts are updated on a weekly basis, and represent the first operational forecasts of Great Lakes water levels and flows that span daily to inter-annual horizons and employ realistic regulation logic and lake-to-lake routing. We will present results from a hindcast assessment conducted during the transition from research to operation, as well as early indications of success rates determined through operational verification of forecasts. Assessment will include an exploration of the relative skill of various forecast configurations at different time horizons and the potential for application to hydropower decision making and Great Lakes water management.

Social dilemma structure hidden behind traffic flow with route selection

NASA Astrophysics Data System (ADS)

Tanimoto, Jun; Nakamura, Kousuke

2016-10-01

Several traffic flows contain social dilemma structures. Herein, we explored a route-selection problem using a cellular automaton simulation dovetailed with evolutionary game theory. In our model, two classes of driver-agents coexist: D agents (defective strategy), which refer to traffic information for route selection to move fast, and C agents (cooperative strategy), which are insensitive to information and less inclined to move fast. Although no evidence suggests that the social dilemma structure in low density causes vehicles to move freely and that in high density causes traffic jams, we found a structure that corresponds to an n-person (multiplayer) Chicken (n-Chicken) game if the provided traffic information is inappropriate. If appropriate traffic information is given to the agents, the n-Chicken game can be solved. The information delivered to vehicles is crucial for easing the social dilemma due to urban traffic congestion when developing technologies to support the intelligent transportation system (ITS).

Effect of current vehicle’s interruption on traffic stability in cooperative car-following theory

NASA Astrophysics Data System (ADS)

Zhang, Geng; Liu, Hui

2017-12-01

To reveal the impact of the current vehicle’s interruption information on traffic flow, a new car-following model with consideration of the current vehicle’s interruption is proposed and the influence of the current vehicle’s interruption on traffic stability is investigated through theoretical analysis and numerical simulation. By linear analysis, the linear stability condition of the new model is obtained and the negative influence of the current vehicle’s interruption on traffic stability is shown in the headway-sensitivity space. Through nonlinear analysis, the modified Korteweg-de Vries (mKdV) equation of the new model near the critical point is derived and it can be used to describe the propagating behavior of the traffic density wave. Finally, numerical simulation confirms the analytical results, which shows that the current vehicle’s interruption information can destabilize traffic flow and should be considered in real traffic.

The 30/20 GHZ net market assessment

NASA Technical Reports Server (NTRS)

Rogers, J. C.; Reiner, P.

1980-01-01

By creating a number of market scenarios variations dealing with network types, network sizes, and service price levels were analyzed for their impact on market demand. Each market scenario represents a market demand forecast with results for voice, data, and video service traffic expressed in peak load megabits per second.

Seasonal streamflow prediction using ensemble streamflow prediction technique for the Rangitata and Waitaki River basins on the South Island of New Zealand

NASA Astrophysics Data System (ADS)

Singh, Shailesh Kumar

2014-05-01

Streamflow forecasts are essential for making critical decision for optimal allocation of water supplies for various demands that include irrigation for agriculture, habitat for fisheries, hydropower production and flood warning. The major objective of this study is to explore the Ensemble Streamflow Prediction (ESP) based forecast in New Zealand catchments and to highlights the present capability of seasonal flow forecasting of National Institute of Water and Atmospheric Research (NIWA). In this study a probabilistic forecast framework for ESP is presented. The basic assumption in ESP is that future weather pattern were experienced historically. Hence, past forcing data can be used with current initial condition to generate an ensemble of prediction. Small differences in initial conditions can result in large difference in the forecast. The initial state of catchment can be obtained by continuously running the model till current time and use this initial state with past forcing data to generate ensemble of flow for future. The approach taken here is to run TopNet hydrological models with a range of past forcing data (precipitation, temperature etc.) with current initial conditions. The collection of runs is called the ensemble. ESP give probabilistic forecasts for flow. From ensemble members the probability distributions can be derived. The probability distributions capture part of the intrinsic uncertainty in weather or climate. An ensemble stream flow prediction which provide probabilistic hydrological forecast with lead time up to 3 months is presented for Rangitata, Ahuriri, and Hooker and Jollie rivers in South Island of New Zealand. ESP based seasonal forecast have better skill than climatology. This system can provide better over all information for holistic water resource management.

Traffic flow behavior at a single-lane urban roundabout

NASA Astrophysics Data System (ADS)

Lakouari, N.; Oubram, O.; Ez-Zahraouy, H.; Cisneros-Villalobos, L.; Velásquez-Aguilar, J. G.

In this paper, we propose a stochastic cellular automata model to study the traffic behavior at a single-lane roundabout. Vehicles can enter the interior lane or exit from it via N intersecting lane, the boundary conditions are stochastic. The traffic is controlled by a self-organized scheme. It has turned out that depending on the rules of insertion to the roundabout, five distinct traffic phases can appear, namely, free flow, congestion, maximum current, jammed and gridlock. The transition between the free flow and the gridlock is forbidden. The density profiles are used to study the traffic pattern at the interior lane of the roundabout. In order to quantify the interactions between vehicles in the interior lane of the roundabout, the velocity correlation coefficient (VCC) is also studied. Besides, the spatiotemporal diagrams corresponding to the entry/exit lanes are derived numerically. Furthermore, we have investigated the effect of displaying signal (PIn), as the PIn decreases, the maximum current increases at the expense of the free flow and the jamming phase. Finally, we have investigated the effect of the braking probability P on the interior lane of the roundabout. We have found that the increase of P raises the spontaneous jam formation on the ring. Thus, enlarges the maximum current and the jamming phase while the free flow phase decreases.

A better understanding of long-range temporal dependence of traffic flow time series

NASA Astrophysics Data System (ADS)

Feng, Shuo; Wang, Xingmin; Sun, Haowei; Zhang, Yi; Li, Li

2018-02-01

Long-range temporal dependence is an important research perspective for modelling of traffic flow time series. Various methods have been proposed to depict the long-range temporal dependence, including autocorrelation function analysis, spectral analysis and fractal analysis. However, few researches have studied the daily temporal dependence (i.e. the similarity between different daily traffic flow time series), which can help us better understand the long-range temporal dependence, such as the origin of crossover phenomenon. Moreover, considering both types of dependence contributes to establishing more accurate model and depicting the properties of traffic flow time series. In this paper, we study the properties of daily temporal dependence by simple average method and Principal Component Analysis (PCA) based method. Meanwhile, we also study the long-range temporal dependence by Detrended Fluctuation Analysis (DFA) and Multifractal Detrended Fluctuation Analysis (MFDFA). The results show that both the daily and long-range temporal dependence exert considerable influence on the traffic flow series. The DFA results reveal that the daily temporal dependence creates crossover phenomenon when estimating the Hurst exponent which depicts the long-range temporal dependence. Furthermore, through the comparison of the DFA test, PCA-based method turns out to be a better method to extract the daily temporal dependence especially when the difference between days is significant.

A review and update of the Virginia Department of Transportation cash flow forecasting model.

DOT National Transportation Integrated Search

1996-01-01

This report details the research done to review and update components of the VDOT cash flow forecasting model. Specifically, the study updated the monthly factors submodel used to predict payments on construction contracts. For the other submodel rev...

Exploratory studies into seasonal flow forecasting potential for large lakes

NASA Astrophysics Data System (ADS)

Sene, Kevin; Tych, Wlodek; Beven, Keith

2018-01-01

In seasonal flow forecasting applications, one factor which can help predictability is a significant hydrological response time between rainfall and flows. On account of storage influences, large lakes therefore provide a useful test case although, due to the spatial scales involved, there are a number of modelling challenges related to data availability and understanding the individual components in the water balance. Here some possible model structures are investigated using a range of stochastic regression and transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world - Lake Malawi and Lake Victoria - with forecast skill demonstrated several months ahead using water balance models formulated in terms of net inflows. In both cases slight improvements were obtained for lead times up to 4-5 months from including climate indices in the data assimilation component. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.

Hourly runoff forecasting for flood risk management: Application of various computational intelligence models

NASA Astrophysics Data System (ADS)

Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.

2015-10-01

Reliable river flow forecasts play a key role in flood risk mitigation. Among different approaches of river flow forecasting, data driven approaches have become increasingly popular in recent years due to their minimum information requirements and ability to simulate nonlinear and non-stationary characteristics of hydrological processes. In this study, attempts are made to apply four different types of data driven approaches, namely traditional artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), wavelet neural networks (WNN), and, hybrid ANFIS with multi resolution analysis using wavelets (WNF). Developed models applied for real time flood forecasting at Casino station on Richmond River, Australia which is highly prone to flooding. Hourly rainfall and runoff data were used to drive the models which have been used for forecasting with 1, 6, 12, 24, 36 and 48 h lead-time. The performance of models further improved by adding an upstream river flow data (Wiangaree station), as another effective input. All models perform satisfactorily up to 12 h lead-time. However, the hybrid wavelet-based models significantly outperforming the ANFIS and ANN models in the longer lead-time forecasting. The results confirm the robustness of the proposed structure of the hybrid models for real time runoff forecasting in the study area.

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.

Operational wind shear detection and warning - The 'CLAWS' experience at Denver and future objectives

NASA Technical Reports Server (NTRS)

Mccarthy, John; Wilson, James W.; Hjelmfelt, Mark R.

1986-01-01

An operational wind shear detection and warning experiment was conducted at Denver's Stapleton International Airport in summer 1984. Based on meteorological interpretation of scope displays from a Doppler weather radar, warnings were transmitted to the air traffic control tower via voice radio. Analyses of results indicated real skill in daily microburst forecasts and very short-term (less than 5-min) warnings. Wind shift advisories with 15-30 min forecasts, permitted more efficient runway reconfigurations. Potential fuel savings were estimated at $875,000/yr at Stapleton. The philosophy of future development toward an automated, operational system is discussed.

Studies in short haul air transportation in the California corridor: Effects of design runway length; community acceptance; impact of return on investment and fuel cost increases. Volume 2: Appendices

NASA Technical Reports Server (NTRS)

Shevell, R. S.; Jones, D. W., Jr.

1973-01-01

The development of a forecast model for short haul air transportation systems in the California Corridor is discussed. The factors which determine the level of air traffic demand are identified. A forecast equation for use in airport utilization analysis is developed. A mathematical model is submitted to show the relationship between population, employment, and income for indicating future air transportation utilization. Diagrams and tables of data are included to support the conclusions reached regarding air transportation economic factors.

Traffic signal synchronization.

PubMed

Huang, Ding-wei; Huang, Wei-neng

2003-05-01

The benefits of traffic signal synchronization are examined within the cellular automata approach. The microsimulations of traffic flow are obtained with different settings of signal period T and time delay delta. Both numerical results and analytical approximations are presented. For undersaturated traffic, the green-light wave solutions can be realized. For saturated traffic, the correlation among the traffic signals has no effect on the throughput. For oversaturated traffic, the benefits of synchronization are manifest only when stochastic noise is suppressed.

32 CFR 634.31 - Parking.

Code of Federal Regulations, 2013 CFR

2013-07-01

... be avoided. (c) Illegal parking contributes to congestion and slows traffic flow on an installation... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.31 Parking. (a) The most efficient use... eliminates conditions causing traffic accidents. (d) The “Denver boot” device is authorized for use as a...

32 CFR 634.31 - Parking.

Code of Federal Regulations, 2011 CFR

2011-07-01

... be avoided. (c) Illegal parking contributes to congestion and slows traffic flow on an installation... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.31 Parking. (a) The most efficient use... eliminates conditions causing traffic accidents. (d) The “Denver boot” device is authorized for use as a...

32 CFR 634.31 - Parking.

Code of Federal Regulations, 2014 CFR

2014-07-01

... be avoided. (c) Illegal parking contributes to congestion and slows traffic flow on an installation... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.31 Parking. (a) The most efficient use... eliminates conditions causing traffic accidents. (d) The “Denver boot” device is authorized for use as a...

32 CFR 634.31 - Parking.

Code of Federal Regulations, 2012 CFR

2012-07-01

... be avoided. (c) Illegal parking contributes to congestion and slows traffic flow on an installation... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.31 Parking. (a) The most efficient use... eliminates conditions causing traffic accidents. (d) The “Denver boot” device is authorized for use as a...

32 CFR 634.31 - Parking.

Code of Federal Regulations, 2010 CFR

2010-07-01

... eliminates conditions causing traffic accidents. (d) The “Denver boot” device is authorized for use as a... INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.31 Parking. (a) The most efficient use... be avoided. (c) Illegal parking contributes to congestion and slows traffic flow on an installation...

Simulation of three lanes one-way freeway in low visibility weather by possible traffic accidents

NASA Astrophysics Data System (ADS)

Pang, Ming-bao; Zheng, Sha-sha; Cai, Zhang-hui

2015-09-01

The aim of this work is to investigate the traffic impact of low visibility weather on a freeway including the fraction of real vehicle rear-end accidents and road traffic capacity. Based on symmetric two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of three-lane freeway mainline with the real occurrence of rear-end accidents in low visibility weather, which considers delayed reaction time and deceleration restriction, was established with access to real-time traffic information of intelligent transportation system (ITS). The characteristics of traffic flow in different visibility weather were discussed via the simulation experiments. The results indicate that incoming flow control (decreasing upstream traffic volume) and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume's enhancing. According to different visibility and traffic demand the appropriate control strategies should be adopted in order to not only decrease the probability of vehicle accidents but also avoid congestion.

A gain-loss framework based on ensemble flow forecasts to switch the urban drainage-wastewater system management towards energy optimization during dry periods

NASA Astrophysics Data System (ADS)

Courdent, Vianney; Grum, Morten; Munk-Nielsen, Thomas; Mikkelsen, Peter S.

2017-05-01

Precipitation is the cause of major perturbation to the flow in urban drainage and wastewater systems. Flow forecasts, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimize the operation of integrated urban drainage-wastewater systems (IUDWSs) during both wet and dry weather periods. Numerical weather prediction (NWP) models have significantly improved in recent years, having increased their spatial and temporal resolution. Finer resolution NWP are suitable for urban-catchment-scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain, and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with ensemble prediction systems (EPSs). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain and therefore errors will be made; decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run). This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The relative economic value (REV) approach associates economic values with the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain-loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecast). The specificity of this study is to optimize the energy consumption in IUDWS during low-flow periods by exploiting the electrical smart grid market (i.e. the actions are taken when no events are forecast). Furthermore, the results demonstrate the benefit of NWP neighbourhood post-processing methods to enhance the forecast skill and increase the range of beneficial uses.

Evaluation of dynamic message signs and their potential impact on traffic flow : [research summary].

DOT National Transportation Integrated Search

2013-04-01

The objective of this research was to understand the potential impact of DMS messages on traffic : flow and evaluate their accuracy, timeliness, relevance and usefulness. Additionally, Bluetooth : sensors were used to track and analyze the diversion ...

Development of a Computational Framework for Big Data-Driven Prediction of Long-Term Bridge Performance and Traffic Flow

DOT National Transportation Integrated Search

2018-04-01

Consistent efforts with dense sensor deployment and data gathering processes for bridge big data have accumulated profound information regarding bridge performance, associated environments, and traffic flows. However, direct applications of bridge bi...

Forecasting the Movement of Educational Administrators Through Vacancy Flows

ERIC Educational Resources Information Center

Brown, Daniel J.

1976-01-01

Discusses the problem of forecasting manpower flows in administrative hierarchies of educational organizations, reviews groups of manpower models, discusses characteristics of administrative hierarchies and the vacancy model as it relates to those characteristics, and carries out validation and projective tests of the model. (Author/IRT)

Long-term forecasting of internet backbone traffic.

PubMed

Papagiannaki, Konstantina; Taft, Nina; Zhang, Zhi-Li; Diot, Christophe

2005-09-01

We introduce a methodology to predict when and where link additions/upgrades have to take place in an Internet protocol (IP) backbone network. Using simple network management protocol (SNMP) statistics, collected continuously since 1999, we compute aggregate demand between any two adjacent points of presence (PoPs) and look at its evolution at time scales larger than 1 h. We show that IP backbone traffic exhibits visible long term trends, strong periodicities, and variability at multiple time scales. Our methodology relies on the wavelet multiresolution analysis (MRA) and linear time series models. Using wavelet MRA, we smooth the collected measurements until we identify the overall long-term trend. The fluctuations around the obtained trend are further analyzed at multiple time scales. We show that the largest amount of variability in the original signal is due to its fluctuations at the 12-h time scale. We model inter-PoP aggregate demand as a multiple linear regression model, consisting of the two identified components. We show that this model accounts for 98% of the total energy in the original signal, while explaining 90% of its variance. Weekly approximations of those components can be accurately modeled with low-order autoregressive integrated moving average (ARIMA) models. We show that forecasting the long term trend and the fluctuations of the traffic at the 12-h time scale yields accurate estimates for at least 6 months in the future.

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...

Parametrisation of initial conditions for seasonal stream flow forecasting in the Swiss Rhine basin

NASA Astrophysics Data System (ADS)

Schick, Simon; Rössler, Ole; Weingartner, Rolf

2016-04-01

Current climate forecast models show - to the best of our knowledge - low skill in forecasting climate variability in Central Europe at seasonal lead times. When it comes to seasonal stream flow forecasting, initial conditions thus play an important role. Here, initial conditions refer to the catchments moisture at the date of forecast, i.e. snow depth, stream flow and lake level, soil moisture content, and groundwater level. The parametrisation of these initial conditions can take place at various spatial and temporal scales. Examples are the grid size of a distributed model or the time aggregation of predictors in statistical models. Therefore, the present study aims to investigate the extent to which the parametrisation of initial conditions at different spatial scales leads to differences in forecast errors. To do so, we conduct a forecast experiment for the Swiss Rhine at Basel, which covers parts of Germany, Austria, and Switzerland and is southerly bounded by the Alps. Seasonal mean stream flow is defined for the time aggregation of 30, 60, and 90 days and forecasted at 24 dates within the calendar year, i.e. at the 1st and 16th day of each month. A regression model is employed due to the various anthropogenic effects on the basins hydrology, which often are not quantifiable but might be grasped by a simple black box model. Furthermore, the pool of candidate predictors consists of antecedent temperature, precipitation, and stream flow only. This pragmatic approach follows the fact that observations of variables relevant for hydrological storages are either scarce in space or time (soil moisture, groundwater level), restricted to certain seasons (snow depth), or regions (lake levels, snow depth). For a systematic evaluation, we therefore focus on the comprehensive archives of meteorological observations and reanalyses to estimate the initial conditions via climate variability prior to the date of forecast. The experiment itself is based on four different approaches, whose differences in model skill were estimated within a rigorous cross-validation framework for the period 1982-2013: The predictands are regressed on antecedent temperature, precipitation, and stream flow. Here, temperature and precipitation constitute basin averages out of the E-OBS gridded data set. As in 1., but temperature and precipitation are used at the E-OBS grid scale (0.25 degree in longitude and latitude) without spatial averaging. As in 1., but the regression model is applied to 66 gauged subcatchments of the Rhine basin. Forecasts for these subcatchments are then simply summed and upscaled to the area of the Rhine basin. As in 3., but the forecasts at the subcatchment scale are additionally weighted in terms of hydrological representativeness of the corresponding subcatchment.

An intelligent traffic controller

DOT National Transportation Integrated Search

1995-11-01

Advances in computing sciences have not been applied to traffic control. This paper describes the development of an intelligent controller. A controller with advanced control logic can significantly improve traffic flows at intersections. In this vei...

Distributed traffic signal control using fuzzy logic

NASA Technical Reports Server (NTRS)

Chiu, Stephen

1992-01-01

We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

NASA Astrophysics Data System (ADS)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

A new macro model of traffic flow by incorporating both timid and aggressive driving behaviors

NASA Astrophysics Data System (ADS)

Peng, Guanghan; Qing, Li

2016-10-01

In this paper, a novel macro model is derived from car-following model by applying the relationship between the micro and macro variables by incorporating the timid and aggressive effects of optimal velocity on a single lane. Numerical simulation shows that the timid and aggressive macro model of traffic flow can correctly reproduce common evolution of shock, rarefaction waves and local cluster effects under small perturbation. Also, the results uncover that the aggressive effect can smoothen the front of the shock wave and the timid effect results in local press peak, which means that the timid effect hastens the process of congregation in the shock wave. The more timid traffic behaviors are, the smaller is the stable range. Furthermore, the research shows that the advantage of the aggressive effect over the timid one lies in the fact that the aggressive traffic behaviors can improve the stability of traffic flow with the consideration of incorporating timid and aggressive driving behaviors at the same time.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street.

PubMed

Panaggio, Mark J; Ottino-Löffler, Bertand J; Hu, Peiguang; Abrams, Daniel M

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this "green-wave" scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Predicting reduced visibility related crashes on freeways using real-time traffic flow data.

PubMed

Hassan, Hany M; Abdel-Aty, Mohamed A

2013-06-01

The main objective of this paper is to investigate whether real-time traffic flow data, collected from loop detectors and radar sensors on freeways, can be used to predict crashes occurring at reduced visibility conditions. In addition, it examines the difference between significant factors associated with reduced visibility related crashes to those factors correlated with crashes occurring at clear visibility conditions. Random Forests and matched case-control logistic regression models were estimated. The findings indicated that real-time traffic variables can be used to predict visibility related crashes on freeways. The results showed that about 69% of reduced visibility related crashes were correctly identified. The results also indicated that traffic flow variables leading to visibility related crashes are slightly different from those variables leading to clear visibility crashes. Using time slices 5-15 minutes before crashes might provide an opportunity for the appropriate traffic management centers for a proactive intervention to reduce crash risk in real-time. Copyright © 2013 Elsevier Ltd. All rights reserved.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street

NASA Astrophysics Data System (ADS)

Panaggio, Mark J.; Ottino-Löffler, Bertand J.; Hu, Peiguang; Abrams, Daniel M.

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this “green-wave” scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Airborne Management of Traffic Conflicts in Descent With Arrival Constraints

NASA Technical Reports Server (NTRS)

Doble, Nathan A.; Barhydt, Richard; Krishnamurthy, Karthik

2005-01-01

NASA is studying far-term air traffic management concepts that may increase operational efficiency through a redistribution of decisionmaking authority among airborne and ground-based elements of the air transportation system. One component of this research, En Route Free Maneuvering, allows trained pilots of equipped autonomous aircraft to assume responsibility for traffic separation. Ground-based air traffic controllers would continue to separate traffic unequipped for autonomous operations and would issue flow management constraints to all aircraft. To evaluate En Route Free Maneuvering operations, a human-in-the-loop experiment was jointly conducted by the NASA Ames and Langley Research Centers. In this experiment, test subject pilots used desktop flight simulators to resolve conflicts in cruise and descent, and to adhere to air traffic flow constraints issued by test subject controllers. Simulators at NASA Langley were equipped with a prototype Autonomous Operations Planner (AOP) flight deck toolset to assist pilots with conflict management and constraint compliance tasks. Results from the experiment are presented, focusing specifically on operations during the initial descent into the terminal area. Airborne conflict resolution performance in descent, conformance to traffic flow management constraints, and the effects of conflicting traffic on constraint conformance are all presented. Subjective data from subject pilots are also presented, showing perceived levels of workload, safety, and acceptability of autonomous arrival operations. Finally, potential AOP functionality enhancements are discussed along with suggestions to improve arrival procedures.

Assessment of methods for simplified traffic noise mapping of small cities: Casework of the city of Valdivia, Chile.

PubMed

Bastián-Monarca, Nicolás A; Suárez, Enrique; Arenas, Jorge P

2016-04-15

In many countries such as Chile, there is scarce official information for generating accurate noise maps. Therefore, specific simplification methods are becoming a real need for the acoustic community in developing countries. Thus, the main purpose of this work was to evaluate and apply simplified methods to generate a cost-effective traffic noise map of a small city of Chile. The experimental design involved the simplification of the cartographic information on buildings by clustering the households within a block, and the classification of the vehicular traffic flows into categories to generate an inexpensive noise map. The streets have been classified according to the official road classification of the country. Segregation of vehicles from light, heavy and motorbikes is made to account for traffic flow. In addition, a number of road traffic noise models were compared with noise measurements and consequently the road traffic model RLS-90 was chosen to generate the noise map of the city using the Computer Aided Noise Abatement (CadnaA) software. It was observed a direct dependence between noise levels and traffic flow versus each category of street used. The methodology developed in this study appears to be convenient in developing countries to obtain accurate approximations to develop inexpensive traffic noise maps. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting areas of sustainable error growth in quasigeostrophic flows using perturbation alignment properties

NASA Astrophysics Data System (ADS)

Rivière, G.; Hua, B. L.

2004-10-01

A new perturbation initialization method is used to quantify error growth due to inaccuracies of the forecast model initial conditions in a quasigeostrophic box ocean model describing a wind-driven double gyre circulation. This method is based on recent analytical results on Lagrangian alignment dynamics of the perturbation velocity vector in quasigeostrophic flows. More specifically, it consists in initializing a unique perturbation from the sole knowledge of the control flow properties at the initial time of the forecast and whose velocity vector orientation satisfies a Lagrangian equilibrium criterion. This Alignment-based Initialization method is hereafter denoted as the AI method.In terms of spatial distribution of the errors, we have compared favorably the AI error forecast with the mean error obtained with a Monte-Carlo ensemble prediction. It is shown that the AI forecast is on average as efficient as the error forecast initialized with the leading singular vector for the palenstrophy norm, and significantly more efficient than that for total energy and enstrophy norms. Furthermore, a more precise examination shows that the AI forecast is systematically relevant for all control flows whereas the palenstrophy singular vector forecast leads sometimes to very good scores and sometimes to very bad ones.A principal component analysis at the final time of the forecast shows that the AI mode spatial structure is comparable to that of the first eigenvector of the error covariance matrix for a "bred mode" ensemble. Furthermore, the kinetic energy of the AI mode grows at the same constant rate as that of the "bred modes" from the initial time to the final time of the forecast and is therefore characterized by a sustained phase of error growth. In this sense, the AI mode based on Lagrangian dynamics of the perturbation velocity orientation provides a rationale of the "bred mode" behavior.

A new bus lane on urban expressway with no-bay bus stop

NASA Astrophysics Data System (ADS)

Tian, Zhao; Jia, Limin

2016-01-01

The sharp increase in residents and vehicles causes heavy traffic pressure in many cities. To ease traffic congestion, it has been the common sense that we should develop public transit system. The priority of the bus appears particularly necessary with the rapid development of the public transport system. The bus lane is an important embodiment of the bus priority. Focusing on the problem of the unreasonable dedicated bus lane (DBL) under the lower ratio of buses, this paper proposed a new bus lane with limited physical length. And this bus lane can reduce the lane-changing conflict caused by the buses and cars running on roads without bus lanes. Based on the cellular automata (CA) traffic flow model and the lane-changing behavior of the vehicle including the optional lane-changing and the mandatory lane-changing, a three-lane traffic model with an isolated no-bay bus stop is proposed. The ordinary three-lane traffic without a bus lane and the cases of traffic with a DBL or the proposed bus lane are simulated, and the comparisons in the form of the fundamental diagrams are made among them. It is shown that the no-bay bus stop can act as a bottleneck on the traffic flow because of the mandatory lane-changing behavior. Under a certain ratio of the bus number to the total vehicles number, (1) the traffic with the proposed bus lane has less lane-changing conflict and can provide higher traffic capacity than the ordinary traffic without a bus lane, (2) compared with the DBL, the proposed bus lane is advantageous in easing congestion on the ordinary lanes when the traffic flow is high and can avoid unreasonable allocation of the road resources.

Atmospheric blocking as a traffic jam in the jet stream

NASA Astrophysics Data System (ADS)

Nakamura, N.; Huang, S. Y.

2017-12-01

It is demonstrated using the ERA-Interim product that synoptic to intraseasonal variabilities of extratropical circulation in the boreal storm track regions are strongly affected by the zonal convergence of the column-integrated eastward flux of local wave activity (LWA). In particular, from the multi-year daily samples of LWA fluxes, we find that the wintertime zonal LWA flux in the jet exit regions tends to maximize for an intermediate value of column-averaged LWA. This is because an increasing LWA decelerates the zonal flow, eventually weakening the eastward advection of LWA. From theory we argue that large wave events on the decreasing side of the flux curve with increasing LWA cannot be maintained as a stable steady state. Consistent with this argument, observed states corresponding to that side of flux curve often exhibit local wave breaking and blocking events. A close parallelism exists for the traffic flow problem, in which the traffic flux (traffic density times traffic speed) is often observed to maximize for an intermediate value of traffic density. This is because the traffic speed is controlled not only by the imposed speed limit but also by the traffic density — an increasingly heavy traffic slows down the flow naturally and eventually decreases the flux. Once the flux starts to decrease with an increasing traffic density, a traffic jam kicks in suddenly (Lighthill and Whitham 1955, Richards 1956). The above idea is demonstrated by a simple conceptual model based on the equivalent barotropic PV contour design (Nakamura and Huang 2017, JAS), which predicts a threshold of blocking onset. The idea also suggests that the LWA that gives the `flux capacity,' i.e., the maximum LWA flux at a given location, is a useful predictor of local wave breaking/block formation.

40 CFR 140.3 - Standard.

Code of Federal Regulations, 2013 CFR

2013-07-01

... traffic subject to this regulation, or in rivers not capable of navigation by interstate vessel traffic... sewage. This shall not be construed to prohibit the carriage of Coast Guard-certified flow-through... promulgation of this regulation with a Coast Guard-certified flow-through marine sanitation device meeting the...

40 CFR 140.3 - Standard.

Code of Federal Regulations, 2012 CFR

2012-07-01

... traffic subject to this regulation, or in rivers not capable of navigation by interstate vessel traffic... sewage. This shall not be construed to prohibit the carriage of Coast Guard-certified flow-through... promulgation of this regulation with a Coast Guard-certified flow-through marine sanitation device meeting the...

40 CFR 140.3 - Standard.

Code of Federal Regulations, 2014 CFR

2014-07-01

... traffic subject to this regulation, or in rivers not capable of navigation by interstate vessel traffic... sewage. This shall not be construed to prohibit the carriage of Coast Guard-certified flow-through... promulgation of this regulation with a Coast Guard-certified flow-through marine sanitation device meeting the...

Human factors integration challenges in the traffic flow management (TFM) environment

DOT National Transportation Integrated Search

2005-08-01

This report discusses a high level examination that was conducted to identify human factors issues in the integration of future traffic flow management (TFM) tools. The focus of the examination is on the integration of future systems and was driven b...

Benefit Analysis of the Automated Flow Control Function of the Air Traffic Control Systems Command Center

DOT National Transportation Integrated Search

1977-06-01

This report summarizes the findings of a benefit analysis study of the present and proposed Air Traffic Control Systems Command Center automation systems. The benefits analyzed were those associated with Fuel Advisory Departure and Quota Flow procedu...

The development of a model and decision support system to use in forecasting truck freight flow in the continental United States

DOT National Transportation Integrated Search

2001-01-01

This research develops a regression-based model for forecasting truck borne freight in the continental United States. This model is capable of predicting freight commodity flow information via trucks to assist transportation planners who wish to unde...

14 CFR 93.67 - General rules: Bryant segment.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Airport shall conform to the flow of traffic shown on the appropriate aeronautical charts, and while in the traffic pattern, shall operate that airplane at an altitude of at least 1,000 feet MSL until... (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal...

14 CFR 271.5 - Carrier revenues.

Code of Federal Regulations, 2014 CFR

2014-01-01

... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...

14 CFR 93.67 - General rules: Bryant segment.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Airport shall conform to the flow of traffic shown on the appropriate aeronautical charts, and while in the traffic pattern, shall operate that airplane at an altitude of at least 1,000 feet MSL until... (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal...

14 CFR 271.5 - Carrier revenues.

Code of Federal Regulations, 2013 CFR

2013-01-01

... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...

14 CFR 93.67 - General rules: Bryant segment.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Airport shall conform to the flow of traffic shown on the appropriate aeronautical charts, and while in the traffic pattern, shall operate that airplane at an altitude of at least 1,000 feet MSL until... (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal...

14 CFR 93.67 - General rules: Bryant segment.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Airport shall conform to the flow of traffic shown on the appropriate aeronautical charts, and while in the traffic pattern, shall operate that airplane at an altitude of at least 1,000 feet MSL until... (CONTINUED) AIR TRAFFIC AND GENERAL OPERATING RULES SPECIAL AIR TRAFFIC RULES Anchorage, Alaska, Terminal...

14 CFR 271.5 - Carrier revenues.

Code of Federal Regulations, 2011 CFR

2011-01-01

... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...

14 CFR 271.5 - Carrier revenues.

Code of Federal Regulations, 2012 CFR

2012-01-01

... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...

Development of automated testing tools for traffic control signals and devices (NTCIP and security) phase 2 : [summary].

DOT National Transportation Integrated Search

2015-02-01

The metal cabinets that house traffic signal : controllers are a common sight at most : intersections in Florida. Traffic engineers use them : to time signal changes and facilitate the flow of : traffic through an intersection. At the core of this : ...

Power Grid Maintenance Scheduling Intelligence Arrangement Supporting System Based on Power Flow Forecasting

NASA Astrophysics Data System (ADS)

Xie, Chang; Wen, Jing; Liu, Wenying; Wang, Jiaming

With the development of intelligent dispatching, the intelligence level of network control center full-service urgent need to raise. As an important daily work of network control center, the application of maintenance scheduling intelligent arrangement to achieve high-quality and safety operation of power grid is very important. By analyzing the shortages of the traditional maintenance scheduling software, this paper designs a power grid maintenance scheduling intelligence arrangement supporting system based on power flow forecasting, which uses the advanced technologies in maintenance scheduling, such as artificial intelligence, online security checking, intelligent visualization techniques. It implements the online security checking of maintenance scheduling based on power flow forecasting and power flow adjusting based on visualization, in order to make the maintenance scheduling arrangement moreintelligent and visual.

A Sector Capacity Assessment Method Based on Airspace Utilization Efficiency

NASA Astrophysics Data System (ADS)

Zhang, Jianping; Zhang, Ping; Li, Zhen; Zou, Xiang

2018-02-01

Sector capacity is one of the core factors affecting the safety and the efficiency of the air traffic system. Most of previous sector capacity assessment methods only considered the air traffic controller’s (ATCO’s) workload. These methods are not only limited which only concern about the safety, but also not accurate enough. In this paper, we employ the integrated quantitative index system proposed in one of our previous literatures. We use the principal component analysis (PCA) to find out the principal indicators among the indicators so as to calculate the airspace utilization efficiency. In addition, we use a series of fitting functions to test and define the correlation between the dense of air traffic flow and the airspace utilization efficiency. The sector capacity is then decided as the value of the dense of air traffic flow corresponding to the maximum airspace utilization efficiency. We also use the same series of fitting functions to test the correlation between the dese of air traffic flow and the ATCOs’ workload. We examine our method with a large amount of empirical operating data of Chengdu Controlling Center and obtain a reliable sector capacity value. Experiment results also show superiority of our method against those only consider the ATCO’s workload in terms of better correlation between the airspace utilization efficiency and the dense of air traffic flow.

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.

Physics of Traffic Flow

NASA Astrophysics Data System (ADS)

Davis, L. C.

2015-03-01

The Texas A&M Transportation Institute estimated that traffic congestion cost the United States 121 billion in 2011 (the latest data available). The cost is due to wasted time and fuel. In addition to accidents and road construction, factors contributing to congestion include large demand, instability of high-density free flow and selfish behavior of drivers, which produces self-organized traffic bottlenecks. Extensive data collected on instrumented highways in various countries have led to a better understanding of traffic dynamics. From these measurements, Boris Kerner and colleagues developed a new theory called three-phase theory. They identified three major phases of flow observed in the data: free flow, synchronous flow and wide moving jams. The intermediate phase is called synchronous because vehicles in different lanes tend to have similar velocities. This congested phase, characterized by lower velocities yet modestly high throughput, frequently occurs near on-ramps and lane reductions. At present there are only two widely used methods of congestion mitigation: ramp metering and the display of current travel-time information to drivers. To find more effective methods to reduce congestion, researchers perform large-scale simulations using models based on the new theories. An algorithm has been proposed to realize Wardrop equilibria with real-time route information. Such equilibria have equal travel time on alternative routes between a given origin and destination. An active area of current research is the dynamics of connected vehicles, which communicate wirelessly with other vehicles and the surrounding infrastructure. These systems show great promise for improving traffic flow and safety.

Traffic Management Plan Effectiveness Study, Final Report

DOT National Transportation Integrated Search

1993-05-28

MULTI-DIMENSIONAL TRAFFIC MANAGEMENT PLANS (TMPS) HAVE BECOME INCREASINGLY ACCEPTED BY TRANSPORTATION PROFESSIONALS, STATE AND LOCAL GOVERNMENTS AND THE PUBLIC AS A VIABLE MEANS OF MAINTANING ACCEPTABLE LEVELS OF TRAFFIC FLOW DURING PERIODS OF TRAFFI...

Use of forecasting signatures to help distinguish periodicity, randomness, and chaos in ripples and other spatial patterns

USGS Publications Warehouse

Rubin, D.M.

1992-01-01

Forecasting of one-dimensional time series previously has been used to help distinguish periodicity, chaos, and noise. This paper presents two-dimensional generalizations for making such distinctions for spatial patterns. The techniques are evaluated using synthetic spatial patterns and then are applied to a natural example: ripples formed in sand by blowing wind. Tests with the synthetic patterns demonstrate that the forecasting techniques can be applied to two-dimensional spatial patterns, with the same utility and limitations as when applied to one-dimensional time series. One limitation is that some combinations of periodicity and randomness exhibit forecasting signatures that mimic those of chaos. For example, sine waves distorted with correlated phase noise have forecasting errors that increase with forecasting distance, errors that, are minimized using nonlinear models at moderate embedding dimensions, and forecasting properties that differ significantly between the original and surrogates. Ripples formed in sand by flowing air or water typically vary in geometry from one to another, even when formed in a flow that is uniform on a large scale; each ripple modifies the local flow or sand-transport field, thereby influencing the geometry of the next ripple downcurrent. Spatial forecasting was used to evaluate the hypothesis that such a deterministic process - rather than randomness or quasiperiodicity - is responsible for the variation between successive ripples. This hypothesis is supported by a forecasting error that increases with forecasting distance, a greater accuracy of nonlinear relative to linear models, and significant differences between forecasts made with the original ripples and those made with surrogate patterns. Forecasting signatures cannot be used to distinguish ripple geometry from sine waves with correlated phase noise, but this kind of structure can be ruled out by two geometric properties of the ripples: Successive ripples are highly correlated in wavelength, and ripple crests display dislocations such as branchings and mergers. ?? 1992 American Institute of Physics.

The THOR Project-Reducing the Impact of Thunderstorms on Aviation and the General Public Through a Multi-Agency Effect

NASA Technical Reports Server (NTRS)

Smith, Stephan B.; Pace, David; Goodman, Steven J.; Burgess, Donald W.; Smarsh, David; Roberts, Rita D.; Wolfson, Marilyn M.; Goodman, H. Michael (Technical Monitor)

2001-01-01

Thunderstorms are high impact weather phenomena. They also pose an extremely challenging forecast problem. The National Oceanic and Atmospheric Administration (NOAA), the Federal Aviation Administration (FAA), the National Aeronautic and Space Administration (NASA), and the Air Force Weather Agency (AFWA), have decided to pool technology and scientific expertise into an unprecedented effort to better observe, diagnose, and forecast thunderstorms. This paper describes plans for an operational field test called the THunderstorm Operational Research (THOR) Project beginning in 2002, the primary goals of which are to: 1) Reduce the number of Thunderstorm-related Air Traffic Delays with in the National Airspace System (NAS) and, 2) Improve severe thunderstorm, tornado and airport thunderstorm warning accuracy and lead time. Aviation field operations will be focused on the prime air traffic bottleneck in the NAS, the airspace bounded roughly by Chicago, New York City and Washington D.C., sometimes called the Northeast Corridor. A variety of new automated thunderstorm forecasting applications will be tested here that, when implemented into FAA-NWS operations, will allow for better tactical decision making and NAS management during thunderstorm days. Severe thunderstorm operations will be centered on Northern Alabama. NWS meteorologists from the forecast office in Birmingham will test the utility of experimental lightning, radar, and profiler data from a mesoscale observing network being established by NASA's Marshall Space Flight Center. In addition, new tornado detection and thunderstorm nowcasting algorithms will be examined for their potential for improving warning accuracy. The Alabama THOR site will also serve as a test bed for new gridded, digital thunderstorm and flash flood warning products.

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development: Executive summary

NASA Technical Reports Server (NTRS)

Martino, J. P.; Lenz, R. C., Jr.; Chen, K. L.

1979-01-01

A cross impact model of the U.S. telecommunications system was developed. For this model, it was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impacts). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics, throughout the telecommunications system.

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1

NASA Technical Reports Server (NTRS)

Martino, J. P.; Lenz, R. C., Jr.; Chen, K. L.; Kahut, P.; Sekely, R.; Weiler, J.

1979-01-01

A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system.

Streamlining Transportation Corridor Planning Processess: Freight and Traffic Information

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

Franzese, Oscar

2010-08-01

The traffic investigation is one of the most important parts of an Environmental Impact Statement of projects involving the construction of new roadway facilities and/or the improvement of existing ones. The focus of the traffic analysis is on the determination of anticipated traffic flow characteristics of the proposed project, by the application of analytical methods that can be grouped under the umbrella of capacity analysis methodologies. In general, the main traffic parameter used in EISs to describe the quality of traffic flow is the Level of Service (LOS). The current state of the practice in terms of the traffic investigationsmore » for EISs has two main shortcomings. The first one is related to the information that is necessary to conduct the traffic analysis, and specifically to the lack of integration among the different transportation models and the sources of information that, in general, reside in GIS databases. A discussion of the benefits of integrating CRS&SI technologies and the transportation models used in the EIS traffic investigation is included. The second shortcoming is in the presentation of the results, both in terms of the appearance and formatting, as well as content. The presentation of traffic results (current and proposed) is discussed. This chapter also addresses the need of additional data, in terms of content and coverage. Regarding the former, other traffic parameters (e.g., delays) that are more meaningful to non-transportation experts than LOS, as well as additional information (e.g., freight flows) that can impact traffic conditions and safety are discussed. Spatial information technologies can decrease the negative effects of, and even eliminate, these shortcomings by making the relevant information that is input to the models more complete and readily available, and by providing the means to communicate the results in a more clear and efficient manner. The benefits that the application and use of CRS&SI technologies can provide to improve and expedite the traffic investigation part of the EIS process are presented.« less

Forecasting drought risks for a water supply storage system using bootstrap position analysis

USGS Publications Warehouse

Tasker, Gary; Dunne, Paul

1997-01-01

Forecasting the likelihood of drought conditions is an integral part of managing a water supply storage and delivery system. Position analysis uses a large number of possible flow sequences as inputs to a simulation of a water supply storage and delivery system. For a given set of operating rules and water use requirements, water managers can use such a model to forecast the likelihood of specified outcomes such as reservoir levels falling below a specified level or streamflows falling below statutory passing flows a few months ahead conditioned on the current reservoir levels and streamflows. The large number of possible flow sequences are generated using a stochastic streamflow model with a random resampling of innovations. The advantages of this resampling scheme, called bootstrap position analysis, are that it does not rely on the unverifiable assumption of normality and it allows incorporation of long-range weather forecasts into the analysis.

Research on traffic flow characteristics at signal intersection

NASA Astrophysics Data System (ADS)

Zeng, Jun-Wei; Yu, Sen-Bin; Qian, Yong-Sheng; Wei, Xu-Ting; Feng, Xiao; Wang, Hui

2017-09-01

Based on the cautious driving behavior and the principle of the vehicles at left-side having priority to pass in the intersection, a two-dimensional cellular automata model for planar signalized intersection (NS-STCA) is established. The different turning vehicles are regarded as the research objects and the effect of the left-turn probability, signal cycle, vehicle flow density on traffic flow at the intersection is investigated.

Optimizing airport capacity utilization in air traffic flow management subject to constraints at arrival and departure fixes

DOT National Transportation Integrated Search

1997-09-01

This paper formulates a new approach for improvement : of air traffic flow management at airports, which leads to : more efficient utilization of existing airport capacity to alleviate : the consequences of congestion. A new model is presented, : whi...

Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory

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

Kerner, Boris S.

It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliable used for control and optimization in traffic networks. It is shown that generally accepted fundamentals and methodologies of traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of traffic and transportation theory belong (i) Lighthill-Whitham-Richards (LWR) theory, (ii) the General Motors (GM) model class (formore » example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular stochastic value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of traffic and transportation theory, we discuss three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.« less

Effect of advanced aircraft noise reduction technology on the 1990 projected noise environment around Patrick Henry Airport. [development of noise exposure forecast contours for projected traffic volume and aircraft types

NASA Technical Reports Server (NTRS)

Cawthorn, J. M.; Brown, C. G.

1974-01-01

A study has been conducted of the future noise environment of Patric Henry Airport and its neighboring communities projected for the year 1990. An assessment was made of the impact of advanced noise reduction technologies which are currently being considered. These advanced technologies include a two-segment landing approach procedure and aircraft hardware modifications or retrofits which would add sound absorbent material in the nacelles of the engines or which would replace the present two- and three-stage fans with a single-stage fan of larger diameter. Noise Exposure Forecast (NEF) contours were computed for the baseline (nonretrofitted) aircraft for the projected traffic volume and fleet mix for the year 1990. These NEF contours are presented along with contours for a variety of retrofit options. Comparisons of the baseline with the noise reduction options are given in terms of total land area exposed to 30 and 40 NEF levels. Results are also presented of the effects on noise exposure area of the total number of daily operations.

Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea

NASA Astrophysics Data System (ADS)

Baek, K. T.; Lee, S.; Kang, M.; Lee, G.

2016-12-01

Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.

Multilane Traffic Flow Modeling Using Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina

2018-02-01

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

Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights.

PubMed

Arita, Chikashi; Foulaadvand, M Ebrahim; Santen, Ludger

2017-03-01

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights

NASA Astrophysics Data System (ADS)

Arita, Chikashi; Foulaadvand, M. Ebrahim; Santen, Ludger

2017-03-01

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

Best response game of traffic on road network of non-signalized intersections

NASA Astrophysics Data System (ADS)

Yao, Wang; Jia, Ning; Zhong, Shiquan; Li, Liying

2018-01-01

This paper studies the traffic flow in a grid road network with non-signalized intersections. The nature of the drivers in the network is simulated such that they play an iterative snowdrift game with other drivers. A cellular automata model is applied to study the characteristics of the traffic flow and the evolution of the behaviour of the drivers during the game. The drivers use best-response as their strategy to update rules. Three major findings are revealed. First, the cooperation rate in simulation experiences staircase-shaped drop as cost to benefit ratio r increases, and cooperation rate can be derived analytically as a function of cost to benefit ratio r. Second, we find that higher cooperation rate corresponds to higher average speed, lower density and higher flow. This reveals that defectors deteriorate the efficiency of traffic on non-signalized intersections. Third, the system experiences more randomness when the density is low because the drivers will not have much opportunity to update strategy when the density is low. These findings help to show how the strategy of drivers in a traffic network evolves and how their interactions influence the overall performance of the traffic system.

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.

Traffic signal synchronization in the saturated high-density grid road network.

PubMed

Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

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...

Fiber optic sensor for monitoring a density of road traffic

NASA Astrophysics Data System (ADS)

Nedoma, Jan; Fajkus, Marcel; Martinek, Radek; Mec, Pavel; Novak, Martin; Jargus, Jan; Vasinek, Vladimir

2017-10-01

Authors of this article have focused on the use of fiber-optic technology in the car traffic. The article describes the use of fiber-optic interferometer for the purpose of the dynamic calculation of traffic density and inclusion the vehicle into the traffic lane. The objective is to increase safety and traffic flow. Presented solution is characterized by the non-destructive character to the road - sensor no need built into the roadway. The sensor works with standard telecommunications fibers of the G.652 standard. Other hallmarks are immunity to electromagnetic interference (EMI) and passivity of concerning the power supply. The massive expansion of optical cables within telecommunication needs along roads offers the possibility of connecting to the existing telecommunications fiber-optic network without a converter. Information can be transmitted at distances of several km up to tens km by this fiber-optic network. Set of experimental measurements in real traffic flow verified the functionality of presented solution.

Traffic evacuation time under nonhomogeneous conditions.

PubMed

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

2017-06-01

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

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.

Analysis and forecast of railway coal transportation volume based on BP neural network combined forecasting model

NASA Astrophysics Data System (ADS)

Xu, Yongbin; Xie, Haihong; Wu, Liuyi

2018-05-01

The share of coal transportation in the total railway freight volume is about 50%. As is widely acknowledged, coal industry is vulnerable to the economic situation and national policies. Coal transportation volume fluctuates significantly under the new economic normal. Grasp the overall development trend of railway coal transportation market, have important reference and guidance significance to the railway and coal industry decision-making. By analyzing the economic indicators and policy implications, this paper expounds the trend of the coal transportation volume, and further combines the economic indicators with the high correlation with the coal transportation volume with the traditional traffic prediction model to establish a combined forecasting model based on the back propagation neural network. The error of the prediction results is tested, which proves that the method has higher accuracy and has practical application.

77 FR 65461 - Amendment of Area Navigation Route Q-1; CA

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-29

... existing ENVIE, CA, and EBINY, OR, waypoints for traffic flow metering with the Oakland Air Route Traffic... FAA is adding two waypoints along to route for air traffic control purposes. In addition, the route... is a routine matter that will only affect air traffic procedures and air navigation, it is certified...

Contributory factors to traffic crashes at signalized intersections in Hong Kong.

PubMed

Wong, S C; Sze, N N; Li, Y C

2007-11-01

Efficient geometric design and signal timing not only improve operational performance at signalized intersections by expanding capacity and reducing traffic delays, but also result in an appreciable reduction in traffic conflicts, and thus better road safety. Information on the incidence of crashes, traffic flow, geometric design, road environment, and traffic control at 262 signalized intersections in Hong Kong during 2002 and 2003 are incorporated into a crash prediction model. Poisson regression and negative binomial regression are used to quantify the influence of possible contributory factors on the incidence of killed and severe injury (KSI) crashes and slight injury crashes, respectively, while possible interventions by traffic flow are controlled. The results for the incidence of slight injury crashes reveal that the road environment, degree of curvature, and presence of tram stops are significant factors, and that traffic volume has a diminishing effect on the crash risk. The presence of tram stops, number of pedestrian streams, road environment, proportion of commercial vehicles, average lane width, and degree of curvature increase the risk of KSI crashes, but the effect of traffic volume is negligible.

Signing and pavement marking for concurrent-flow high-occupancy-vehicle lanes : summary of current practice

DOT National Transportation Integrated Search

1997-01-01

Concurrent-flow lanes account for more than half of existing high-occupancy-vehicle (HOV) mileage in the United States. Traffic on this type of HOV lane operates in the same direction as the adjacent traffic, typically in the far-left lane. Limited n...

Dynamic Capacity Allocation Algorithms for iNET Link Manager

DTIC Science & Technology

2014-05-01

algorithm that can better cope with severe congestion and misbehaving users and traffic flows. We compare the E-LM with the LM baseline algorithm (B-LM...capacity allocation algorithm that can better cope with severe congestion and misbehaving users and traffic flows. We compare the E-LM with the LM

Big data analytics : predicting traffic flow regimes from simulated connected vehicle messages using data analytics and machine learning.

DOT National Transportation Integrated Search

2016-12-25

The key objectives of this study were to: 1. Develop advanced analytical techniques that make use of a dynamically configurable connected vehicle message protocol to predict traffic flow regimes in near-real time in a virtual environment and examine ...