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.

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).

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.

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

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.

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.

Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

PubMed

Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

2017-10-01

Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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...

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.

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.

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.

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

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.

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 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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

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

Traffic Flow Management Wrap-Up

NASA Technical Reports Server (NTRS)

Grabbe, Shon

2011-01-01

Traffic Flow Management involves the scheduling and routing of air traffic subject to airport and airspace capacity constraints, and the efficient use of available airspace. Significant challenges in this area include: (1) weather integration and forecasting, (2) accounting for user preferences in the Traffic Flow Management decision making process, and (3) understanding and mitigating the environmental impacts of air traffic on the environment. To address these challenges, researchers in the Traffic Flow Management area are developing modeling, simulation and optimization techniques to route and schedule air traffic flights and flows while accommodating user preferences, accounting for system uncertainties and considering the environmental impacts of aviation. This presentation will highlight some of the major challenges facing researchers in this domain, while also showcasing recent innovations designed to address these challenges.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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....

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.

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

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

A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

PubMed

Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

2015-01-01

Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.

Applicability of models to estimate traffic noise for urban roads.

PubMed

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

2015-01-01

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

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.

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.

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.

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

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

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

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

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

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

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

Cellular automata model for use with real freeway data

DOT National Transportation Integrated Search

2002-01-01

The exponential rate of increase in freeway traffic is expanding the need for accurate and : realistic methods to model and predict traffic flow. Traffic modeling and simulation facilitates an : examination of both microscopic and macroscopic views o...

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.

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

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

NASA Astrophysics Data System (ADS)

Treiber, Martin; Helbing, Dirk

2003-10-01

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

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.

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.

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.

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.

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.

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.

Path Flow Estimation Using Time Varying Coefficient State Space Model

NASA Astrophysics Data System (ADS)

Jou, Yow-Jen; Lan, Chien-Lun

2009-08-01

The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.

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.

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...

Modeling self-consistent multi-class dynamic traffic flow

NASA Astrophysics Data System (ADS)

Cho, Hsun-Jung; Lo, Shih-Ching

2002-09-01

In this study, we present a systematic self-consistent multiclass multilane traffic model derived from the vehicular Boltzmann equation and the traffic dispersion model. The multilane domain is considered as a two-dimensional space and the interaction among vehicles in the domain is described by a dispersion model. The reason we consider a multilane domain as a two-dimensional space is that the driving behavior of road users may not be restricted by lanes, especially motorcyclists. The dispersion model, which is a nonlinear Poisson equation, is derived from the car-following theory and the equilibrium assumption. Under the concept that all kinds of users share the finite section, the density is distributed on a road by the dispersion model. In addition, the dynamic evolution of the traffic flow is determined by the systematic gas-kinetic model derived from the Boltzmann equation. Multiplying Boltzmann equation by the zeroth, first- and second-order moment functions, integrating both side of the equation and using chain rules, we can derive continuity, motion and variance equation, respectively. However, the second-order moment function, which is the square of the individual velocity, is employed by previous researches does not have physical meaning in traffic flow. Although the second-order expansion results in the velocity variance equation, additional terms may be generated. The velocity variance equation we propose is derived from multiplying Boltzmann equation by the individual velocity variance. It modifies the previous model and presents a new gas-kinetic traffic flow model. By coupling the gas-kinetic model and the dispersion model, a self-consistent system is presented.

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.

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.

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.

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.

Effects of Stochastic Traffic Flow Model on Expected System Performance

DTIC Science & Technology

2012-12-01

NSWC-PCD has made considerable improvements to their pedestrian flow modeling . In addition to the linear paths, the 2011 version now includes...using stochastic paths. 2.2 Linear Paths vs. Stochastic Paths 2.2.1 Linear Paths and Direct Maximum Pd Calculation Modeling pedestrian traffic flow...as a stochastic process begins with the linear path model . Let the detec- tion area be R x C voxels. This creates C 2 total linear paths, path(Cs

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

PubMed

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

2014-01-01

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

A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

PubMed Central

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

2014-01-01

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

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.

Modeling the Environmental Impact of Air Traffic Operations

NASA Technical Reports Server (NTRS)

Chen, Neil

2011-01-01

There is increased interest to understand and mitigate the impacts of air traffic on the climate, since greenhouse gases, nitrogen oxides, and contrails generated by air traffic can have adverse impacts on the climate. The models described in this presentation are useful for quantifying these impacts and for studying alternative environmentally aware operational concepts. These models have been developed by leveraging and building upon existing simulation and optimization techniques developed for the design of efficient traffic flow management strategies. Specific enhancements to the existing simulation and optimization techniques include new models that simulate aircraft fuel flow, emissions and contrails. To ensure that these new models are beneficial to the larger climate research community, the outputs of these new models are compatible with existing global climate modeling tools like the FAA's Aviation Environmental Design Tool.

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.

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.

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...

A microcomputer based traffic evacuation modeling system for emergency planning application

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

Rathi, A.K.

1995-12-31

The US Army stockpiles unitary chemical weapons, both as bulk chemicals and as munitions, at eight major sites in the United States. The continued storage and disposal of the chemical stockpile has the potential for accidental releases of toxic gases that could escape the installation boundaries and pose a threat to the civilian population in the vicinity. 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 evacuatemore » 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 this 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

A microscopic lane changing process model for multilane traffic

NASA Astrophysics Data System (ADS)

Lv, Wei; Song, Wei-guo; Liu, Xiao-dong; Ma, Jian

2013-03-01

In previous simulations lane-changing behavior is usually assumed as an instantaneous action. However, in real traffic, lane changing is a continuing process which can seriously affect the following cars. In this paper, a microscopic lane-changing process (LCP) model is clearly described. A new idea of simplifying the lane-changing process to the car-following framework is presented by controlling fictitious cars. To verify the model, the results of flow, lane-changing frequency, and single-car velocity are extracted from experimental observations and are compared with corresponding simulation. It is found that the LCP model agrees well with actual traffic flow and lane-changing behaviors may induce a 12%-18% reduction of traffic flow. The results also reflect that most of the drivers on the two roads in a city are conservative but not aggressive to change lanes. Investigation of lane-changing frequency shows that the largest lane-changing frequency occurs at a medium density range from 15 vehs km lane to 35 vehs km lane. It also implies that the lane-changing process might strengthen velocity variation at medium density and weaken velocity variation at high density. It is hoped that the idea of this study may be helpful to promote the modeling and simulation study of traffic flow.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

NASA Astrophysics Data System (ADS)

Li, Shubin; Cao, Danni

2018-02-01

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

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.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

Yu, Shao-Wei; Shi, Zhong-Ke

2015-01-01

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

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.

A queuing model for road traffic simulation

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

Guerrouahane, N.; Aissani, D.; Bouallouche-Medjkoune, L.

We present in this article a stochastic queuing model for the raod traffic. The model is based on the M/G/c/c state dependent queuing model, and is inspired from the deterministic Godunov scheme for the road traffic simulation. We first propose a variant of M/G/c/c state dependent model that works with density-flow fundamental diagrams rather than density-speed relationships. We then extend this model in order to consider upstream traffic demand as well as downstream traffic supply. Finally, we show how to model a whole raod by concatenating raod sections as in the deterministic Godunov scheme.

GENERAL: A modified weighted probabilistic cellular automaton traffic flow model

NASA Astrophysics Data System (ADS)

Zhuang, Qian; Jia, Bin; Li, Xin-Gang

2009-08-01

This paper modifies the weighted probabilistic cellular automaton model (Li X L, Kuang H, Song T, et al 2008 Chin. Phys. B 17 2366) which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits. In the new model, the effects of the velocity at the last time step and drivers' desire for acceleration are taken into account. The fundamental diagram, spatial-temporal diagram, and the time series of one-minute data are analyzed. The results show that this model reproduces synchronized flow. Finally, it simulates the on-ramp system with the proposed model. Some characteristics including the phase diagram are studied.

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.

Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting

PubMed Central

Ming-jun, Deng; Shi-ru, Qu

2015-01-01

Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting. PMID:26779258

Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting.

PubMed

Deng, Ming-jun; Qu, Shi-ru

2015-01-01

Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting.

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.

Nonlinear density wave investigation for an extended car-following model considering driver’s memory and jerk

NASA Astrophysics Data System (ADS)

Jin, Zhizhan; Li, Zhipeng; Cheng, Rongjun; Ge, Hongxia

2018-01-01

Based on the two velocity difference model (TVDM), an extended car-following model is developed to investigate the effect of driver’s memory and jerk on traffic flow in this paper. By using linear stability analysis, the stability conditions are derived. And through nonlinear analysis, the time-dependent Ginzburg-Landau (TDGL) equation and the modified Korteweg-de Vries (mKdV) equation are obtained, respectively. The mKdV equation is constructed to describe the traffic behavior near the critical point. The evolution of traffic congestion and the corresponding energy consumption are discussed. Numerical simulations show that the improved model is found not only to enhance the stability of traffic flow, but also to depress the energy consumption, which are consistent with the theoretical analysis.

Exact results of 1D traffic cellular automata: The low-density behavior of the Fukui-Ishibashi model

NASA Astrophysics Data System (ADS)

Salcido, Alejandro; Hernández-Zapata, Ernesto; Carreón-Sierra, Susana

2018-03-01

The maximum entropy states of the cellular automata models for traffic flow in a single-lane with no anticipation are presented and discussed. The exact analytical solutions for the low-density behavior of the stochastic Fukui-Ishibashi traffic model were obtained and compared with computer simulations of the model. An excellent agreement was found.

Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

PubMed Central

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

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN. PMID:25663835

Soliton and kink jams in traffic flow with open boundaries.

PubMed

Muramatsu, M; Nagatani, T

1999-07-01

Soliton density wave is investigated numerically and analytically in the optimal velocity model (a car-following model) of a one-dimensional traffic flow with open boundaries. Soliton density wave is distinguished from the kink density wave. It is shown that the soliton density wave appears only at the threshold of occurrence of traffic jams. The Korteweg-de Vries (KdV) equation is derived from the optimal velocity model by the use of the nonlinear analysis. It is found that the traffic soliton appears only near the neutral stability line. The soliton solution is analytically obtained from the perturbed KdV equation. It is shown that the soliton solution obtained from the nonlinear analysis is consistent with that of the numerical simulation.

A least-effort principle based model for heterogeneous pedestrian flow considering overtaking behavior

NASA Astrophysics Data System (ADS)

Liu, Chi; Ye, Rui; Lian, Liping; Song, Weiguo; Zhang, Jun; Lo, Siuming

2018-05-01

In the context of global aging, how to design traffic facilities for a population with a different age composition is of high importance. For this purpose, we propose a model based on the least effort principle to simulate heterogeneous pedestrian flow. In the model, the pedestrian is represented by a three-disc shaped agent. We add a new parameter to realize pedestrians' preference to avoid changing their direction of movement too quickly. The model is validated with numerous experimental data on unidirectional pedestrian flow. In addition, we investigate the influence of corridor width and velocity distribution of crowds on unidirectional heterogeneous pedestrian flow. The simulation results reflect that widening corridors could increase the specific flow for the crowd composed of two kinds of pedestrians with significantly different free velocities. Moreover, compared with a unified crowd, the crowd composed of pedestrians with great mobility differences requires a wider corridor to attain the same traffic efficiency. This study could be beneficial in providing a better understanding of heterogeneous pedestrian flow, and quantified outcomes could be applied in traffic facility design.

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...

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.

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.

The Airspace Concepts Evaluation System Architecture and System Plant

NASA Technical Reports Server (NTRS)

Windhorst, Robert; Meyn, Larry; Manikonda, Vikram; Carlos, Patrick; Capozzi, Brian

2006-01-01

The Airspace Concepts Evaluation System is a simulation of the National Airspace System. It includes models of flights, airports, airspaces, air traffic controls, traffic flow managements, and airline operation centers operating throughout the United States. It is used to predict system delays in response to future capacity and demand scenarios and perform benefits assessments of current and future airspace technologies and operational concepts. Facilitation of these studies requires that the simulation architecture supports plug and play of different air traffic control, traffic flow management, and airline operation center models and multi-fidelity modeling of flights, airports, and airspaces. The simulation is divided into two parts that are named, borrowing from classical control theory terminology, control and plant. The control consists of air traffic control, traffic flow management, and airline operation center models, and the plant consists of flight, airport, and airspace models. The plant can run open loop, in the absence of the control. However, undesired affects, such as conflicts and over congestions in the airspaces and airports, can occur. Different controls are applied, "plug and played", to the plant. A particular control is evaluated by analyzing how well it managed conflicts and congestions. Furthermore, the terminal area plants consist of models of airports and terminal airspaces. Each model consists of a set of nodes and links which are connected by the user to form a network. Nodes model runways, fixes, taxi intersections, gates, and/or other points of interest, and links model taxiways, departure paths, and arrival paths. Metering, flow distribution, and sequencing functions can be applied at nodes. Different fidelity model of how a flight transits are can be used by links. The fidelity of the model can be adjusted by the user by either changing the complexity of the node/link network-or the way that the link models how the flights transit from one node to the other.

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.

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.

Safe distance car-following model including backward-looking and its stability analysis

NASA Astrophysics Data System (ADS)

Yang, Da; Jin, Peter Jing; Pu, Yun; Ran, Bin

2013-03-01

The focus of this paper is the car-following behavior including backward-looking, simply called the bi-directional looking car-following behavior. This study is motivated by the potential changes of the physical properties of traffic flow caused by the fast developing intelligent transportation system (ITS), especially the new connected vehicle technology. Existing studies on this topic focused on general motors (GM) models and optimal velocity (OV) models. The safe distance car-following model, Gipps' model, which is more widely used in practice have not drawn too much attention in the bi-directional looking context. This paper explores the property of the bi-directional looking extension of Gipps' safe distance model. The stability condition of the proposed model is derived using the linear stability theory and is verified using numerical simulations. The impacts of the driver and vehicle characteristics appeared in the proposed model on the traffic flow stability are also investigated. It is found that taking into account the backward-looking effect in car-following has three types of effect on traffic flow: stabilizing, destabilizing and producing non-physical phenomenon. This conclusion is more sophisticated than the study results based on the OV bi-directional looking car-following models. Moreover, the drivers who have the smaller reaction time or the larger additional delay and think the other vehicles have larger maximum decelerations can stabilize traffic flow.

From Traffic Flow to Economic System

NASA Astrophysics Data System (ADS)

Bando, M.

The optimal velocity model which is applied to traffic flow phenomena explains a spontaneous formation of traffic congestion. We discuss why the model works well in describing both free-flow and congested flow states in a unified way. The essential ingredient is that our model takes account of a sort of time delay in reacting to a given stimulus. This causes instability of many-body system, and yields a kind of phase transition above a certain critical density. Especially there appears a limit cycle on the phase space along which individual vehicle moves, and they show cyclic behavior. Once that we recognize the mechanism the same idea can be applied to a variety of phenomena which show cyclic behavior observed in many-body systems. As an example of such applications, we investigate business cycles commonly observed in economic system. We further discuss a possible origin of a kind of cyclic behavior observed in climate change.

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.

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.

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.

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...

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.

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...

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.

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

DOT National Transportation Integrated Search

1978-11-01

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

Minimal Traffic Model with Safe Driving Conditions

NASA Astrophysics Data System (ADS)

Terborg, Heinrich; Pérez, Luis A.

We have developed a new computational traffic model in which security aspects are fundamental. In this paper we show that this model reproduces many known empirical aspects of vehicular traffic such as the three states of traffic flow and the backward speed of the downstream front of a traffic jam (C), without the aid of adjustable parameters. The model is studied for both open and closed single lane traffic systems. Also, we were able to analytically compute the value of C as 15.37 km/h from a relation that only includes the human reaction time, the mean vehicle length and the effective friction coefficient during the braking process of a vehicle as its main components.

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

Drinking, driving, and crashing: a traffic-flow model of alcohol-related motor vehicle accidents.

PubMed

Gruenewald, Paul J; Johnson, Fred W

2010-03-01

This study examined the influence of on-premise alcohol-outlet densities and of drinking-driver densities on rates of alcohol-related motor vehicle crashes. A traffic-flow model is developed to represent geographic relationships between residential locations of drinking drivers, alcohol outlets, and alcohol-related motor vehicle crashes. Cross-sectional and time-series cross-sectional spatial analyses were performed using data collected from 144 geographic units over 4 years. Data were obtained from archival and survey sources in six communities. Archival data were obtained within community areas and measured activities of either the resident population or persons visiting these communities. These data included local and highway traffic flow, locations of alcohol outlets, population density, network density of the local roadway system, and single-vehicle nighttime (SVN) crashes. Telephone-survey data obtained from residents of the communities were used to estimate the size of the resident drinking and driving population. Cross-sectional analyses showed that effects relating on-premise densities to alcohol-related crashes were moderated by highway trafficflow. Depending on levels of highway traffic flow, 10% greater densities were related to 0% to 150% greater rates of SVN crashes. Time-series cross-sectional analyses showed that changes in the population pool of drinking drivers and on-premise densities interacted to increase SVN crash rates. A simple traffic-flow model can assess the effects of on-premise alcohol-outlet densities and of drinking-driver densities as they vary across communities to produce alcohol-related crashes. Analyses based on these models can usefully guide policy decisions on the sitting of on-premise alcohol outlets.

Safety performance of traffic phases and phase transitions in three phase traffic theory.

PubMed

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

2015-12-01

Crash risk prediction models were developed to link safety to various phases and phase transitions defined by the three phase traffic theory. Results of the Bayesian conditional logit analysis showed that different traffic states differed distinctly with respect to safety performance. The random-parameter logit approach was utilized to account for the heterogeneity caused by unobserved factors. The Bayesian inference approach based on the Markov Chain Monte Carlo (MCMC) method was used for the estimation of the random-parameter logit model. The proposed approach increased the prediction performance of the crash risk models as compared with the conventional logit model. The three phase traffic theory can help us better understand the mechanism of crash occurrences in various traffic states. The contributing factors to crash likelihood can be well explained by the mechanism of phase transitions. We further discovered that the free flow state can be divided into two sub-phases on the basis of safety performance, including a true free flow state in which the interactions between vehicles are minor, and a platooned traffic state in which bunched vehicles travel in successions. The results of this study suggest that a safety perspective can be added to the three phase traffic theory. The results also suggest that the heterogeneity between different traffic states should be considered when estimating the risks of crash occurrences on freeways. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

A cellular automation model accounting for bicycle's group behavior

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Rui, Ying-Xu; Zhang, Jian; Shang, Hua-Yan

2018-02-01

Recently, bicycle has become an important traffic tool in China, again. Due to the merits of bicycle, the group behavior widely exists in urban traffic system. However, little effort has been made to explore the impacts of the group behavior on bicycle flow. In this paper, we propose a CA (cellular automaton) model with group behavior to explore the complex traffic phenomena caused by shoulder group behavior and following group behavior on an open road. The numerical results illustrate that the proposed model can qualitatively describe the impacts of the two kinds of group behaviors on bicycle flow and that the effects are related to the mode and size of group behaviors. The results can help us to better understand the impacts of the bicycle's group behaviors on urban traffic system and effectively control the bicycle's group behavior.

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.

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 ...

The use of random forests in modelling short-term air pollution effects based on traffic and meteorological conditions: A case study in Wrocław.

PubMed

Kamińska, Joanna A

2018-07-01

Random forests, an advanced data mining method, are used here to model the regression relationships between concentrations of the pollutants NO 2 , NO x and PM 2.5 , and nine variables describing meteorological conditions, temporal conditions and traffic flow. The study was based on hourly values of wind speed, wind direction, temperature, air pressure and relative humidity, temporal variables, and finally traffic flow, in the two years 2015 and 2016. An air quality measurement station was selected on a main road, located a short distance (40 m) from a large intersection equipped with a traffic flow measurement system. Nine different time subsets were defined, based among other things on the climatic conditions in Wrocław. An analysis was made of the fit of models created for those subsets, and of the importance of the predictors. Both the fit and the importance of particular predictors were found to be dependent on season. The best fit was obtained for models created for the six-month warm season (April-September) and for the summer season (June-August). The most important explanatory variable in the models of concentrations of nitrogen oxides was traffic flow, while in the case of PM 2.5 the most important were meteorological conditions, in particular temperature, wind speed and wind direction. Temporal variables (except for month in the case of PM 2.5 ) were found to have no significant effect on the concentrations of the studied pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assimilating Eulerian and Lagrangian data in traffic-flow models

NASA Astrophysics Data System (ADS)

Xia, Chao; Cochrane, Courtney; DeGuire, Joseph; Fan, Gaoyang; Holmes, Emma; McGuirl, Melissa; Murphy, Patrick; Palmer, Jenna; Carter, Paul; Slivinski, Laura; Sandstede, Björn

2017-05-01

Data assimilation of traffic flow remains a challenging problem. One difficulty is that data come from different sources ranging from stationary sensors and camera data to GPS and cell phone data from moving cars. Sensors and cameras give information about traffic density, while GPS data provide information about the positions and velocities of individual cars. Previous methods for assimilating Lagrangian data collected from individual cars relied on specific properties of the underlying computational model or its reformulation in Lagrangian coordinates. These approaches make it hard to assimilate both Eulerian density and Lagrangian positional data simultaneously. In this paper, we propose an alternative approach that allows us to assimilate both Eulerian and Lagrangian data. We show that the proposed algorithm is accurate and works well in different traffic scenarios and regardless of whether ensemble Kalman or particle filters are used. We also show that the algorithm is capable of estimating parameters and assimilating real traffic observations and synthetic observations obtained from microscopic models.

Modeling and Control of Airport Queueing Dynamics under Severe Flow Restrictions

NASA Technical Reports Server (NTRS)

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

2003-01-01

Based on field observations and interviews with controllers at BOS and EWR, we identify the closure of local departure fixes as the most severe class of airport departure restrictions. A set of simple queueing dynamics and traffic rules are developed to model departure traffic under such restrictions. The validity of the proposed model is tested via Monte Carlo simulation against 10 hours of actual operations data collected during a case-study at EWR on June 29,2000. In general, the model successfully reproduces the aggregate departure congestion. An analysis of the average error over 40 simulation runs indicates that flow-rate restrictions also significantly impact departure traffic; work is underway to capture these effects. Several applications and what-if scenarios are discussed for future evaluation using the calibrated model.

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

PubMed

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

2017-01-01

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

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.

Traveling waves in an optimal velocity model of freeway traffic.

PubMed

Berg, P; Woods, A

2001-03-01

Car-following models provide both a tool to describe traffic flow and algorithms for autonomous cruise control systems. Recently developed optimal velocity models contain a relaxation term that assigns a desirable speed to each headway and a response time over which drivers adjust to optimal velocity conditions. These models predict traffic breakdown phenomena analogous to real traffic instabilities. In order to deepen our understanding of these models, in this paper, we examine the transition from a linear stable stream of cars of one headway into a linear stable stream of a second headway. Numerical results of the governing equations identify a range of transition phenomena, including monotonic and oscillating travelling waves and a time- dependent dispersive adjustment wave. However, for certain conditions, we find that the adjustment takes the form of a nonlinear traveling wave from the upstream headway to a third, intermediate headway, followed by either another traveling wave or a dispersive wave further downstream matching the downstream headway. This intermediate value of the headway is selected such that the nonlinear traveling wave is the fastest stable traveling wave which is observed to develop in the numerical calculations. The development of these nonlinear waves, connecting linear stable flows of two different headways, is somewhat reminiscent of stop-start waves in congested flow on freeways. The different types of adjustments are classified in a phase diagram depending on the upstream and downstream headway and the response time of the model. The results have profound consequences for autonomous cruise control systems. For an autocade of both identical and different vehicles, the control system itself may trigger formations of nonlinear, steep wave transitions. Further information is available [Y. Sugiyama, Traffic and Granular Flow (World Scientific, Singapore, 1995), p. 137].

Traveling waves in an optimal velocity model of freeway traffic

NASA Astrophysics Data System (ADS)

Berg, Peter; Woods, Andrew

2001-03-01

Car-following models provide both a tool to describe traffic flow and algorithms for autonomous cruise control systems. Recently developed optimal velocity models contain a relaxation term that assigns a desirable speed to each headway and a response time over which drivers adjust to optimal velocity conditions. These models predict traffic breakdown phenomena analogous to real traffic instabilities. In order to deepen our understanding of these models, in this paper, we examine the transition from a linear stable stream of cars of one headway into a linear stable stream of a second headway. Numerical results of the governing equations identify a range of transition phenomena, including monotonic and oscillating travelling waves and a time- dependent dispersive adjustment wave. However, for certain conditions, we find that the adjustment takes the form of a nonlinear traveling wave from the upstream headway to a third, intermediate headway, followed by either another traveling wave or a dispersive wave further downstream matching the downstream headway. This intermediate value of the headway is selected such that the nonlinear traveling wave is the fastest stable traveling wave which is observed to develop in the numerical calculations. The development of these nonlinear waves, connecting linear stable flows of two different headways, is somewhat reminiscent of stop-start waves in congested flow on freeways. The different types of adjustments are classified in a phase diagram depending on the upstream and downstream headway and the response time of the model. The results have profound consequences for autonomous cruise control systems. For an autocade of both identical and different vehicles, the control system itself may trigger formations of nonlinear, steep wave transitions. Further information is available [Y. Sugiyama, Traffic and Granular Flow (World Scientific, Singapore, 1995), p. 137].

Stability analysis of dynamic collaboration model with control signals on two lanes

NASA Astrophysics Data System (ADS)

Li, Zhipeng; Zhang, Run; Xu, Shangzhi; Qian, Yeqing; Xu, Juan

2014-12-01

In this paper, the influence of control signals on the stability of two-lane traffic flow is mainly studied by applying control theory with lane changing behaviors. We present the two-lane dynamic collaboration model with lateral friction and the expressions of feedback control signals. What is more, utilizing the delayed feedback control theory to the two-lane dynamic collaboration model with control signals, we investigate the stability of traffic flow theoretically and the stability conditions for both lanes are derived with finding that the forward and lateral feedback signals can improve the stability of traffic flow while the backward feedback signals cannot achieve it. Besides, direct simulations are conducted to verify the results of theoretical analysis, which shows that the feedback signals have a significant effect on the running state of two vehicle groups, and the results are same with the theoretical analysis.

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.

Path-preference cellular-automaton model for traffic flow through transit points and its application to the transcription process in human cells.

PubMed

Ohta, Yoshihiro; Nishiyama, Akinobu; Wada, Yoichiro; Ruan, Yijun; Kodama, Tatsuhiko; Tsuboi, Takashi; Tokihiro, Tetsuji; Ihara, Sigeo

2012-08-01

We all use path routing everyday as we take shortcuts to avoid traffic jams, or by using faster traffic means. Previous models of traffic flow of RNA polymerase II (RNAPII) during transcription, however, were restricted to one dimension along the DNA template. Here we report the modeling and application of traffic flow in transcription that allows preferential paths of different dimensions only restricted to visit some transit points, as previously introduced between the 5' and 3' end of the gene. According to its position, an RNAPII protein molecule prefers paths obeying two types of time-evolution rules. One is an asymmetric simple exclusion process (ASEP) along DNA, and the other is a three-dimensional jump between transit points in DNA where RNAPIIs are staying. Simulations based on our model, and comparison experimental results, reveal how RNAPII molecules are distributed at the DNA-loop-formation-related protein binding sites as well as CTCF insulator proteins (or exons). As time passes after the stimulation, the RNAPII density at these sites becomes higher. Apparent far-distance jumps in one dimension are realized by short-range three-dimensional jumps between DNA loops. We confirm the above conjecture by applying our model calculation to the SAMD4A gene by comparing the experimental results. Our probabilistic model provides possible scenarios for assembling RNAPII molecules into transcription factories, where RNAPII and related proteins cooperatively transcribe DNA.

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.

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

PubMed

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

2011-09-01

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

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.

40 CFR 52.1164 - Localized high concentrations-carbon monoxide.

Code of Federal Regulations, 2010 CFR

2010-07-01

... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...

40 CFR 52.1164 - Localized high concentrations-carbon monoxide.

Code of Federal Regulations, 2014 CFR

2014-07-01

... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...

40 CFR 52.1164 - Localized high concentrations-carbon monoxide.

Code of Federal Regulations, 2013 CFR

2013-07-01

... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...

40 CFR 52.1164 - Localized high concentrations-carbon monoxide.

Code of Federal Regulations, 2011 CFR

2011-07-01

... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...

40 CFR 52.1164 - Localized high concentrations-carbon monoxide.

Code of Federal Regulations, 2012 CFR

2012-07-01

... meteorological modeling, traffic flow monitoring, air quality monitoring and other measures necessary to... reviewing all available traffic data, physical site data and air quality and meteorological data for all... containing measures to regulate traffic and parking so as to reduce carbon monoxide emissions to achieve air...

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Yang, Lingrun; Li, Jing

2018-07-01

Most of the previous studies on dynamic traffic assignment are based on traditional analytical framework, for instance, the idea of Dynamic User Equilibrium has been widely used in depicting both the route choice and the departure time choice. However, some recent studies have demonstrated that the dynamic traffic flow assignment largely depends on travelers' rationality degree, travelers' heterogeneity and what the traffic information the travelers have. In this paper, we develop a new self-adaptive multi agent model to depict travelers' behavior in Dynamic Traffic Assignment. We use Cumulative Prospect Theory with heterogeneous reference points to illustrate travelers' bounded rationality. We use reinforcement-learning model to depict travelers' route and departure time choosing behavior under the condition of imperfect information. We design the evolution rule of travelers' expected arrival time and the algorithm of traffic flow assignment. Compared with the traditional model, the self-adaptive multi agent model we proposed in this paper can effectively help travelers avoid the rush hour. Finally, we report and analyze the effect of travelers' group behavior on the transportation system, and give some insights into the relation between travelers' group behavior and the performance of transportation system.

Integrated Traffic Flow Management Decision Making

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.; Sridhar, Banavar; Mukherjee, Avijit

2009-01-01

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

Methodology and guidelines for regulating traffic flows under air quality constraints in metropolitan areas.

DOT National Transportation Integrated Search

2010-02-01

This project developed a methodology to couple a new pollutant dispersion model with a traffic : assignment process to contain air pollution while maximizing mobility. The overall objective of the air : quality modeling part of the project is to deve...

Weather Impact on Airport Arrival Meter Fix Throughput

NASA Technical Reports Server (NTRS)

Wang, Yao

2017-01-01

Time-based flow management provides arrival aircraft schedules based on arrival airport conditions, airport capacity, required spacing, and weather conditions. In order to meet a scheduled time at which arrival aircraft can cross an airport arrival meter fix prior to entering the airport terminal airspace, air traffic controllers make regulations on air traffic. Severe weather may create an airport arrival bottleneck if one or more of airport arrival meter fixes are partially or completely blocked by the weather and the arrival demand has not been reduced accordingly. Under these conditions, aircraft are frequently being put in holding patterns until they can be rerouted. A model that predicts the weather impacted meter fix throughput may help air traffic controllers direct arrival flows into the airport more efficiently, minimizing arrival meter fix congestion. This paper presents an analysis of air traffic flows across arrival meter fixes at the Newark Liberty International Airport (EWR). Several scenarios of weather impacted EWR arrival fix flows are described. Furthermore, multiple linear regression and regression tree ensemble learning approaches for translating multiple sector Weather Impacted Traffic Indexes (WITI) to EWR arrival meter fix throughputs are examined. These weather translation models are developed and validated using the EWR arrival flight and weather data for the period of April-September in 2014. This study also compares the performance of the regression tree ensemble with traditional multiple linear regression models for estimating the weather impacted throughputs at each of the EWR arrival meter fixes. For all meter fixes investigated, the results from the regression tree ensemble weather translation models show a stronger correlation between model outputs and observed meter fix throughputs than that produced from multiple linear regression method.

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.

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).

Study on traffic characteristics for a typical expressway on-ramp bottleneck considering various merging behaviors

NASA Astrophysics Data System (ADS)

Sun, Jie; Li, Zhipeng; Sun, Jian

2015-12-01

Recurring bottlenecks at freeway/expressway are considered as the main cause of traffic congestion in urban traffic system while on-ramp bottlenecks are the most significant sites that may result in congestion. In this paper, the traffic bottleneck characteristics for a simple and typical expressway on-ramp are investigated by the means of simulation modeling under the open boundary condition. In simulations, the running behaviors of each vehicle are described by a car-following model with a calibrated optimal velocity function, and lane changing actions at the merging section are modeled by a novel set of rules. We numerically derive the traffic volume of on-ramp bottleneck under different upstream arrival rates of mainline and ramp flows. It is found that the vehicles from the ramp strongly affect the pass of mainline vehicles and the merging ratio changes with the increasing of ramp vehicle, when the arrival rate of mainline flow is greater than a critical value. In addition, we clarify the dependence of the merging ratio of on-ramp bottleneck on the probability of lane changing and the length of the merging section, and some corresponding intelligent control strategies are proposed in actual traffic application.

Modeling the effect of microscopic driving behaviors on Kerner's time-delayed traffic breakdown at traffic signal using cellular automata

NASA Astrophysics Data System (ADS)

Wang, Yang; Chen, Yan-Yan

2016-12-01

The signalized traffic is considerably complex due to the fact that various driving behaviors have emerged to respond to traffic signals. However, the existing cellular automaton models take the signal-vehicle interactions into account inadequately, resulting in a potential risk that vehicular traffic flow dynamics may not be completely explored. To remedy this defect, this paper proposes a more realistic cellular automaton model by incorporating a number of the driving behaviors typically observed when the vehicles are approaching a traffic light. In particular, the anticipatory behavior proposed in this paper is realized with a perception factor designed by considering the vehicle speed implicitly and the gap to its preceding vehicle explicitly. Numerical simulations have been performed based on a signal controlled road which is partitioned into three sections according to the different reactions of drivers. The effects of microscopic driving behaviors on Kerner's time-delayed traffic breakdown at signal (Kerner 2011, 2013) have been investigated with the assistance of spatiotemporal pattern and trajectory analysis. Furthermore, the contributions of the driving behaviors on the traffic breakdown have been statistically examined. Finally, with the activation of the anticipatory behavior, the influences of the other driving behaviors on the formation of platoon have been investigated in terms of the number of platoons, the averaged platoon size, and the averaged flow rate.

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.

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

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

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

2014-11-15

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

Developing a method for estimating AADT on all Louisiana roads.

DOT National Transportation Integrated Search

2015-07-01

Traffic flow volumes present key information needed for making transportation engineering and planning decisions. : Accurate traffic volume count has many applications including: roadway planning, design, air quality compliance, travel : model valida...

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Composable Flexible Real-time Packet Scheduling for Networks on-Chip

DTIC Science & Technology

2012-05-16

unclassified b . ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Copyright © 2012...words, real-time flows need to be composable. We set this as the design goal for our packet scheduling discipline developed in this paper. B . Motivating...with closest deadline is chosen to forward to the next router. B . Traffic Model We assume a traffic model for real-time flows similar to the one used

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

PubMed

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

2017-12-15

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

CO and NO2 pollution in a long two-way traffic road tunnel: investigation of NO2/NOx ratio and modelling of NO2 concentration.

PubMed

Indrehus, O; Vassbotn, P

2001-02-01

The CO, NO and NO2 concentrations, visibility and air flow velocity were measured using continuous analysers in a long Norwegian road tunnel (7.5 km) with traffic in both directions in April 1994 and 1995. The traffic density was monitored at the same time. The NO2 concentration exceeded Norwegian air quality limits for road tunnels 17% of the time in 1994. The traffic through the tunnel decreased from 1994 to 1995, and the mean NO2 concentration was reduced from 0.73 to 0.22 ppm. The ventilation fan control, based on the CO concentration only, was unsatisfactory and the air flow was sometimes low for hours. Models for NO2 concentration based on CO concentration and absolute air flow velocity were developed and tested. The NO2/NOx ratio showed an increase for NOx levels above 2 ppm; a likely explanation for this phenomenon is NO oxidation by O2. Exposure to high NO2 concentrations may represent a health risk for people with respiratory and cardiac diseases. In long road tunnels with two-way traffic, this study indicates that ventilation fan control based on CO concentration should be adjusted for changes in vehicle CO emission and should be supplemented by air flow monitoring to limit the NO2 concentration.

Analysis and improvement measures of flight delay in China

NASA Astrophysics Data System (ADS)

Zang, Yuhang

2017-03-01

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

Nonlinear relative-proportion-based route adjustment process for day-to-day traffic dynamics: modeling, equilibrium and stability analysis

NASA Astrophysics Data System (ADS)

Zhu, Wenlong; Ma, Shoufeng; Tian, Junfang; Li, Geng

2016-11-01

Travelers' route adjustment behaviors in a congested road traffic network are acknowledged as a dynamic game process between them. Existing Proportional-Switch Adjustment Process (PSAP) models have been extensively investigated to characterize travelers' route choice behaviors; PSAP has concise structure and intuitive behavior rule. Unfortunately most of which have some limitations, i.e., the flow over adjustment problem for the discrete PSAP model, the absolute cost differences route adjustment problem, etc. This paper proposes a relative-Proportion-based Route Adjustment Process (rePRAP) maintains the advantages of PSAP and overcomes these limitations. The rePRAP describes the situation that travelers on higher cost route switch to those with lower cost at the rate that is unilaterally depended on the relative cost differences between higher cost route and its alternatives. It is verified to be consistent with the principle of the rational behavior adjustment process. The equivalence among user equilibrium, stationary path flow pattern and stationary link flow pattern is established, which can be applied to judge whether a given network traffic flow has reached UE or not by detecting the stationary or non-stationary state of link flow pattern. The stability theorem is proved by the Lyapunov function approach. A simple example is tested to demonstrate the effectiveness of the rePRAP model.

Effect of interactions between vehicles and pedestrians on fuel consumption and emissions

NASA Astrophysics Data System (ADS)

Li, Xiang; Sun, Jian-Qiao

2014-12-01

This paper presents a study of variations of fuel consumption and emissions of vehicles due to random street crossings of pedestrians. The pedestrian and vehicle movement models as well as the interaction model between the two entities are presented. Extensive numerical simulations of single and multiple cars are carried out to investigate the traffic flow rate, vehicle average speed, fuel consumption, CO, HC and NOx emissions. Generally more noncompliant road-crossings of pedestrians lead to higher level of fuel consumptions and emissions of vehicles, and the traffic situation can be improved by imposing higher vehicle speed limit to some extent. Different traffic characteristics in low and high vehicle density regions are studied. The traffic flow is more influenced by crossing pedestrians in the low vehicle density region, while in the high vehicle density region, the interactions among vehicles dominate. The main contribution of this paper lies in the qualitative analysis of the impact of the interactions between pedestrians and vehicles on the traffic, its energy economy and emissions.

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.

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.

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.

An extended lattice model accounting for traffic jerk

NASA Astrophysics Data System (ADS)

Redhu, Poonam; Siwach, Vikash

2018-02-01

In this paper, a flux difference lattice hydrodynamics model is extended by considering the traffic jerk effect which comes due to vehicular motion of non-motor automobiles. The effect of traffic jerk has been examined through linear stability analysis and shown that it can significantly enlarge the unstable region on the phase diagram. To describe the phase transition of traffic flow, mKdV equation near the critical point is derived through nonlinear stability analysis. The theoretical findings have been verified using numerical simulation which confirms that the jerk parameter plays an important role in stabilizing the traffic jam efficiently in sensing the flux difference of leading sites.

Analysis of social optimum 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

2017-03-01

This paper investigates the traffic flow dynamics under the social optimum (SO) principle in a single-entry traffic corridor with staggered shifts from the analytical and numerical perspectives. The LWR (Lighthill-Whitham and Richards) model and the Greenshield's velocity-density function are utilized to describe the dynamic properties of traffic flow. The closed-form SO solution is analytically derived and some numerical examples are used to further testify the analytical solution. The optimum proportion of the numbers of commuters with different desired arrival times is further discussed, where the analytical and numerical results both indicate that the cumulative outflow curve under the SO principle is piecewise smooth.

Inspections of Interstate Commercial Vehicles 1994

DOT National Transportation Integrated Search

1974-01-01

The objective of this effort was to complete the development of the computer simulation model SCOT (Simulation of Corridor Traffic) designed to represent traffic flow on an urban grid-freeway integrated highway system by simulating an existing system...

Characteristics of traffic flow at nonsignalized T-shaped intersection with U-turn movements.

PubMed

Fan, Hong-Qiang; Jia, Bin; Li, Xin-Gang; Tian, Jun-Fang; Yan, Xue-Dong

2013-01-01

Most nonsignalized T-shaped intersections permit U-turn movements, which make the traffic conditions of intersection complex. In this paper, a new cellular automaton (CA) model is proposed to characterize the traffic flow at the intersection of this type. In present CA model, new rules are designed to avoid the conflicts among different directional vehicles and eliminate the gridlock. Two kinds of performance measures (i.e., flux and average control delay) for intersection are compared. The impacts of U-turn movements are analyzed under different initial conditions. Simulation results demonstrate that (i) the average control delay is more practical than flux in measuring the performance of intersection, (ii) U-turn movements increase the range and degree of high congestion, and (iii) U-turn movements on the different direction of main road have asymmetrical influences on the traffic conditions of intersection.

Investigating the relationship between run-off-the-road crash frequency and traffic flow through different functional forms.

PubMed

Roque, Carlos; Cardoso, João Lourenço

2014-02-01

Crash prediction models play a major role in highway safety analysis. These models can be used for various purposes, such as predicting the number of road crashes or establishing relationships between these crashes and different covariates. However, the appropriate choice for the functional form of these models is generally not discussed in research literature on road safety. In case of run-off-the-road crashes, empirical evidence and logical considerations lead to conclusion that the relationship between expected frequency and traffic flow is not monotonously increasing. Copyright © 2013 Elsevier Ltd. All rights reserved.

Driving Parameters for Distributed and Centralized Air Transportation Architectures

NASA Technical Reports Server (NTRS)

Feron, Eric

2001-01-01

This report considers the problem of intersecting aircraft flows under decentralized conflict avoidance rules. Using an Eulerian standpoint (aircraft flow through a fixed control volume), new air traffic control models and scenarios are defined that enable the study of long-term airspace stability problems. Considering a class of two intersecting aircraft flows, it is shown that airspace stability, defined both in terms of safety and performance, is preserved under decentralized conflict resolution algorithms. Performance bounds are derived for the aircraft flow problem under different maneuver models. Besides analytical approaches, numerical examples are presented to test the theoretical results, as well as to generate some insight about the structure of the traffic flow after resolution. Considering more than two intersecting aircraft flows, simulations indicate that flow stability may not be guaranteed under simple conflict avoidance rules. Finally, a comparison is made with centralized strategies to conflict resolution.

Phase-plane analysis to an “anisotropic” higher-order traffic flow model

NASA Astrophysics Data System (ADS)

Wu, Chun-Xiu

2018-04-01

The qualitative theory of differential equations is applied to investigate the traveling wave solution to an “anisotropic” higher-order viscous traffic flow model under the Lagrange coordinate system. The types and stabilities of the equilibrium points are discussed in the phase plane. Through the numerical simulation, the overall distribution structures of trajectories are drawn to analyze the relation between the phase diagram and the selected conservative solution variables, and the influences of the parameters on the system are studied. The limit-circle, limit circle-spiral point, saddle-spiral point and saddle-nodal point solutions are obtained. These steady-state solutions provide good explanation for the phenomena of the oscillatory and homogeneous congestions in real-world traffic.

Variations in Driver Behavior: An Analysis of Car-Following Behavior Heterogeneity as a Function of Road Type and Traffic Condition

DOT National Transportation Integrated Search

2017-11-15

Microsimulation modeling is a tool used by practitioners and researchers to predict and evaluate the flow of traffic on real transportation networks. These models are used in practice to inform decisions and thus must reflect a high level of accuracy...

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.

Stability analysis and wave dynamics of an extended hybrid traffic flow model

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Zhou, Chao-Fan; Li, Wei-Kang; Yan, Bo-Wen; Jia, Bin; Wang, Ji-Xin

2018-02-01

The stability analysis and wave dynamic properties of an extended hybrid traffic flow model, WZY model, are intensively studied in this paper. The linear stable condition obtained by the linear stability analysis is presented. Besides, by means of analyzing Korteweg-de Vries equation, we present soliton waves in the metastable region. Moreover, the multiscale perturbation technique is applied to derive the traveling wave solution of the model. Furthermore, by means of performing Darboux transformation, the first-order and second-order doubly-periodic solutions and rational solutions are presented. It can be found that analytical solutions match well with numerical simulations.

Modeling merging behavior at lane drops.

DOT National Transportation Integrated Search

2015-02-01

In work-zone configurations where lane drops are present, merging of traffic at the taper presents an operational concern. In : addition, as flow through the work zone is reduced, the relative traffic safety of the work zone is also reduced. Improvin...

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

PubMed Central

2017-01-01

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

A cellular automata traffic flow model for three-phase theory

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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.

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.

Marine traffic model based on cellular automaton: Considering the change of the ship's velocity under the influence of the weather and sea

NASA Astrophysics Data System (ADS)

Qi, Le; Zheng, Zhongyi; Gang, Longhui

2017-10-01

It was found that the ships' velocity change, which is impacted by the weather and sea, e.g., wind, sea wave, sea current, tide, etc., is significant and must be considered in the marine traffic model. Therefore, a new marine traffic model based on cellular automaton (CA) was proposed in this paper. The characteristics of the ship's velocity change are taken into account in the model. First, the acceleration of a ship was divided into two components: regular component and random component. Second, the mathematical functions and statistical distribution parameters of the two components were confirmed by spectral analysis, curve fitting and auto-correlation analysis methods. Third, by combining the two components, the acceleration was regenerated in the update rules for ships' movement. To test the performance of the model, the ship traffic flows in the Dover Strait, the Changshan Channel and the Qiongzhou Strait were studied and simulated. The results show that the characteristics of ships' velocities in the simulations are consistent with the measured data by Automatic Identification System (AIS). Although the characteristics of the traffic flow in different areas are different, the velocities of ships can be simulated correctly. It proves that the velocities of ships under the influence of weather and sea can be simulated successfully using the proposed model.

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.

Network traffic behaviour near phase transition point

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-03-01

We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.

Nature of the Congested Traffic and Quasi-steady States of the General Motor Models

NASA Astrophysics Data System (ADS)

Yang, Bo; Xu, Xihua; Pang, John Z. F.; Monterola, Christopher

2015-03-01

We look at the general motor (GM) class microscopic traffic models and analyze some of the universal features of the (multi-)cluster solutions, including the emergence of an intrinsic scale and the quasisoliton dynamics. We show that the GM models can capture the essential physics of the real traffic dynamics, especially the phase transition from the free flow to the congested phase, from which the wide moving jams emerges (the F-S-J transition pioneered by B.S. Kerner). In particular, the congested phase can be associated with either the multi-cluster quasi-steady states, or their more homogeneous precursor states. In both cases the states can last for a long time, and the narrow clusters will eventually grow and merge, leading to the formation of the wide moving jams. We present a general method to fit the empirical parameters so that both quantitative and qualitative macroscopic empirical features can be reproduced with a minimal GM model. We present numerical results for the traffic dynamics both with and without the bottleneck, including various types of spontaneous and induced ``synchronized flow,'' as well as the evolution of wide moving jams. We also discuss its implications to the nature of different phases in traffic dynamics.

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.

A framework for the nationwide multimode transportation demand analysis.

DOT National Transportation Integrated Search

2010-09-01

This study attempts to analyze the impact of traffic on the US highway system considering both passenger vehicles and : trucks. For the analysis, a pseudo-dynamic traffic assignment model is proposed to estimate the time-dependent link flow : from th...

How long will the traffic flow time series keep efficacious to forecast the future?

NASA Astrophysics Data System (ADS)

Yuan, PengCheng; Lin, XuXun

2017-02-01

This paper investigate how long will the historical traffic flow time series keep efficacious to forecast the future. In this frame, we collect the traffic flow time series data with different granularity at first. Then, using the modified rescaled range analysis method, we analyze the long memory property of the traffic flow time series by computing the Hurst exponent. We calculate the long-term memory cycle and test its significance. We also compare it with the maximum Lyapunov exponent method result. Our results show that both of the freeway traffic flow time series and the ground way traffic flow time series demonstrate positively correlated trend (have long-term memory property), both of their memory cycle are about 30 h. We think this study is useful for the short-term or long-term traffic flow prediction and management.

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Investigation of pedestrian crashes on two-way two-lane rural roads in Ethiopia.

PubMed

Tulu, Getu Segni; Washington, Simon; Haque, Md Mazharul; King, Mark J

2015-05-01

Understanding pedestrian crash causes and contributing factors in developing countries is critically important as they account for about 55% of all traffic crashes. Not surprisingly, considerable attention in the literature has been paid to road traffic crash prediction models and methodologies in developing countries of late. Despite this interest, there are significant challenges confronting safety managers in developing countries. For example, in spite of the prominence of pedestrian crashes occurring on two-way two-lane rural roads, it has proven difficult to develop pedestrian crash prediction models due to a lack of both traffic and pedestrian exposure data. This general lack of available data has further hampered identification of pedestrian crash causes and subsequent estimation of pedestrian safety performance functions. The challenges are similar across developing nations, where little is known about the relationship between pedestrian crashes, traffic flow, and road environment variables on rural two-way roads, and where unique predictor variables may be needed to capture the unique crash risk circumstances. This paper describes pedestrian crash safety performance functions for two-way two-lane rural roads in Ethiopia as a function of traffic flow, pedestrian flows, and road geometry characteristics. In particular, random parameter negative binomial model was used to investigate pedestrian crashes. The models and their interpretations make important contributions to road crash analysis and prevention in developing countries. They also assist in the identification of the contributing factors to pedestrian crashes, with the intent to identify potential design and operational improvements. Copyright © 2015. Published by Elsevier Ltd.

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.

Impacts of the driver's bounded rationality on the traffic running cost under the car-following model

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Luo, Xiao-Feng; Liu, Kai

2016-09-01

The driver's bounded rationality has significant influences on the micro driving behavior and researchers proposed some traffic flow models with the driver's bounded rationality. However, little effort has been made to explore the effects of the driver's bounded rationality on the trip cost. In this paper, we use our recently proposed car-following model to study the effects of the driver's bounded rationality on his running cost and the system's total cost under three traffic running costs. The numerical results show that considering the driver's bounded rationality will enhance his each running cost and the system's total cost under the three traffic running costs.

Self-Organization in 2D Traffic Flow Model with Jam-Avoiding Drive

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

1995-04-01

A stochastic cellular automaton (CA) model is presented to investigate the traffic jam by self-organization in the two-dimensional (2D) traffic flow. The CA model is the extended version of the 2D asymmetric exclusion model to take into account jam-avoiding drive. Each site contains either a car moving to the up, a car moving to the right, or is empty. A up car can shift right with probability p ja if it is blocked ahead by other cars. It is shown that the three phases (the low-density phase, the intermediate-density phase and the high-density phase) appear in the traffic flow. The intermediate-density phase is characterized by the right moving of up cars. The jamming transition to the high-density jamming phase occurs with higher density of cars than that without jam-avoiding drive. The jamming transition point p 2c increases with the shifting probability p ja. In the deterministic limit of p ja=1, it is found that a new jamming transition occurs from the low-density synchronized-shifting phase to the high-density moving phase with increasing density of cars. In the synchronized-shifting phase, all up cars do not move to the up but shift to the right by synchronizing with the move of right cars. We show that the jam-avoiding drive has an important effect on the dynamical jamming transition.

Street Viewer: An Autonomous Vision Based Traffic Tracking System.

PubMed

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

2016-06-03

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

Air Traffic Management Research at NASA Ames

NASA Technical Reports Server (NTRS)

Davis, Thomas J.

2012-01-01

The Aviation Systems Division at the NASA Ames Research Center conducts leading edge research in air traffic management concepts and technologies. This overview will present concepts and simulation results for research in traffic flow management, safe and efficient airport surface operations, super density terminal area operations, separation assurance and system wide modeling and simulation. A brief review of the ongoing air traffic management technology demonstration (ATD-1) will also be presented. A panel discussion, with Mr. Davis serving as a panelist, on air traffic research will follow the briefing.

Reducing Traffic Congestions by Introducing CACC-Vehicles on a Multi-Lane Highway Using Agent-Based Approach

NASA Technical Reports Server (NTRS)

Arnaout, Georges M.; Bowling, Shannon R.

2011-01-01

Traffic congestion is an ongoing problem of great interest to researchers from different areas in academia. With the emerging technology for inter-vehicle communication, vehicles have the ability to exchange information with predecessors by wireless communication. In this paper, we present an agent-based model of traffic congestion and examine the impact of having CACC (Cooperative Adaptive Cruise Control) embedded vehicle(s) on a highway system consisting of 4 traffic lanes without overtaking. In our model, CACC vehicles adapt their acceleration/deceleration according to vehicle-to-vehicle inter-communication. We analyze the average speed of the cars, the shockwaves, and the evolution of traffic congestion throughout the lifecycle of the model. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce the oscillatory behavior (stop and go) resulting from the acceleration/deceleration of the vehicles.

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.

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

Understanding how roadside concentrations of NOx are influenced by the background levels, traffic density, and meteorological conditions using Boosted Regression Trees

NASA Astrophysics Data System (ADS)

Sayegh, Arwa; Tate, James E.; Ropkins, Karl

2016-02-01

Oxides of Nitrogen (NOx) is a major component of photochemical smog and its constituents are considered principal traffic-related pollutants affecting human health. This study investigates the influence of background concentrations of NOx, traffic density, and prevailing meteorological conditions on roadside concentrations of NOx at UK urban, open motorway, and motorway tunnel sites using the statistical approach Boosted Regression Trees (BRT). BRT models have been fitted using hourly concentration, traffic, and meteorological data for each site. The models predict, rank, and visualise the relationship between model variables and roadside NOx concentrations. A strong relationship between roadside NOx and monitored local background concentrations is demonstrated. Relationships between roadside NOx and other model variables have been shown to be strongly influenced by the quality and resolution of background concentrations of NOx, i.e. if it were based on monitored data or modelled prediction. The paper proposes a direct method of using site-specific fundamental diagrams for splitting traffic data into four traffic states: free-flow, busy-flow, congested, and severely congested. Using BRT models, the density of traffic (vehicles per kilometre) was observed to have a proportional influence on the concentrations of roadside NOx, with different fitted regression line slopes for the different traffic states. When other influences are conditioned out, the relationship between roadside concentrations and ambient air temperature suggests NOx concentrations reach a minimum at around 22 °C with high concentrations at low ambient air temperatures which could be associated to restricted atmospheric dispersion and/or to changes in road traffic exhaust emission characteristics at low ambient air temperatures. This paper uses BRT models to study how different critical factors, and their relative importance, influence the variation of roadside NOx concentrations. The paper highlights the importance of either setting up local background continuous monitors or improving the quality and resolution of modelled UK background maps and the need to further investigate the influence of ambient air temperature on NOx emissions and roadside NOx concentrations.

Analysis of capacity and traffic operations impacts of the World Trade Bridge in Laredo

DOT National Transportation Integrated Search

2001-07-01

Project 0-1800 pioneered the use of modern micro-simulation software to analyze the complex procedures involved in international border crossings. The animated models simulate the entire southbound commercial traffic flow, starting with U.S. Customs ...

Chaos in a dynamic model of traffic flows in an origin-destination network.

PubMed

Zhang, Xiaoyan; Jarrett, David F.

1998-06-01

In this paper we investigate the dynamic behavior of road traffic flows in an area represented by an origin-destination (O-D) network. Probably the most widely used model for estimating the distribution of O-D flows is the gravity model, [J. de D. Ortuzar and L. G. Willumsen, Modelling Transport (Wiley, New York, 1990)] which originated from an analogy with Newton's gravitational law. The conventional gravity model, however, is static. The investigation in this paper is based on a dynamic version of the gravity model proposed by Dendrinos and Sonis by modifying the conventional gravity model [D. S. Dendrinos and M. Sonis, Chaos and Social-Spatial Dynamics (Springer-Verlag, Berlin, 1990)]. The dynamic model describes the variations of O-D flows over discrete-time periods, such as each day, each week, and so on. It is shown that when the dimension of the system is one or two, the O-D flow pattern either approaches an equilibrium or oscillates. When the dimension is higher, the behavior found in the model includes equilibria, oscillations, periodic doubling, and chaos. Chaotic attractors are characterized by (positive) Liapunov exponents and fractal dimensions.(c) 1998 American Institute of Physics.

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

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.

Analyses of a heterogeneous lattice hydrodynamic model with low and high-sensitivity vehicles

NASA Astrophysics Data System (ADS)

Kaur, Ramanpreet; Sharma, Sapna

2018-06-01

Basic lattice model is extended to study the heterogeneous traffic by considering the optimal current difference effect on a unidirectional single lane highway. Heterogeneous traffic consisting of low- and high-sensitivity vehicles is modeled and their impact on stability of mixed traffic flow has been examined through linear stability analysis. The stability of flow is investigated in five distinct regions of the neutral stability diagram corresponding to the amount of higher sensitivity vehicles present on road. In order to investigate the propagating behavior of density waves non linear analysis is performed and near the critical point, the kink antikink soliton is obtained by driving mKdV equation. The effect of fraction parameter corresponding to high sensitivity vehicles is investigated and the results indicates that the stability rise up due to the fraction parameter. The theoretical findings are verified via direct numerical simulation.

Investigation of Roadway Geometric and Traffic Flow Factors for Vehicle Crashes Using Spatiotemporal Interaction

NASA Astrophysics Data System (ADS)

Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

2017-09-01

Traffic safety is a major concern in the transportation industry due to immense monetary and emotional burden caused by crashes of various severity levels, especially the injury and fatality ones. To reduce such crashes on all public roads, the safety management processes are commonly implemented which include network screening, problem diagnosis, countermeasure identification, and project prioritization. The selection of countermeasures for potential mitigation of crashes is governed by the influential factors which impact roadway crashes. Crash prediction model is the tool widely adopted by safety practitioners or researchers to link various influential factors to crash occurrences. Many different approaches have been used in the past studies to develop better fitting models which also exhibit prediction accuracy. In this study, a crash prediction model is developed to investigate the vehicular crashes occurring at roadway segments. The spatial and temporal nature of crash data is exploited to form a spatiotemporal model which accounts for the different types of heterogeneities among crash data and geometric or traffic flow variables. This study utilizes the Poisson lognormal model with random effects, which can accommodate the yearly variations in explanatory variables and the spatial correlations among segments. The dependency of different factors linked with roadway geometric, traffic flow, and road surface type on vehicular crashes occurring at segments was established as the width of lanes, posted speed limit, nature of pavement, and AADT were found to be correlated with vehicle crashes.

Modeling and simulation of driver's anticipation effect in a two lane system on curved road with slope

NASA Astrophysics Data System (ADS)

Kaur, Ramanpreet; Sharma, Sapna

2018-06-01

The complexity of traffic flow phenomena on curved road with slope is investigated and a new lattice model is presented with the addition of driver's anticipation effect for two lane system. The condition under which the free flow turns into the jammed one, is obtained theoretically by using stability analysis. The results obtained through linear analysis indicates that the stable region increases (decreases) corresponding to uphill (downhill) case due to increasing slope angle for fixed anticipation parameter. It is found that when the vehicular density becomes higher than a critical value, traffic jam appears in the form of kink antikink density waves. Analytically, the kink antikink density waves are described by the solution of mKdV equation obtained from non linear analysis. In addition, the theoretical results has been verified through numerical simulation, which confirm that the slope on a curved highway significantly influence the traffic dynamics and traffic jam can be suppressed efficiently by considering the anticipation parameter in a two lane lattice model when lane changing is allowed.

Selfish Routing

DTIC Science & Technology

2002-05-01

traffic models , thereby identifying types of networks for which the cost of routing selfishly is mild. The inefficiency inherent in an uncoordinated outcome...17 1.6 Bibliographic Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2 Preliminaries 18 2.1 The Model ...to Other Models 68 4.1 Flows at Approximate Nash Equilibrium . . . . . . . . . . . . . . . . 69 4.2 Finitely Many Users: Splittable Flow

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

NASA Astrophysics Data System (ADS)

Yan, Fei; Tian, Fuli; Shi, Zhongke

2016-10-01

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

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.

Impacts analysis of car following models considering variable vehicular gap policies

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

An electricity consumption model for electric vehicular flow

NASA Astrophysics Data System (ADS)

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

2016-09-01

In this paper, we apply the relationships between the macro and micro variables of traffic flow to develop an electricity consumption model for electric vehicular flow. We use the proposed model to study the quantitative relationships between the electricity consumption/total power and speed/density under uniform flow, and the electricity consumptions during the evolution processes of shock, rarefaction wave and small perturbation. The numerical results indicate that the proposed model can perfectly describe the electricity consumption for electric vehicular flow, which shows that the proposed model is reasonable.

Nonlinear stability of traffic models and the use of Lyapunov vectors for estimating the traffic state

NASA Astrophysics Data System (ADS)

Palatella, Luigi; Trevisan, Anna; Rambaldi, Sandro

2013-08-01

Valuable information for estimating the traffic flow is obtained with current GPS technology by monitoring position and velocity of vehicles. In this paper, we present a proof of concept study that shows how the traffic state can be estimated using only partial and noisy data by assimilating them in a dynamical model. Our approach is based on a data assimilation algorithm, developed by the authors for chaotic geophysical models, designed to be equivalent but computationally much less demanding than the traditional extended Kalman filter. Here we show that the algorithm is even more efficient if the system is not chaotic and demonstrate by numerical experiments that an accurate reconstruction of the complete traffic state can be obtained at a very low computational cost by monitoring only a small percentage of vehicles.

A new cellular automaton for signal controlled traffic flow based on driving behaviors

NASA Astrophysics Data System (ADS)

Wang, Yang; Chen, Yan-Yan

2015-03-01

The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined. Project supported by the National Basic Research Program of China (Grand No. 2012CB723303) and the Beijing Committee of Science and Technology, China (Grand No. Z1211000003120100).

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

PubMed

Kesting, Arne; Treiber, Martin; Helbing, Dirk

2010-10-13

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

Traffic protection in MPLS networks using an off-line flow optimization model

NASA Astrophysics Data System (ADS)

Krzesinski, Anthony E.; Muller, Karen E.

2002-07-01

MPLS-based recovery is intended to effect rapid and complete restoration of traffic affected by a fault in an MPLS network. Two MPLS-based recovery models have been proposed: IP re-routing which establishes recovery paths on demand, and protection switching which works with pre-established recovery paths. IP re-routing is robust and frugal since no resources are pre-committed but is inherently slower than protection switching which is intended to offer high reliability to premium services where fault recovery takes place at the 100 ms time scale. We present a model of protection switching in MPLS networks. A variant of the flow deviation method is used to find and capacitate a set of optimal label switched paths. The traffic is routed over a set of working LSPs. Global repair is implemented by reserving a set of pre-established recovery LSPs. An analytic model is used to evaluate the MPLS-based recovery mechanisms in response to bi-directional link failures. A simulation model is used to evaluate the MPLS recovery cycle in terms of the time needed to restore the traffic after a uni-directional link failure. The models are applied to evaluate the effectiveness of protection switching in networks consisting of between 20 and 100 nodes.

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.

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)

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.

Detecting Abnormal Vehicular Dynamics at Intersections Based on an Unsupervised Learning Approach and a Stochastic Model

PubMed Central

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems. PMID:22163616

Detecting abnormal vehicular dynamics at intersections based on an unsupervised learning approach and a stochastic model.

PubMed

Jiménez-Hernández, Hugo; González-Barbosa, Jose-Joel; Garcia-Ramírez, Teresa

2010-01-01

This investigation demonstrates an unsupervised approach for modeling traffic flow and detecting abnormal vehicle behaviors at intersections. In the first stage, the approach reveals and records the different states of the system. These states are the result of coding and grouping the historical motion of vehicles as long binary strings. In the second stage, using sequences of the recorded states, a stochastic graph model based on a Markovian approach is built. A behavior is labeled abnormal when current motion pattern cannot be recognized as any state of the system or a particular sequence of states cannot be parsed with the stochastic model. The approach is tested with several sequences of images acquired from a vehicular intersection where the traffic flow and duration used in connection with the traffic lights are continuously changed throughout the day. Finally, the low complexity and the flexibility of the approach make it reliable for use in real time systems.

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.

What do autonomous vehicles mean to traffic congestion and crash? : Network traffic flow modeling and simulation for autonomous vehicles.

DOT National Transportation Integrated Search

2016-01-01

Transportation infrastructure is quickly moving towards revolutionary changes to : accommodate the deployment of AVs. On the other hand, the transition to new : vehicle technologies will be shaped in large part by changes in performance of : roadway ...

Stochastic fundamental diagram for probabilistic traffic flow modeling.

DOT National Transportation Integrated Search

2011-09-01

Flowing water in river, transported gas or oil in pipe, electric current in wire, moving : goods on conveyor, molecular motors in living cell, and driving vehicles on a highway are : various kinds of flow from physical or non-physical systems, yet ea...

Traffic flow behavior at un-signalized intersection with crossings pedestrians

NASA Astrophysics Data System (ADS)

Khallouk, A.; Echab, H.; Ez-Zahraouy, H.; Lakouari, N.

2018-02-01

Mixed traffic flux composed of crossing pedestrians and vehicles extensively exists in cities. To study the characteristics of the interference traffic flux, we develop a pedestrian-vehicle cellular automata model to present the interaction behaviors on a simple cross road. By realizing the fundamental parameters (i.e. injecting rates α1, α2, the extracting rate β and the pedestrian arrival rate αP), simulations are carried out. The vehicular traffic flux is calculated in terms of rates. The effect of the crosswalk can be regarded as a dynamic impurity. The system phase diagrams in the (α1 ,αP) plane are built. It is found that the phase diagrams consist essentially of four phases namely Free Flow, Congested, Maximal Current and Gridlock. The value of the Maximal current phase depends on the extracting rate β, while the Gridlock phase is achieved only when the pedestrians generating rate is higher than a critical value. Furthermore, the effect of vehicles changing lane (Pch1 ,Pch2) and the location of the crosswalk XP on the dynamic characteristics of vehicles flow are investigated. It is found that traffic situation in the system is slightly enhanced if the location of the crosswalks XP is far from the intersection. However, when Pch1, Pch2 increase, the traffic becomes congested and the Gridlock phase enlarges.

Speed-volume relationship and headway distribution analysis of motorcycle (case study: Teuku Nyak Arief Road)

NASA Astrophysics Data System (ADS)

Prahara, E.; Prasetya, R. A.

2018-01-01

In many developing countries, transportation modes are more varied than the other country. For example, in Jakarta, Indonesia, in some roadway, motorcycle is the most dominant vehicle, with total volume is four times higher than a passenger car. Thus, the traffic characteristic in motorcycle-dominated traffic differs from a common traffic situation. The purpose of this study is to apply the concept and theory developed to analyze motorcycle behaviour under motorcycle-dominated traffic condition. The survey is applied by recording the traffic flow movement of research location at specified time period. The macroscopic characteristic analyzed in this research is a speed-flow relationship based on motorcycle equivalent unit (MCU). Furthermore, a detail microscopic characteristic analyzed that is motorcycle time headway regarding traffic flow. MCU values computed were consists of motorcycle (MC), light vehicle (LV) and heavy vehicle (HV). Those values were calculated 1.00, 6.13 and 10.71 respectively. The speed and volume relationship result is showing a linear regression model with R2 value is 0.58, it can be explained that the correlation between two variables is intermediate. The headway distribution of motorcycle is compatible with the negative exponential distribution which fitted with the proposed theory for a small vehicle such as a motorcycle.

A CFD study on the effectiveness of trees to disperse road traffic emissions at a city scale

NASA Astrophysics Data System (ADS)

Jeanjean, A. P. R.; Hinchliffe, G.; McMullan, W. A.; Monks, P. S.; Leigh, R. J.

2015-11-01

This paper focuses on the effectiveness of trees at dispersing road traffic emissions on a city scale. CFD simulations of air-pollutant concentrations were performed using the OpenFOAM software platform using the k-ε model. Results were validated against the CODASC wind tunnel database before being applied to a LIDAR database of buildings and trees representing the City of Leicester (UK). Most other CFD models in the literature typically use idealised buildings to model wind flow and pollution dispersion. However, the methodology used in this study uses real buildings and trees data from LIDAR to reconstruct a 3D representation of Leicester City Centre. It focuses on a 2 × 2 km area which is on a scale larger than those usually used in other CFD studies. Furthermore, the primary focus of this study is on the interaction of trees with wind flow dynamics. It was found that in effect, trees have a regionally beneficial impact on road traffic emissions by increasing turbulence and reducing ambient concentrations of road traffic emissions by 7% at pedestrian height on average. This was an important result given that previous studies generally concluded that trees trapped pollution by obstructing wind flow in street canyons. Therefore, this study is novel both in its methodology and subsequent results, highlighting the importance of combining local and regional scale models for assessing the impact of trees in urban planning.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

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.

Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE). Volume 1: User's guide

NASA Technical Reports Server (NTRS)

Dupnick, E.; Wiggins, D.

1980-01-01

An interactive computer program for automatically generating traffic models for the Space Transportation System (STS) is presented. Information concerning run stream construction, input data, and output data is provided. The flow of the interactive data stream is described. Error messages are specified, along with suggestions for remedial action. In addition, formats and parameter definitions for the payload data set (payload model), feasible combination file, and traffic model are documented.

Development and Evaluation of an Airborne Separation Assurance System for Autonomous Aircraft Operations

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Palmer, Michael T.; Eischeid, Todd M.

2004-01-01

NASA Langley Research Center is developing an Autonomous Operations Planner (AOP) that functions as an Airborne Separation Assurance System for autonomous flight operations. This development effort supports NASA s Distributed Air-Ground Traffic Management (DAG-TM) operational concept, designed to significantly increase capacity of the national airspace system, while maintaining safety. Autonomous aircraft pilots use the AOP to maintain traffic separation from other autonomous aircraft and managed aircraft flying under today's Instrument Flight Rules, while maintaining traffic flow management constraints assigned by Air Traffic Service Providers. AOP is designed to facilitate eventual implementation through careful modeling of its operational environment, interfaces with other aircraft systems and data links, and conformance with established flight deck conventions and human factors guidelines. AOP uses currently available or anticipated data exchanged over modeled Arinc 429 data buses and an Automatic Dependent Surveillance Broadcast 1090 MHz link. It provides pilots with conflict detection, prevention, and resolution functions and works with the Flight Management System to maintain assigned traffic flow management constraints. The AOP design has been enhanced over the course of several experiments conducted at NASA Langley and is being prepared for an upcoming Joint Air/Ground Simulation with NASA Ames Research Center.

An A-train climatology of extratropical cyclone clouds and precipitation

NASA Astrophysics Data System (ADS)

Naud, C. M.; Booth, J.; Del Genio, A. D.; van den Heever, S. C.; Posselt, D. J.

2016-12-01

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.

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.

Studies of uncontrolled air traffic patterns, phase 1

NASA Technical Reports Server (NTRS)

Baxa, E. G., Jr.; Scharf, L. L.; Ruedger, W. H.; Modi, J. A.; Wheelock, S. L.; Davis, C. M.

1975-01-01

The general aviation air traffic flow patterns at uncontrolled airports are investigated and analyzed and traffic pattern concepts are developed to minimize the midair collision hazard in uncontrolled airspace. An analytical approach to evaluate midair collision hazard probability as a function of traffic densities is established which is basically independent of path structure. Two methods of generating space-time interrelationships between terminal area aircraft are presented; one is a deterministic model to generate pseudorandom aircraft tracks, the other is a statistical model in preliminary form. Some hazard measures are presented for selected traffic densities. It is concluded that the probability of encountering a hazard should be minimized independently of any other considerations and that the number of encounters involving visible-avoidable aircraft should be maximized at the expense of encounters in other categories.

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.

A hybrid model for traffic flow and crowd dynamics with random individual properties.

PubMed

Schleper, Veronika

2015-04-01

Based on an established mathematical model for the behavior of large crowds, a new model is derived that is able to take into account the statistical variation of individual maximum walking speeds. The same model is shown to be valid also in traffic flow situations, where for instance the statistical variation of preferred maximum speeds can be considered. The model involves explicit bounds on the state variables, such that a special Riemann solver is derived that is proved to respect the state constraints. Some care is devoted to a valid construction of random initial data, necessary for the use of the new model. The article also includes a numerical method that is shown to respect the bounds on the state variables and illustrative numerical examples, explaining the properties of the new model in comparison with established models.

Green-wave control of an unbalanced two-route traffic system with signals

NASA Astrophysics Data System (ADS)

Tobita, Kazuhiro; Nagatani, Takashi

2013-11-01

We introduce the preference parameter into the two-route dynamic model proposed by Wahle et al. The parameter represents the driver’s preference for the route choice. When the driver prefers a route, the traffic flow on route A does not balance with that on route B. We study the signal control for the unbalanced two-route traffic flow at the tour-time feedback strategy where the vehicles move ahead through a series of signals. The traffic signals are controlled by both cycle time and phase shift (offset time). We find that the mean tour time can be balanced by selecting the offset time successfully. We derive the relationship between the mean tour time and offset time (phase shift). Also, the dependences of the mean density and mean current on the offset time are derived.

Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

PubMed Central

Chen, Hong; Li, Yang

2014-01-01

The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969

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.

Development of kinks in car-following models

NASA Astrophysics Data System (ADS)

Kurtze, Douglas A.

2017-03-01

Many car-following models of traffic flow admit the possibility of absolute stability, a situation in which uniform traffic flow at any spacing is linearly stable. Near the threshold of absolute stability, these models can often be reduced to a modified Korteweg-deVries (mKdV) equation plus small corrections. The hyperbolic-tangent "kink" solutions of the mKdV equation are usually of particular interest, as they represent transition zones between regions of different traffic spacings. Solvability analysis is believed to show that only a single member of the one-parameter family of kink solutions is preserved by the correction terms, and this is interpreted as a kind of selection. We show, however, that the usual solvability calculation rests on an unstated, unjustified assumption, and that without this assumption it merely gives a first-order correction to the relation between the traffic spacings far behind and far ahead of the kink, rather than any kind of "selection" criterion for the family of kink solutions. On the other hand, we display a two-parameter family of traveling wave solutions of the mKdV equation, which describe regions of one traffic spacing embedded in traffic of a different spacing; this family includes the kink solutions as a limiting case. We carry out a multiple-time-scales calculation and find conditions under which the inclusions decay, conditions that lead to a selected inclusion, and conditions for which the inclusion evolves into a pair of kinks.

Integrating internet GPS vehicle tracking data into a bottom-up vehicular emissions inventory and atmospheric simulation in South-East, Brazil

NASA Astrophysics Data System (ADS)

Ibarra Espinosa, S.; Ynoue, R.; Giannotti, M., , Dr

2017-12-01

It has been shown the importance of emissions inventories for air quality studies and environmental planning at local, regional (REAS), hemispheric (CLRTAP) and global (IPCC) scales. It has been shown also that vehicules are becoming the most important sources in urban centers. Several efforts has been made in order to model vehicular emissions to obtain more accurate emission factors based on Vehicular Specific Power (VPS) with IVE and MOVES based on VSP, MOBILE, VERSIT and COPERT based on average speed, or ARTEMIS and HBEFA based on traffic situations. However, little effort has been made to improve traffic activity data. In this study we are proposing using a novel approach to develop vehicular emissions inventory including point data from MAPLINK a company that feeds with traffic data to Google. This includes working and transforming massive amount of data to generate traffic flow and speeds. The region of study is the south east of Brazil including São Paulo metropolitan areas. To estimate vehicular emissions we are using the open source model VEIN available at https://CRAN.R-project.org/package=vein. We generated hourly traffic between 2010-04-21 and 2010-10-22, totalizing 145 hours. This data consists GPS readings from vehicles with assurance policy, applications and other sources. This type data presents spacial bias meaning that only a part of the vehicles are tracked. We corrected this bias using the calculated speed as proxy of traffic flow using measurements of traffic flow and speed per lane made in São Paulo. Then we calibrated the total traffic estimating Fuel Consumption with VEIN and comparing Fuel Sales for the region. We estimated the hourly vehicular emissions and produced emission maps and data-bases. In addition, we simulated atmospheric simulations using WRF-Chem to identify which inventory produces better agreement with air pollutant observations. New technologies and big data provides opportunities to improve vehicular emissions inventories.

INTEGRATED SPEED ESTIMATION MODEL FOR MULTILANE EXPREESSWAYS

NASA Astrophysics Data System (ADS)

Hong, Sungjoon; Oguchi, Takashi

In this paper, an integrated speed-estimation model is developed based on empirical analyses for the basic sections of intercity multilane expressway un der the uncongested condition. This model enables a speed estimation for each lane at any site under arb itrary highway-alignment, traffic (traffic flow and truck percentage), and rainfall conditions. By combin ing this model and a lane-use model which estimates traffic distribution on the lanes by each vehicle type, it is also possible to es timate an average speed across all the lanes of one direction from a traffic demand by vehicle type under specific highway-alignment and rainfall conditions. This model is exp ected to be a tool for the evaluation of traffic performance for expressways when the performance me asure is travel speed, which is necessary for Performance-Oriented Highway Planning and Design. Regarding the highway-alignment condition, two new estimators, called effective horizo ntal curvature and effective vertical grade, are proposed in this paper which take into account the influence of upstream and downstream alignment conditions. They are applied to the speed-estimation model, and it shows increased accuracy of the estimation.

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.

A New Interpretation of Effects of the Probabilistic Delayed Start on the One-Dimensional Traffic Flow

NASA Astrophysics Data System (ADS)

Ishibashi, Yoshihiro; Fukui, Minoru

2018-03-01

The effect of the probabilistic delayed start on the one-dimensional traffic flow is investigated on the basis of several models. Analogy with the degeneracy of the states and its resolution, as well as that with the mathematical procedures adopted for them, is utilized. The perturbation is assumed to be proportional to the probability of the delayed start, and the perturbation function is determined so that imposed conditions are fulfilled. The obtained formulas coincide with those previously derived on the basis of the mean-field analyses of the Nagel-Schreckenberg and Fukui-Ishibashi models, and reproduce the cellular automaton simulation results.

Non-lane-discipline-based car-following model under honk environment

NASA Astrophysics Data System (ADS)

Rong, Ying; Wen, Huiying

2018-04-01

This study proposed a non-lane-discipline-based car-following model by synthetically considering the visual angles and the timid/aggressive characteristics of drivers under honk environment. We firstly derived the neutral stability condition by the linear stability theory. It showed that the parameters related to visual angles and driving characteristics of drivers under honk environment all have significant impact on the stability of non-lane-discipline traffic flow. For better understanding the inner mechanism among these factors, we further analyzed how each parameter affects the traffic flow and gained further insight into how the visual angles information influences other parameters and then influences the non-lane-discipline traffic flow under honk environment. And the results showed that the other aspects such as driving characteristics of drivers or honk effect are all interacted with the "Visual-Angle Factor". And the effect of visual angle is not just to say simply it has larger stable region or not as the existing studies. Finally, to verify the proposed model, we carried out the numerical simulation under the periodic boundary condition. And the results of numerical simulation are agreed well with the theoretical findings.

Impact of Rainfall on Multilane Roundabout Flowrate Contraction

NASA Astrophysics Data System (ADS)

PARKSHIR, Amir; BEN-EDIGBE, Johnnie

2017-08-01

In this study, roundabouts at two sites in the Malaysia were investigated under rainy and dry weather conditions. Two automatic traffic counters per roundabout arm as well as two rain gauge stations were used to collect data at each surveyed site. Nearly one million vehicles were investigated at four sites. Vehicle volume, speeds and headways for entry and circulating flows were collected continuously at each roundabout about arm for six weeks between November 2013 and January 2014. Empirical regression technique and gap-acceptance models were modified and used to analyze roundabout capacity. Good fits to the data were obtained; the results also fit models developed in other countries. It was assumed that entry capacity depends on the geometric characteristics of the roundabout, particularly the diameter of the outside circle of the intersection. It was also postulated that geometric characteristics determine the speed of vehicles around the central island and, therefore, have an impact on the gap-acceptance process and consequently the capacity. Only off-peak traffic data per light, moderate or heavy rainfall were analysed. Peak traffic data were not used because of the presence of peak traffic flow. Passenger car equivalent values being an instrument of conversion from traffic volume to flow were modified. Results show that, average entry capacity loss is about 22.6% under light rainfall, about 18.1% under moderate rainfall and about 5.6% under heavy rainfall. Significant entry capacity loss would result from rainfall irrespective of their intensity. It can be postulated that entry capacity loss under heavy rainfall is lowest because the advantage enjoyed by circulating flow would be greatly reduced with increased rainfall intensity. The paper concluded that rainfall has significant impact of flowrate contraction at roundabouts.

Distributed and Centralized Conflict Management Under Traffic Flow Management Constraints

NASA Technical Reports Server (NTRS)

Feron, Eric; Bilimoria, Karl (Technical Monitor)

2001-01-01

The past year's activity has concentrated on the following two activities: (1) Refining and completing our study on the stability of interacting flows of aircraft when they have to resolve conflicts in a decentralized and sequential manner. More specifically, it was felt that some of the modeling assumptions made during previous research (such offset maneuvering models) could be improved to include more realistic models such as heading changes when analyzing interacting flow stability problems. We extended our analysis to achieve this goal. The results of this study have been submitted for presentation at the 2002 American Control Conference; (2) Examining the issues associated with delay propagation across multiple enroute sectors. This study was initiated at NASA in cooperation with Dr. Karl Bilimoria. Considering a set of adjacent sectors, this ongoing study concentrates on the effect of various traffic flow management strategies on the propagation of delays and congestion across sectors. The problem description and findings so far are reported in the attached working paper "Enroute sector buffering capacity."

A quantum mechanics-based approach to model incident-induced dynamic driver behavior

NASA Astrophysics Data System (ADS)

Sheu, Jiuh-Biing

2008-08-01

A better understanding of the psychological factors influencing drivers, and the resulting driving behavior responding to incident-induced lane traffic phenomena while passing by an incident site is vital to the improvement of road safety. This paper presents a microscopic driver behavior model to explain the dynamics of the instantaneous driver decision process under lane-blocking incidents on adjacent lanes. The proposed conceptual framework decomposes the corresponding driver decision process into three sequential phases: (1) initial stimulus, (2) glancing-around car-following, and (3) incident-induced driving behavior. The theorem of quantum mechanics in optical flows is applied in the first phase to explain the motion-related perceptual phenomena while vehicles approach the incident site in adjacent lanes, followed by the incorporation of the effect of quantum optical flows in modeling the induced glancing-around car-following behavior in the second phase. Then, an incident-induced driving behavior model is formulated to reproduce the dynamics of driver behavior conducted in the process of passing by an incident site in the adjacent lanes. Numerical results of model tests using video-based incident data indicate the validity of the proposed traffic behavior model in analyzing the incident-induced lane traffic phenomena. It is also expected that such a proposed quantum-mechanics based methodology can throw more light if applied to driver psychology and response in anomalous traffic environments in order to improve road safety.

Full velocity difference model for a car-following theory.

PubMed

Jiang, R; Wu, Q; Zhu, Z

2001-07-01

In this paper, we present a full velocity difference model for a car-following theory based on the previous models in the literature. To our knowledge, the model is an improvement over the previous ones theoretically, because it considers more aspects in car-following process than others. This point is verified by numerical simulation. Then we investigate the property of the model using both analytic and numerical methods, and find that the model can describe the phase transition of traffic flow and estimate the evolution of traffic congestion.

Glass-like dynamics in confined and congested ant traffic.

PubMed

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

2015-09-07

The collective movement of animal groups often occurs in confined spaces. As animal groups are challenged to move at high density, their mobility dynamics may resemble the flow of densely packed non-living soft materials such as colloids, grains, or polymers. However, unlike inert soft-materials, self-propelled collective living systems often display social interactions whose influence on collective mobility are only now being explored. In this paper, we study the mobility of bi-directional traffic flow in a social insect (the fire ant Solenopsis invicta) as we vary the diameter of confining foraging tunnels. In all tunnel diameters, we observe the emergence of spatially heterogeneous regions of fast and slow traffic that are induced through two phenomena: physical obstruction, arising from the inability of individual ants to interpenetrate, and time-delay resulting from social interaction in which ants stop to briefly antennate. Density correlation functions reveal that the relaxation dynamics of high density traffic fluctuations scale linearly with fluctuation size and are sensitive to tunnel diameter. We separate the roles of physical obstruction and social interactions in traffic flow using cellular automata based simulation. Social interaction between ants is modeled as a dwell time (Tint) over which interacting ants remain stationary in the tunnel. Investigation over a range of densities and Tint reveals that the slowing dynamics of collective motion in social living systems are consistent with dynamics near a fragile glass transition in inert soft-matter systems. In particular, flow is relatively insensitive to density until a critical density is reached. As social interaction affinity is increased (increasing Tint) traffic dynamics change and resemble a strong glass transition. Thus, social interactions play an important role in the mobility of collective living systems at high density. Our experiments and model demonstrate that the concepts of soft-matter physics aid understanding of the mobility of collective living systems, and motivate further inquiry into the dynamics of densely confined social living systems.

Three-dimensional modeling of air flow and pollutant dispersion in an urban street canyon with thermal effects.

PubMed

Tsai, Mong-Yu; Chen, Kang-Shin; Wu, Chung-Hsing

2005-08-01

Effects of excess ground and building temperatures on airflow and dispersion of pollutants in an urban street canyon with an aspect ratio of 0.8 and a length-to-width ratio of 3 were investigated numerically. Three-dimensional governing equations of mass, momentum, energy, and species were modeled using the RNG k-epsilon turbulence model and Boussinesq approximation, which were solved using the finite volume method. Vehicle emissions were estimated from the measured traffic flow rates and modeled as banded line sources, with a street length and bandwidths equal to typical vehicle widths. Both measurements and simulations reveal that pollutant concentrations typically follow the traffic flow rate; they decline as the height increases and are higher on the leeward side than on the windward side. Three-dimensional simulations reveal that the vortex line, joining the centers of cross-sectional vortexes of the street canyon, meanders between street buildings and shifts toward the windward side when heating strength is increased. Thermal boundary layers are very thin. Entrainment of outside air increases, and pollutant concentration decreases with increasing heating condition. Also, traffic-produced turbulence enhances the turbulent kinetic energy and the mixing of temperature and admixtures in the canyon. Factors affecting the inaccuracy of the simulations are addressed.

Multi-agent systems design for aerospace applications

NASA Astrophysics Data System (ADS)

Waslander, Steven L.

2007-12-01

Engineering systems with independent decision makers are becoming increasingly prevalent and present many challenges in coordinating actions to achieve systems goals. In particular, this work investigates the applications of air traffic flow control and autonomous vehicles as motivation to define algorithms that allow agents to agree to safe, efficient and equitable solutions in a distributed manner. To ensure system requirements will be satisfied in practice, each method is evaluated for a specific model of agent behavior, be it cooperative or non-cooperative. The air traffic flow control problem is investigated from the point of view of the airlines, whose costs are directly affected by resource allocation decisions made by the Federal Aviation Administration in order to mitigate traffic disruptions caused by weather. Airlines are first modeled as cooperative, and a distributed algorithm is presented with various global cost metrics which balance efficient and equitable use of resources differently. Next, a competitive airline model is assumed and two market mechanisms are developed for allocating contested airspace resources. The resource market mechanism provides a solution for which convergence to an efficient solution can be guaranteed, and each airline will improve on the solution that would occur without its inclusion in the decision process. A lump-sum market is then introduced as an alternative mechanism, for which efficiency loss bounds exist if airlines attempt to manipulate prices. Initial convergence results for lump-sum markets are presented for simplified problems with a single resource. To validate these algorithms, two air traffic flow models are developed which extend previous techniques, the first a convenient convex model made possible by assuming constant velocity flow, and the second a more complex flow model with full inflow, velocity and rerouting control. Autonomous vehicle teams are envisaged for many applications including mobile sensing and search and rescue. To enable these high-level applications, multi-vehicle collision avoidance is solved using a cooperative, decentralized algorithm. For the development of coordination algorithms for autonomous vehicles, the Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC) is presented. This testbed provides significant advantages over other aerial testbeds due to its small size and low maintenance requirements.

Temporal variation of traffic on highways and the development of accurate temporal allocation factors for air pollution analyses

NASA Astrophysics Data System (ADS)

Batterman, Stuart; Cook, Richard; Justin, Thomas

2015-04-01

Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates.

Temporal variation of traffic on highways and the development of accurate temporal allocation factors for air pollution analyses

PubMed Central

Batterman, Stuart; Cook, Richard; Justin, Thomas

2015-01-01

Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates. PMID:25844042

Modeling and analyses for an extended car-following model accounting for drivers' situation awareness from cyber physical perspective

NASA Astrophysics Data System (ADS)

Chen, Dong; Sun, Dihua; Zhao, Min; Zhou, Tong; Cheng, Senlin

2018-07-01

In fact, driving process is a typical cyber physical process which couples tightly the cyber factor of traffic information with the physical components of the vehicles. Meanwhile, the drivers have situation awareness in driving process, which is not only ascribed to the current traffic states, but also extrapolates the changing trend. In this paper, an extended car-following model is proposed to account for drivers' situation awareness. The stability criterion of the proposed model is derived via linear stability analysis. The results show that the stable region of proposed model will be enlarged on the phase diagram compared with previous models. By employing the reductive perturbation method, the modified Korteweg de Vries (mKdV) equation is obtained. The kink-antikink soliton of mKdV equation reveals theoretically the evolution of traffic jams. Numerical simulations are conducted to verify the analytical results. Two typical traffic Scenarios are investigated. The simulation results demonstrate that drivers' situation awareness plays a key role in traffic flow oscillations and the congestion transition.

Health risk represented by inhaling polycyclic aromatic hydrocarbons (PAH) during daily commuting involving using a high traffic flow route in Bogotá.

PubMed

Pachón, Jorge E; Sarmiento, Hugo; Hoshiko, Tomomi

2013-01-01

Assessing the risk to health by inhaling particles and particle-bound PAH during daily commuting along a high traffic flow route/corridor in Bogotá. A van was equipped with a PAS2000 photo-electric sensor for real-time measurement of particle-bound PAH and a Dust Trakfor monitoring PM10 concentration; it drove along typical commuting routes in the city. Exposure to particles and particle-bound PAH was assessed by using an inhalation intake model. A similar trend was observed for both PM10 and PAH concentration, indicating that traffic was the same source for both contaminants. Extreme PM10 and PAH inhalation concentrations were recorded every time direct bus and microbus emissions were measured by the van. Inhalation model results indicated that exposure was significantly greater when using a venues having mixed traffic use (i.e. buses, microbuses, passenger vehicles, motorcycles) compared to using roads where the TransMilenio system (articulated buses) had been implemented. The results may support evaluating bus drivers, commuters and bike users' exposure to toxic compounds in the city.

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...

Bifurcation analysis of a heterogeneous traffic flow model

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Yan, Bo-Wen; Zhou, Chao-Fan; Li, Wei-Kang; Jia, Bin

2018-03-01

In this work, a heterogeneous traffic flow model coupled with the periodic boundary condition is proposed. Based on the previous models, a heterogeneous system composed of more than one kind of vehicles is considered. By bifurcation analysis, bifurcation patterns of the heterogeneous system are discussed in three situations in detail and illustrated by diagrams of bifurcation patterns. Besides, the stability analysis of the heterogeneous system is performed to test its anti-interference ability. The relationship between the number of vehicles and the stability is obtained. Furthermore, the attractor analysis is applied to investigate the nature of the heterogeneous system near its steady-state neighborhood. Phase diagrams of the process of the heterogeneous system from initial state to equilibrium state are intuitively presented.

Competition between Local Collisions and Collective Hydrodynamic Feedback Controls Traffic Flows in Microfluidic Networks

NASA Astrophysics Data System (ADS)

Belloul, M.; Engl, W.; Colin, A.; Panizza, P.; Ajdari, A.

2009-05-01

By studying the repartition of monodisperse droplets at a simple T junction, we show that the traffic of discrete fluid systems in microfluidic networks results from two competing mechanisms, whose significance is driven by confinement. Traffic is dominated by collisions occurring at the junction for small droplets and by collective hydrodynamic feedback for large ones. For each mechanism, we present simple models in terms of the pertinent dimensionless parameters of the problem.

Achieving QoS for TCP Traffic in Satellite Networks with Differentiated Services

NASA Technical Reports Server (NTRS)

Durresi, Arjan; Kota, Sastri; Goyal, Mukul; Jain, Raj; Bharani, Venkata

2001-01-01

Satellite networks play an indispensable role in providing global Internet access and electronic connectivity. To achieve such a global communications, provisioning of quality of service (QoS) within the advanced satellite systems is the main requirement. One of the key mechanisms of implementing the quality of service is traffic management. Traffic management becomes a crucial factor in the case of satellite network because of the limited availability of their resources. Currently, Internet Protocol (IP) only has minimal traffic management capabilities and provides best effort services. In this paper, we presented a broadband satellite network QoS model and simulated performance results. In particular, we discussed the TCP flow aggregates performance for their good behavior in the presence of competing UDP flow aggregates in the same assured forwarding. We identified several factors that affect the performance in the mixed environments and quantified their effects using a full factorial design of experiment methodology.

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...

Effective flow resistivity of highway pavements.

PubMed

Rochat, Judith L; Read, David R

2013-12-01

In the case of highway traffic noise, propagating sound is influenced by the ground over which it travels, whether it is the pavement itself or the ground between the highway and nearby communities. Properly accounting for ground type in modeling can increase accuracy in noise impact determinations and noise abatement design. Pavement-specific effective flow resistivity values are being investigated for inclusion in the Federal Highway Administration Traffic Noise Model, which uses these values in the sound propagation algorithms and currently applies a single effective flow resistivity value to all pavement. Pavement-specific effective flow resistivity values were obtained by applying a modified version of the American National Standards Institute S1.18 standard. The data analysis process was tailored to allow for increased sensitivity and extraction of effective flow resistivity values for a broad range of pavements (sound absorptive to reflective). For porous pavements (sound absorptive), it was determined that examination of the measured data can reveal influence from an underlying structure. Use of such techniques can aid in the design of quieter pavements.

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao Xun; Sridhar, Banavar

2013-01-01

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

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

PubMed

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

2014-04-01

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

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.

An improved car-following model from the perspective of driver’s forecast behavior

NASA Astrophysics Data System (ADS)

Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

In this paper, a new car-following model considering effect of the driver’s forecast behavior is proposed based on the full velocity difference model (FVDM). Using the new model, we investigate the starting process of the vehicle motion under a traffic signal and find that the delay time of vehicle motion is reduced. Then the stability condition of the new model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Numerical simulation is compatible with the analysis of theory such as density wave, hysteresis loop, which shows that the new model is reasonable. The results show that considering the effect of driver’s forecast behavior can help to enhance the stability of traffic flow.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Self-Organized Criticality and Scaling in Lifetime of Traffic Jams

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

1995-01-01

The deterministic cellular automaton 184 (the one-dimensional asymmetric simple-exclusion model with parallel dynamics) is extended to take into account injection or extraction of particles. The model presents the traffic flow on a highway with inflow or outflow of cars.Introducing injection or extraction of particles into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. The typical lifetime of traffic jams scales as \\cong Lν with ν=0.65±0.04. It is shown that the cumulative distribution Nm (L) of lifetimes satisfies the finite-size scaling form Nm (L) \\cong L-1 f(m/Lν).

Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE). Volume 3: The GREEDY algorithm

NASA Technical Reports Server (NTRS)

Dupnick, E.; Wiggins, D.

1980-01-01

The functional specifications, functional design and flow, and the program logic of the GREEDY computer program are described. The GREEDY program is a submodule of the Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE) program and has been designed as a continuation of the shuttle Mission Payloads (MPLS) program. The MPLS uses input payload data to form a set of feasible payload combinations; from these, GREEDY selects a subset of combinations (a traffic model) so all payloads can be included without redundancy. The program also provides the user a tutorial option so that he can choose an alternate traffic model in case a particular traffic model is unacceptable.

A Minimax Network Flow Model for Characterizing the Impact of Slot Restrictions

NASA Technical Reports Server (NTRS)

Lee, Douglas W.; Patek, Stephen D.; Alexandrov, Natalia; Bass, Ellen J.; Kincaid, Rex K.

2010-01-01

This paper proposes a model for evaluating long-term measures to reduce congestion at airports in the National Airspace System (NAS). This model is constructed with the goal of assessing the global impacts of congestion management strategies, specifically slot restrictions. We develop the Minimax Node Throughput Problem (MINNTHRU), a multicommodity network flow model that provides insight into air traffic patterns when one minimizes the worst-case operation across all airports in a given network. MINNTHRU is thus formulated as a model where congestion arises from network topology. It reflects not market-driven airline objectives, but those of a regulatory authority seeking a distribution of air traffic beneficial to all airports, in response to congestion management measures. After discussing an algorithm for solving MINNTHRU for moderate-sized (30 nodes) and larger networks, we use this model to study the impacts of slot restrictions on the operation of an entire hub-spoke airport network. For both a small example network and a medium-sized network based on 30 airports in the NAS, we use MINNTHRU to demonstrate that increasing the severity of slot restrictions increases the traffic around unconstrained hub airports as well as the worst-case level of operation over all airports.

Linear stability and nonlinear analyses of traffic waves for the general nonlinear car-following model with multi-time delays

NASA Astrophysics Data System (ADS)

Sun, Dihua; Chen, Dong; Zhao, Min; Liu, Weining; Zheng, Linjiang

2018-07-01

In this paper, the general nonlinear car-following model with multi-time delays is investigated in order to describe the reactions of vehicle to driving behavior. Platoon stability and string stability criteria are obtained for the general nonlinear car-following model. Burgers equation and Korteweg de Vries (KdV) equation and their solitary wave solutions are derived adopting the reductive perturbation method. We investigate the properties of typical optimal velocity model using both analytic and numerical methods, which estimates the impact of delays about the evolution of traffic congestion. The numerical results show that time delays in sensing relative movement is more sensitive to the stability of traffic flow than time delays in sensing host motion.

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.

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

PubMed

Morley, David W; Gulliver, John

2016-09-01

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

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.

Mechanisms of jamming in the Nagel-Schreckenberg model for traffic flow.

PubMed

Bette, Henrik M; Habel, Lars; Emig, Thorsten; Schreckenberg, Michael

2017-01-01

We study the Nagel-Schreckenberg cellular automata model for traffic flow by both simulations and analytical techniques. To better understand the nature of the jamming transition, we analyze the fraction of stopped cars P(v=0) as a function of the mean car density. We present a simple argument that yields an estimate for the free density where jamming occurs, and show satisfying agreement with simulation results. We demonstrate that the fraction of jammed cars P(v∈{0,1}) can be decomposed into the three factors (jamming rate, jam lifetime, and jam size) for which we derive, from random walk arguments, exponents that control their scaling close to the critical density.

Mechanisms of jamming in the Nagel-Schreckenberg model for traffic flow

NASA Astrophysics Data System (ADS)

Bette, Henrik M.; Habel, Lars; Emig, Thorsten; Schreckenberg, Michael

2017-01-01

We study the Nagel-Schreckenberg cellular automata model for traffic flow by both simulations and analytical techniques. To better understand the nature of the jamming transition, we analyze the fraction of stopped cars P (v =0 ) as a function of the mean car density. We present a simple argument that yields an estimate for the free density where jamming occurs, and show satisfying agreement with simulation results. We demonstrate that the fraction of jammed cars P (v ∈{0 ,1 }) can be decomposed into the three factors (jamming rate, jam lifetime, and jam size) for which we derive, from random walk arguments, exponents that control their scaling close to the critical density.

Characteristics of traffic flow at a non-signalized intersection in the framework of game theory

NASA Astrophysics Data System (ADS)

Fan, Hongqiang; Jia, Bin; Tian, Junfang; Yun, Lifen

2014-12-01

At a non-signalized intersection, some vehicles violate the traffic rules to pass the intersection as soon as possible. These behaviors may cause many traffic conflicts even traffic accidents. In this paper, a simulation model is proposed to research the effects of these behaviors at a non-signalized intersection. Vehicle’s movement is simulated by the cellular automaton (CA) model. The game theory is introduced for simulating the intersection dynamics. Two types of driver participate the game process: cooperator (C) and defector (D). The cooperator obey the traffic rules, but the defector does not. A transition process may occur when the cooperator is waiting before the intersection. The critical value of waiting time follows the Weibull distribution. One transition regime is found in the phase diagram. The simulation results illustrate the applicability of the proposed model and reveal a number of interesting insights into the intersection management, including that the existence of defectors is benefit for the capacity of intersection, but also reduce the safety of intersection.

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.

Phase transition of a new lattice hydrodynamic model with consideration of on-ramp and off-ramp

NASA Astrophysics Data System (ADS)

Zhang, Geng; Sun, Di-hua; Zhao, Min

2018-01-01

A new traffic lattice hydrodynamic model with consideration of on-ramp and off-ramp is proposed in this paper. The influence of on-ramp and off-ramp on the stability of the main road is uncovered by theoretical analysis and computer simulation. Through linear stability theory, the neutral stability condition of the new model is obtained and the results show that the unstable region in the phase diagram is enlarged by considering the on-ramp effect but shrunk with consideration of the off-ramp effect. The mKdV equation near the critical point is derived via nonlinear reductive perturbation method and the occurrence of traffic jamming transition can be described by the kink-antikink soliton solution of the mKdV equation. From the simulation results of space-time evolution of traffic density waves, it is shown that the on-ramp can worsen the traffic stability of the main road but off-ramp is positive in stabilizing the traffic flow of the main road.

Order-parameter model for unstable multilane traffic flow

NASA Astrophysics Data System (ADS)

Lubashevsky, Ihor A.; Mahnke, Reinhard

2000-11-01

We discuss a phenomenological approach to the description of unstable vehicle motion on multilane highways that explains in a simple way the observed sequence of the ``free flow <--> synchronized mode <--> jam'' phase transitions as well as the hysteresis in these transitions. We introduce a variable called an order parameter that accounts for possible correlations in the vehicle motion at different lanes. So, it is principally due to the ``many-body'' effects in the car interaction in contrast to such variables as the mean car density and velocity being actually the zeroth and first moments of the ``one-particle'' distribution function. Therefore, we regard the order parameter as an additional independent state variable of traffic flow. We assume that these correlations are due to a small group of ``fast'' drivers and by taking into account the general properties of the driver behavior we formulate a governing equation for the order parameter. In this context we analyze the instability of homogeneous traffic flow that manifested itself in the above-mentioned phase transitions and gave rise to the hysteresis in both of them. Besides, the jam is characterized by the vehicle flows at different lanes which are independent of one another. We specify a certain simplified model in order to study the general features of the car cluster self-formation under the ``free flow <--> synchronized motion'' phase transition. In particular, we show that the main local parameters of the developed cluster are determined by the state characteristics of vehicle motion only.

An optimization model for the US Air-Traffic System

NASA Technical Reports Server (NTRS)

Mulvey, J. M.

1986-01-01

A systematic approach for monitoring U.S. air traffic was developed in the context of system-wide planning and control. Towards this end, a network optimization model with nonlinear objectives was chosen as the central element in the planning/control system. The network representation was selected because: (1) it provides a comprehensive structure for depicting essential aspects of the air traffic system, (2) it can be solved efficiently for large scale problems, and (3) the design can be easily communicated to non-technical users through computer graphics. Briefly, the network planning models consider the flow of traffic through a graph as the basic structure. Nodes depict locations and time periods for either individual planes or for aggregated groups of airplanes. Arcs define variables as actual airplanes flying through space or as delays across time periods. As such, a special case of the network can be used to model the so called flow control problem. Due to the large number of interacting variables and the difficulty in subdividing the problem into relatively independent subproblems, an integrated model was designed which will depict the entire high level (above 29000 feet) jet route system for the 48 contiguous states in the U.S. As a first step in demonstrating the concept's feasibility a nonlinear risk/cost model was developed for the Indianapolis Airspace. The nonlinear network program --NLPNETG-- was employed in solving the resulting test cases. This optimization program uses the Truncated-Newton method (quadratic approximation) for determining the search direction at each iteration in the nonlinear algorithm. It was shown that aircraft could be re-routed in an optimal fashion whenever traffic congestion increased beyond an acceptable level, as measured by the nonlinear risk function.

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)

[Estimation of average traffic emission factor based on synchronized incremental traffic flow and air pollutant concentration].

PubMed

Li, Run-Kui; Zhao, Tong; Li, Zhi-Peng; Ding, Wen-Jun; Cui, Xiao-Yong; Xu, Qun; Song, Xian-Feng

2014-04-01

On-road vehicle emissions have become the main source of urban air pollution and attracted broad attentions. Vehicle emission factor is a basic parameter to reflect the status of vehicle emissions, but the measured emission factor is difficult to obtain, and the simulated emission factor is not localized in China. Based on the synchronized increments of traffic flow and concentration of air pollutants in the morning rush hour period, while meteorological condition and background air pollution concentration retain relatively stable, the relationship between the increase of traffic and the increase of air pollution concentration close to a road is established. Infinite line source Gaussian dispersion model was transformed for the inversion of average vehicle emission factors. A case study was conducted on a main road in Beijing. Traffic flow, meteorological data and carbon monoxide (CO) concentration were collected to estimate average vehicle emission factors of CO. The results were compared with simulated emission factors of COPERT4 model. Results showed that the average emission factors estimated by the proposed approach and COPERT4 in August were 2.0 g x km(-1) and 1.2 g x km(-1), respectively, and in December were 5.5 g x km(-1) and 5.2 g x km(-1), respectively. The emission factors from the proposed approach and COPERT4 showed close values and similar seasonal trends. The proposed method for average emission factor estimation eliminates the disturbance of background concentrations and potentially provides real-time access to vehicle fleet emission factors.

Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...

EPA Pesticide Factsheets

With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th

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

The importance of antipersistence for traffic jams

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Microscopic Statistical Characterisation of the Congested Traffic Flow and Some Salient Empirical Features

NASA Astrophysics Data System (ADS)

Yang, Bo; Yoon, Ji Wei; Monterola, Christopher

We present large scale, detailed analysis of the microscopic empirical data of the congested traffic flow, focusing on the non-linear interactions between the components of the many-body traffic system. By implementing a systematic procedure that averages over relatively unimportant factors, we extract the effective dependence of the acceleration on the gap between the vehicles, velocity and relative velocity. Such relationship is characterised not just by a few vehicles but the traffic system as a whole. Several interesting features of the detailed vehicle-to-vehicle interactions are revealed, including the stochastic distribution of the human responses, relative importance of the non-linear terms in different density regimes, symmetric response to the relative velocity, and the insensitivity of the acceleration to the velocity within a certain gap and velocity range. The latter leads to a multitude of steady-states without a fundamental diagram. The empirically constructed functional dependence of the acceleration on the important dynamical quantities not only gives the detailed collective driving behaviours of the traffic system, it also serves as the fundamental reference for the validations of the deterministic and stochastic microscopic traffic models in the literature.

Estimation and prediction of origin-destination matrices for I-66.

DOT National Transportation Integrated Search

2011-09-01

This project uses the Box-Jenkins time-series technique to model and forecast the traffic flows and then : uses the flow forecasts to predict the origin-destination matrices. First, a detailed analysis was conducted : to investigate the best data cor...

Interrupted flow reference energy mean emission levels for the FHWA Traffic Noise Model

DOT National Transportation Integrated Search

1997-01-01

This report presents the measurement, data reduction and analysis of individual vehicle sound level and speed data for non-constant speed situations. These situations are referred to as interrupted flow conditions and include acceleration from stop s...

A lattice hydrodynamic model based on delayed feedback control considering the effect of flow rate difference

NASA Astrophysics Data System (ADS)

Wang, Yunong; Cheng, Rongjun; Ge, Hongxia

2017-08-01

In this paper, a lattice hydrodynamic model is derived considering not only the effect of flow rate difference but also the delayed feedback control signal which including more comprehensive information. The control method is used to analyze the stability of the model. Furthermore, the critical condition for the linear steady traffic flow is deduced and the numerical simulation is carried out to investigate the advantage of the proposed model with and without the effect of flow rate difference and the control signal. The results are consistent with the theoretical analysis correspondingly.

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.

Dynamics of functional failures and recovery in complex road networks

NASA Astrophysics Data System (ADS)

Zhan, Xianyuan; Ukkusuri, Satish V.; Rao, P. Suresh C.

2017-11-01

We propose a new framework for modeling the evolution of functional failures and recoveries in complex networks, with traffic congestion on road networks as the case study. Differently from conventional approaches, we transform the evolution of functional states into an equivalent dynamic structural process: dual-vertex splitting and coalescing embedded within the original network structure. The proposed model successfully explains traffic congestion and recovery patterns at the city scale based on high-resolution data from two megacities. Numerical analysis shows that certain network structural attributes can amplify or suppress cascading functional failures. Our approach represents a new general framework to model functional failures and recoveries in flow-based networks and allows understanding of the interplay between structure and function for flow-induced failure propagation and recovery.

Software Tools to Support Research on Airport Departure Planning

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

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.

Freight Transportation Energy Use : Volume 2. Methodology and Program Documentation.

DOT National Transportation Integrated Search

1978-07-01

The structure and logic of the transportation network model component of the TSC Freight Energy Model are presented. The model assigns given origin-destination commodity flows to specific transport modes and routes, thereby determining the traffic lo...

Traffic dynamics of an on-ramp system with a cellular automaton model

NASA Astrophysics Data System (ADS)

Li, Xin-Gang; Gao, Zi-You; Jia, Bin; Jiang, Rui

2010-06-01

This paper uses the cellular automaton model to study the dynamics of traffic flow around an on-ramp with an acceleration lane. It adopts a parameter, which can reflect different lane-changing behaviour, to represent the diversity of driving behaviour. The refined cellular automaton model is used to describe the lower acceleration rate of a vehicle. The phase diagram and the capacity of the on-ramp system are investigated. The simulation results show that in the single cell model, the capacity of the on-ramp system will stay at the highest flow of a one lane system when the driver is moderate and careful; it will be reduced when the driver is aggressive. In the refined cellular automaton model, the capacity is always reduced even when the driver is careful. It proposes that the capacity drop of the on-ramp system is caused by aggressive lane-changing behaviour and lower acceleration rate.

Optimization and Planning of Emergency Evacuation Routes Considering Traffic Control

PubMed Central

Zhang, Lijun; Wang, Zhaohua

2014-01-01

Emergencies, especially major ones, happen fast, randomly, as well as unpredictably, and generally will bring great harm to people's life and the economy. Therefore, governments and lots of professionals devote themselves to taking effective measures and providing optimal evacuation plans. This paper establishes two different emergency evacuation models on the basis of the maximum flow model (MFM) and the minimum-cost maximum flow model (MC-MFM), and proposes corresponding algorithms for the evacuation from one source node to one designated destination (one-to-one evacuation). Ulteriorly, we extend our evaluation model from one source node to many designated destinations (one-to-many evacuation). At last, we make case analysis of evacuation optimization and planning in Beijing, and obtain the desired evacuation routes and effective traffic control measures from the perspective of sufficiency and practicability. Both analytical and numerical results support that our models are feasible and practical. PMID:24991636

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

NASA Astrophysics Data System (ADS)

Ren, Yihui

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

Influence of lateral discomfort on the stability of traffic flow based on visual angle car-following model

NASA Astrophysics Data System (ADS)

Zheng, Liang; Zhong, Shiquan; Jin, Peter J.; Ma, Shoufeng

2012-12-01

Due to the poor road markings and irregular driving behaviors, not every vehicle is positioned in the center of the lane. The deviation from the center can cause discomfort to drivers in the neighboring lane, which is referred to as lateral discomfort (or lateral friction). Such lateral discomfort can be incorporated into the driver stimulus-response framework by considering the visual angle and its changing rate from the psychological viewpoint. In this study, a two-lane visual angle based car-following model is proposed and its stability condition is obtained through linear stability theory. Further derivations indicate that the neutral stability line of the model is asymmetry and four factors including the vehicle width and length, the lateral separation and the sensitivity regarding the changing rate of visual angle have large impacts on the stability of traffic flow. Numerical simulations further verify these theoretical results, and demonstrate that the behaviors of diverging, merging and lane changing can break the original steady state and cause traffic fluctuations. However, these fluctuations may be alleviated to some extent by reducing the lateral discomfort.

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

On supervised graph Laplacian embedding CA model & kernel construction and its application

NASA Astrophysics Data System (ADS)

Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

2017-01-01

There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

Outside and inside noise exposure in urban and suburban areas

Treesearch

Dwight E. Bishop; Myles A. Simpson

1977-01-01

In urban and suburban areas of the United States (away from major airports), the outdoor noise environment usually depends strongly on local vehicular traffic. By relating traffic flow to population density, a model of outdoor noise exposure has been developed for estimating the cumulative 24-hour noise exposure based upon the population density of the area. This noise...

Discrete Mathematical Approaches to Graph-Based Traffic Analysis

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

Joslyn, Cliff A.; Cowley, Wendy E.; Hogan, Emilie A.

2014-04-01

Modern cyber defense and anlaytics requires general, formal models of cyber systems. Multi-scale network models are prime candidates for such formalisms, using discrete mathematical methods based in hierarchically-structured directed multigraphs which also include rich sets of labels. An exemplar of an application of such an approach is traffic analysis, that is, observing and analyzing connections between clients, servers, hosts, and actors within IP networks, over time, to identify characteristic or suspicious patterns. Towards that end, NetFlow (or more generically, IPFLOW) data are available from routers and servers which summarize coherent groups of IP packets flowing through the network. In thismore » paper, we consider traffic analysis of Netflow using both basic graph statistics and two new mathematical measures involving labeled degree distributions and time interval overlap measures. We do all of this over the VAST test data set of 96M synthetic Netflow graph edges, against which we can identify characteristic patterns of simulated ground-truth network attacks.« less

Crash risk analysis during fog conditions using real-time traffic data.

PubMed

Wu, Yina; Abdel-Aty, Mohamed; Lee, Jaeyoung

2018-05-01

This research investigates the changes of traffic characteristics and crash risks during fog conditions. Using real-time traffic flow and weather data at two regions in Florida, the traffic patterns at the fog duration were compared to the traffic patterns at the clear duration. It was found that the average 5-min speed and the average 5-min volume were prone to decreasing during fog. Based on previous studies, a "Crash Risk Increase Indicator (CRII)" was proposed to explore the differences of crash risk between fog and clear conditions. A binary logistic regression model was applied to link the increase of crash risks with traffic flow characteristics. The results suggested that the proposed indicator worked well in evaluating the increase of crash risk under fog condition. It was indicated that the crash risk was prone to increase at ramp vicinities in fog conditions. Also, the average 5-min volume during fog and the lane position are important factors for crash risk increase. The differences between the regions were also explored in this study. The results indicated that the locations with heavier traffic or locations at the lanes that were closest to the median in Region 2 were more likely to observe an increase in crash risks in fog conditions. It is expected that the proposed indicator can help identify the dangerous traffic status under fog conditions and then proper ITS technologies can be implemented to enhance traffic safety when the visibility declines. Copyright © 2017 Elsevier Ltd. All rights reserved.

Traffic flow theory and chaotic behavior

DOT National Transportation Integrated Search

1989-03-01

Many commonly occurring natural systems are modeled with mathematical experessions and exhibit a certain stability. The inherent stability of these equations allows them to serve as the basis for engineering predictions. More complex models, such as ...

A review of fundamental drivers governing the emissions, dispersion and exposure to vehicle-emitted nanoparticles at signalised traffic intersections

NASA Astrophysics Data System (ADS)

Goel, Anju; Kumar, Prashant

2014-11-01

Signalised traffic intersections (TIs) are considered as pollution hot-spots in urban areas, but the knowledge of fundamental drivers governing emission, dispersion and exposure to vehicle-emitted nanoparticles (represented by particle number concentration, PNC) at TIs is yet to be established. A number of following key factors, which are important for developing an emission and exposure framework for nanoparticles at TIs, are critically evaluated as a part of this review article. In particular, (i) how do traffic- and wind-flow features affect emission and dispersion of nanoparticles? (ii) What levels of PNCs can be typically expected under diverse signal- and traffic-conditions? (iii) How does the traffic driving condition affect the particle number (PN) emissions and the particle number emission factors (PNEF)? (iv) What is the relative importance of particle transformation processes in affecting the PNCs? (v) What are important considerations for the dispersion modelling of nanoparticles? (vi) What is extent of exposure at TIs with respect to other locations in urban settings? (vii) What are the gaps in current knowledge on this topic where the future research should focus? We found that the accurate consideration of dynamic traffic flow features at TIs is essential for reliable estimates of PN emissions. Wind flow features at TIs are generally complex to generalise. Only a few field studies have monitored PNCs at TIs until now, reporting over an order of magnitude larger peak PNCs (0.7-5.4 × 105 cm-3) compared with average PNCs at typical roadsides (˜0.3 × 105 cm-3). The PN emission and thus the PNEFs can be up to an order of magnitude higher during acceleration compared with steady speed conditions. The time scale analysis suggests nucleation as the fastest transformation process, followed by dilution, deposition, coagulation and condensation. Consideration of appropriate flow features, PNEFs and transformation processes emerged as important parameters for reliable modelling of PNCs at TIs. Computation of respiratory deposition doses (RDD) based on the available PNC data suggest that the peak RDD at TIs can be up to 12-times higher compared with average RDD at urban roadsides. Systematic field and modelling studies are needed to develop a sound understanding of the emissions, dispersion and exposure of nanoparticles at the TIs.

A mixed-mode traffic assignment model with new time-flow impedance function

NASA Astrophysics Data System (ADS)

Lin, Gui-Hua; Hu, Yu; Zou, Yuan-Yang

2018-01-01

Recently, with the wide adoption of electric vehicles, transportation network has shown different characteristics and been further developed. In this paper, we present a new time-flow impedance function, which may be more realistic than the existing time-flow impedance functions. Based on this new impedance function, we present an optimization model for a mixed-mode traffic network in which battery electric vehicles (BEVs) and gasoline vehicles (GVs) are chosen. We suggest two approaches to handle the model: One is to use the interior point (IP) algorithm and the other is to employ the sequential quadratic programming (SQP) algorithm. Three numerical examples are presented to illustrate the efficiency of these approaches. In particular, our numerical results show that more travelers prefer to choosing BEVs when the distance limit of BEVs is long enough and the unit operating cost of GVs is higher than that of BEVs, and the SQP algorithm is faster than the IP algorithm.

Contribution of highway capital to industry and national productivity growth

DOT National Transportation Integrated Search

1973-10-01

The report contains the authors initial efforts aimed at extending the steady state freeway model for optimizing freeway traffic flow to a non-steady state model. The steady-state model does not allow reaction to continuously changing conditions whic...

Game theory model of traffic participants within amber time at signalized intersection.

PubMed

Qi, Weiwei; Wen, Huiying; Fu, Chuanyun; Song, Mo

2014-01-01

The traffic light scheme is composed of red, green, and amber lights, and it has been defined clearly for the traffic access of red and green lights; however, the definition of that for the amber light is indistinct, which leads to the appearance of uncertainty factors and serious traffic conflicts during the amber light. At present, the traffic administrations are faced with the decision of whether to forbid passing or not during the amber light in the cities of China. On one hand, it will go against the purpose of setting amber lights if forbidding passing; on the other hand, it may lead to a mess of traffic flow running if not. And meanwhile the drivers are faced with the decision of passing the intersection or stopping during the amber light as well. So the decision-making behavior of traffic administrations and drivers can be converted into a double game model. And through quantification of their earnings in different choice conditions, the optimum decision-making plan under specific conditions could be solved via the Nash equilibrium solution concept. Thus the results will provide a basis for the formulation of the traffic management strategy.

Game Theory Model of Traffic Participants within Amber Time at Signalized Intersection

PubMed Central

Qi, Weiwei; Wen, Huiying; Fu, Chuanyun; Song, Mo

2014-01-01

The traffic light scheme is composed of red, green, and amber lights, and it has been defined clearly for the traffic access of red and green lights; however, the definition of that for the amber light is indistinct, which leads to the appearance of uncertainty factors and serious traffic conflicts during the amber light. At present, the traffic administrations are faced with the decision of whether to forbid passing or not during the amber light in the cities of China. On one hand, it will go against the purpose of setting amber lights if forbidding passing; on the other hand, it may lead to a mess of traffic flow running if not. And meanwhile the drivers are faced with the decision of passing the intersection or stopping during the amber light as well. So the decision-making behavior of traffic administrations and drivers can be converted into a double game model. And through quantification of their earnings in different choice conditions, the optimum decision-making plan under specific conditions could be solved via the Nash equilibrium solution concept. Thus the results will provide a basis for the formulation of the traffic management strategy. PMID:25580108

Droplet Traffic Control at a simple T junction

NASA Astrophysics Data System (ADS)

Panizza, Pascal; Engl, Wilfried; Colin, Annie; Ajdari, Armand

2006-03-01

A basic yet essential element of every traffic flow control is the effect of a junction where the flow is separated into several streams. How do pedestrians, vehicles or blood cells divide when they reach a junction? How does the outcome depend on their density? Similar fundamental questions hold for much simpler systems: in this paper, we have studied the behaviour of periodic trains of water droplets flowing in oil through a channel as they reach a simple, locally symmetric, T junction. Depending on their dilution, we observe that the droplets are either alternately partitioned between both outlets or sorted exclusively into the shortest one. We show that this surprising behaviour results from the hydrodynamic feed-back of drops in the two outlets on the selection process occurring at the junction. Our results offer a first guide for the design and modelling of droplet traffic in complex branched networks, a necessary step towards parallelized droplet-based ``lab-on-chip'' devices.

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

Optimal topology to minimizing congestion in connected communication complex network

NASA Astrophysics Data System (ADS)

Benyoussef, M.; Ez-Zahraouy, H.; Benyoussef, A.

In this paper, a new model of the interdependent complex network is proposed, based on two assumptions that (i) the capacity of a node depends on its degree, and (ii) the traffic load depends on the distribution of the links in the network. Based on these assumptions, the presented model proposes a method of connection not based on the node having a higher degree but on the region containing hubs. It is found that the final network exhibits two kinds of degree distribution behavior, depending on the kind and the way of the connection. This study reveals a direct relation between network structure and traffic flow. It is found that pc the point of transition between the free flow and the congested phase depends on the network structure and the degree distribution. Moreover, this new model provides an improvement in the traffic compared to the results found in a single network. The same behavior of degree distribution found in a BA network and observed in the real world is obtained; except for this model, the transition point between the free phase and congested phase is much higher than the one observed in a network of BA, for both static and dynamic protocols.

Self-organized criticality in asymmetric exclusion model with noise for freeway traffic

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

1995-02-01

The one-dimensional asymmetric simple-exclusion model with open boundaries for parallel update is extended to take into account temporary stopping of particles. The model presents the traffic flow on a highway with temporary deceleration of cars. Introducing temporary stopping into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. In the self-organized critical state, start-stop waves (or traffic jams) appear with various sizes (or lifetimes). The typical interval < s>between consecutive jams scales as < s> ≃ Lv with v = 0.51 ± 0.05 where L is the system size. It is shown that the cumulative jam-interval distribution Ns( L) satisfies the finite-size scaling form ( Ns( L) ≃ L- vf( s/ Lv). Also, the typical lifetime ≃ Lv‧ with v‧ = 0.52 ± 0.05. The cumulative distribution Nm( L) of lifetimes satisfies the finite-size scaling form Nm( L)≃ L-1g( m/ Lv‧).

Prediction of Particle Concentration using Traffic Emission Model

NASA Astrophysics Data System (ADS)

He, Hong-di; Lu, Jane Wei-zhen

2010-05-01

Vehicle emission is regarded as one of major sources of air pollution in urban area. Much attention has been addressed on it especially at traffic intersection. At intersection, vehicles frequently stop with idling engine during the red time and speed-up rapidly in the green time, which result in a high velocity fluctuation and produce extra pollutants to the surrounding air. To deeply understand such process, a semi-empirical model for predicting the changing effect of traffic flow patterns on particulate concentrations is proposed. The performance of the model is evaluated using the correlation coefficient and other parameters. From the results, the correlation coefficients in morning and afternoon data were found to be 0.86 an 0.73 respectively, which implies that the semi-empirical model for morning and afternoon data are 86% and 73% error free. Due to less affected by possible factors such as traffic volume and movement of pedestrian, the dispersion of the particulate matter in the morning is smaller and then contributes to higher performance than that in the afternoon.

Many particle approximation of the Aw-Rascle-Zhang second order model for vehicular traffic.

PubMed

Francesco, Marco Di; Fagioli, Simone; Rosini, Massimiliano D

2017-02-01

We consider the follow-the-leader approximation of the Aw-Rascle-Zhang (ARZ) model for traffic flow in a multi population formulation. We prove rigorous convergence to weak solutions of the ARZ system in the many particle limit in presence of vacuum. The result is based on uniform BV estimates on the discrete particle velocity. We complement our result with numerical simulations of the particle method compared with some exact solutions to the Riemann problem of the ARZ system.

An extended car-following model with consideration of the electric vehicle's driving range

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Chen, Liang; Yang, Shi-Chun; Shang, Hua-Yan

2015-07-01

In this paper, we propose a car-following model to explore the influences of the electric vehicle's driving range on the driving behavior under four traffic situations. The numerical results illustrate that the electric vehicle's behavior of exchanging battery at the charge station can destroy the stability of traffic flow and produce some prominent jams, and that the influences are related to the electric vehicle's driving range, i.e., the shorter the driving range is, the greater the effects are.

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.

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...

Modelling and optimization of rotary parking system

NASA Astrophysics Data System (ADS)

Skrzyniowski, A.

2016-09-01

The increasing number of vehicles in cities is a cause of traffic congestion which interrupts the smooth traffic flow. The established EU policy underlines the importance of restoring spaces for pedestrian traffic and public communication. The overall vehicle parking process in some parts of a city takes so much time that it has a negative impact on the environment. This article presents different kinds of solution with special focus on the rotary parking system (PO). This article is based on a project realized at the Faculty of Mechanical Engineering of Cracow University of Technology.

A two-stage flow-based intrusion detection model for next-generation networks.

PubMed

Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.

A two-stage flow-based intrusion detection model for next-generation networks

PubMed Central

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results. PMID:29329294

Project 0-1800 : NAFTA impacts on operations : executive summary

DOT National Transportation Integrated Search

2001-07-01

Project 0-1800 pioneered the use of modern micro-simulation models to analyze the complex procedures involved in international border crossing in Texas. Animated models simulate the entire southbound commercial traffic flow in two important internati...

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...

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.

A hierarchical framework for air traffic control

NASA Astrophysics Data System (ADS)

Roy, Kaushik

Air travel in recent years has been plagued by record delays, with over $8 billion in direct operating costs being attributed to 100 million flight delay minutes in 2007. Major contributing factors to delay include weather, congestion, and aging infrastructure; the Next Generation Air Transportation System (NextGen) aims to alleviate these delays through an upgrade of the air traffic control system. Changes to large-scale networked systems such as air traffic control are complicated by the need for coordinated solutions over disparate temporal and spatial scales. Individual air traffic controllers must ensure aircraft maintain safe separation locally with a time horizon of seconds to minutes, whereas regional plans are formulated to efficiently route flows of aircraft around weather and congestion on the order of every hour. More efficient control algorithms that provide a coordinated solution are required to safely handle a larger number of aircraft in a fixed amount of airspace. Improved estimation algorithms are also needed to provide accurate aircraft state information and situational awareness for human controllers. A hierarchical framework is developed to simultaneously solve the sometimes conflicting goals of regional efficiency and local safety. Careful attention is given in defining the interactions between the layers of this hierarchy. In this way, solutions to individual air traffic problems can be targeted and implemented as needed. First, the regional traffic flow management problem is posed as an optimization problem and shown to be NP-Hard. Approximation methods based on aggregate flow models are developed to enable real-time implementation of algorithms that reduce the impact of congestion and adverse weather. Second, the local trajectory design problem is solved using a novel slot-based sector model. This model is used to analyze sector capacity under varying traffic patterns, providing a more comprehensive understanding of how increased automation in NextGen will affect the overall performance of air traffic control. The dissertation also provides solutions to several key estimation problems that support corresponding control tasks. Throughout the development of these estimation algorithms, aircraft motion is modeled using hybrid systems, which encapsulate both the discrete flight mode of an aircraft and the evolution of continuous states such as position and velocity. The target-tracking problem is posed as one of hybrid state estimation, and two new algorithms are developed to exploit structure specific to aircraft motion, especially near airports. First, discrete mode evolution is modeled using state-dependent transitions, in which the likelihood of changing flight modes is dependent on aircraft state. Second, an estimator is designed for systems with limited mode changes, including arrival aircraft. Improved target tracking facilitates increased safety in collision avoidance and trajectory design problems. A multiple-target tracking and identity management algorithm is developed to improve situational awareness for controllers about multiple maneuvering targets in a congested region. Finally, tracking algorithms are extended to predict aircraft landing times; estimated time of arrival prediction is one example of important decision support information for air traffic control.

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.

2017-01-01

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

NASA Astrophysics Data System (ADS)

Wang, Lina; Jayaratne, Rohan; Heuff, Darlene; Morawska, Lidia

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

A cellular automata model for traffic flow based on kinetics theory, vehicles capabilities and driver reactions

NASA Astrophysics Data System (ADS)

Guzmán, H. A.; Lárraga, M. E.; Alvarez-Icaza, L.; Carvajal, J.

2018-02-01

In this paper, a reliable cellular automata model oriented to faithfully reproduce deceleration and acceleration according to realistic reactions of drivers, when vehicles with different deceleration capabilities are considered is presented. The model focuses on describing complex traffic phenomena by coding in its rules the basic mechanisms of drivers behavior, vehicles capabilities and kinetics, while preserving simplicity. In particular, vehiclés kinetics is based on uniform accelerated motion, rather than in impulsive accelerated motion as in most existing CA models. Thus, the proposed model calculates in an analytic way three safe preserving distances to determine the best action a follower vehicle can take under a worst case scenario. Besides, the prediction analysis guarantees that under the proper assumptions, collision between vehicles may not happen at any future time. Simulations results indicate that all interactions of heterogeneous vehicles (i.e., car-truck, truck-car, car-car and truck-truck) are properly reproduced by the model. In addition, the model overcomes one of the major limitations of CA models for traffic modeling: the inability to perform smooth approach to slower or stopped vehicles. Moreover, the model is also capable of reproducing most empirical findings including the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Like most CA models, integer values are used to make the model run faster, which makes the proposed model suitable for real time traffic simulation of large networks.

Design of Center-TRACON Automation System

NASA Technical Reports Server (NTRS)

Erzberger, Heinz; Davis, Thomas J.; Green, Steven

1993-01-01

A system for the automated management and control of terminal area traffic, referred to as the Center-TRACON Automation System (CTAS), is being developed at NASA Ames Research Center. In a cooperative program, NASA and FAA have efforts underway to install and evaluate the system at the Denver area and Dallas/Ft. Worth area air traffic control facilities. This paper will review CTAS architecture, and automation functions as well as the integration of CTAS into the existing operational system. CTAS consists of three types of integrated tools that provide computer-generated advisories for both en-route and terminal area controllers to guide them in managing and controlling arrival traffic efficiently. One tool, the Traffic Management Advisor (TMA), generates runway assignments, landing sequences and landing times for all arriving aircraft, including those originating from nearby feeder airports. TMA also assists in runway configuration control and flow management. Another tool, the Descent Advisor (DA), generates clearances for the en-route controllers handling arrival flows to metering gates. The DA's clearances ensure fuel-efficient and conflict free descents to the metering gates at specified crossing times. In the terminal area, the Final Approach Spacing Tool (FAST) provides heading and speed advisories that help controllers produce an accurately spaced flow of aircraft on the final approach course. Data bases consisting of several hundred aircraft performance models, airline preferred operational procedures, and a three dimensional wind model support the operation of CTAS. The first component of CTAS, the Traffic Management Advisor, is being evaluated at the Denver TRACON and the Denver Air Route Traffic Control Center. The second component, the Final Approach Spacing Tool, will be evaluated in several stages at the Dallas/Fort Worth Airport beginning in October 1993. An initial stage of the Descent Advisor tool is being prepared for testing at the Denver Center in late 1994. Operational evaluations of all three integrated CTAS tools are expected to begin at the two field sites in 1995.

Road Traffic Anomaly Detection via Collaborative Path Inference from GPS Snippets

PubMed Central

Wang, Hongtao; Wen, Hui; Yi, Feng; Zhu, Hongsong; Sun, Limin

2017-01-01

Road traffic anomaly denotes a road segment that is anomalous in terms of traffic flow of vehicles. Detecting road traffic anomalies from GPS (Global Position System) snippets data is becoming critical in urban computing since they often suggest underlying events. However, the noisy and sparse nature of GPS snippets data have ushered multiple problems, which have prompted the detection of road traffic anomalies to be very challenging. To address these issues, we propose a two-stage solution which consists of two components: a Collaborative Path Inference (CPI) model and a Road Anomaly Test (RAT) model. CPI model performs path inference incorporating both static and dynamic features into a Conditional Random Field (CRF). Dynamic context features are learned collaboratively from large GPS snippets via a tensor decomposition technique. Then RAT calculates the anomalous degree for each road segment from the inferred fine-grained trajectories in given time intervals. We evaluated our method using a large scale real world dataset, which includes one-month GPS location data from more than eight thousand taxicabs in Beijing. The evaluation results show the advantages of our method beyond other baseline techniques. PMID:28282948

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 ...

The influence of heavy vehicles on traffic dynamics around on-ramp system: Cellular automata approach

NASA Astrophysics Data System (ADS)

Kong, Dewen; Guo, Xiucheng; Wu, Dingxin

Although the on-ramp system has been widely studied, the influence of heavy vehicles is unknown because researchers only investigate the traffic dynamics around on-ramp system under homogeneous traffic conditions, which is different in real-world settings. This paper uses an improved cellular automaton model to study the heterogeneous traffic around on-ramp system. The forward motion rules are improved by considering the differences of driving behavior in different vehicle combinations. The lane change rules are improved by reflecting the aggressive behavior in mandatory lane changes. The phase diagram, traffic flow, capacity and spatial-temporal diagram are analyzed under the influences of heavy vehicles. The results show that by increasing the percentage of heavy vehicles, there will be more severe traffic congestion around on-ramp system, lower saturated flow and capacity. Also, the interactions between main road and on-ramp have been investigated. Increasing the percentage of heavy vehicles at the upstream of the conflict area on the main road or restricting heavy vehicles on the outside lane of the main road will deteriorate the performance of on-ramp. While the main road will have better performance as the percentage of heavy vehicles on the on-ramp increases when the on-ramp inflow rate is not low.

The influence of continuous historical velocity difference information on micro-cooperative driving stability

NASA Astrophysics Data System (ADS)

Yang, Liang-Yi; Sun, Di-Hua; Zhao, Min; Cheng, Sen-Lin; Zhang, Geng; Liu, Hui

2018-03-01

In this paper, a new micro-cooperative driving car-following model is proposed to investigate the effect of continuous historical velocity difference information on traffic stability. The linear stability criterion of the new model is derived with linear stability theory and the results show that the unstable region in the headway-sensitivity space will be shrunk by taking the continuous historical velocity difference information into account. Through nonlinear analysis, the mKdV equation is derived to describe the traffic evolution behavior of the new model near the critical point. Via numerical simulations, the theoretical analysis results are verified and the results indicate that the continuous historical velocity difference information can enhance the stability of traffic flow in the micro-cooperative driving process.

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.

Development of a Tool for an Efficient Calibration of CORSIM Models

DOT National Transportation Integrated Search

2014-08-01

This project proposes a Memetic Algorithm (MA) for the calibration of microscopic traffic flow simulation models. The proposed MA includes a combination of genetic and simulated annealing algorithms. The genetic algorithm performs the exploration of ...

Statewide mesoscopic simulation for Wyoming.

DOT National Transportation Integrated Search

2013-10-01

This study developed a mesoscopic simulator which is capable of representing both city-level and statewide roadway : networks. The key feature of such models are the integration of (i) a traffic flow model which is efficient enough to : scale to larg...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Open Source Surrogate Safety Assessment Model, 2017 Enhancement and Update: SSAM Version 3.0 [Tech Brief

DOT National Transportation Integrated Search

2016-11-17

The ETFOMM (Enhanced Transportation Flow Open Source Microscopic Model) Cloud Service (ECS) is a software product sponsored by the U.S. Department of Transportation in conjunction with the Microscopic Traffic Simulation Models and SoftwareAn Op...

Analysis of traffic congestion induced by the work zone

NASA Astrophysics Data System (ADS)

Fei, L.; Zhu, H. B.; Han, X. L.

2016-05-01

Based on the cellular automata model, a meticulous two-lane cellular automata model is proposed, in which the driving behavior difference and the difference of vehicles' accelerations between the moving state and the starting state are taken into account. Furthermore the vehicles' motion is refined by using the small cell of one meter long. Then accompanied by coming up with a traffic management measure, a two-lane highway traffic model containing a work zone is presented, in which the road is divided into normal area, merging area and work zone. The vehicles in different areas move forward according to different lane changing rules and position updating rules. After simulation it is found that when the density is small the cluster length in front of the work zone increases with the decrease of the merging probability. Then the suitable merging length and the appropriate speed limit value are recommended. The simulation result in the form of the speed-flow diagram is in good agreement with the empirical data. It indicates that the presented model is efficient and can partially reflect the real traffic. The results may be meaningful for traffic optimization and road construction management.

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.

An extended car-following model to describe connected traffic dynamics under cyberattacks

NASA Astrophysics Data System (ADS)

Wang, Pengcheng; Yu, Guizhen; Wu, Xinkai; Qin, Hongmao; Wang, Yunpeng

2018-04-01

In this paper, the impacts of the potential cyberattacks on vehicles are modeled through an extended car-following model. To better understand the mechanism of traffic disturbance under cyberattacks, the linear and nonlinear stability analysis are conducted respectively. Particularly, linear stability analysis is performed to obtain different neutral stability conditions with various parameters; and nonlinear stability analysis is carried out by using reductive perturbation method to derive the soliton solution of the modified Korteweg de Vries equation (mKdV) near the critical point, which is used to draw coexisting stability lines. Furthermore, by applying linear and nonlinear stability analysis, traffic flow state can be divided into three states, i.e., stable, metastable and unstable states which are useful to describe shockwave dynamics and driving behaviors under cyberattacks. The theoretical results show that the proposed car-following model is capable of successfully describing the car-following behavior of connected vehicles with cyberattacks. Finally, numerical simulation using real values has confirmed the validity of theoretical analysis. The results further demonstrate our model can be used to help avoid collisions and relieve traffic congestion with cybersecurity threats.

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

The impact of self-driving cars on existing transportation networks

NASA Astrophysics Data System (ADS)

Ji, Xiang

2018-04-01

In this paper, considering the usage of self-driving, I research the congestion problems of traffic networks from both macro and micro levels. Firstly, the macroscopic mathematical model is established using the Greenshields function, analytic hierarchy process and Monte Carlo simulation, where the congestion level is divided into five levels according to the average vehicle speed. The roads with an obvious congestion situation is investigated mainly and the traffic flow and topology of the roads are analyzed firstly. By processing the data, I propose a traffic congestion model. In the model, I assume that half of the non-self-driving cars only take the shortest route and the other half can choose the path randomly. While self-driving cars can obtain vehicle density data of each road and choose the path more reasonable. When the path traffic density exceeds specific value, it cannot be selected. To overcome the dimensional differences of data, I rate the paths by BORDA sorting. The Monte Carlo simulation of Cellular Automaton is used to obtain the negative feedback information of the density of the traffic network, where the vehicles are added into the road network one by one. I then analyze the influence of negative feedback information on path selection of intelligent cars. The conclusion is that the increase of the proportion of intelligent vehicles will make the road load more balanced, and the self-driving cars can avoid the peak and reduce the degree of road congestion. Combined with other models, the optimal self-driving ratio is about sixty-two percent. From the microscopic aspect, by using the single-lane traffic NS rule, another model is established to analyze the road Partition scheme. The self-driving traffic is more intelligent, and their cooperation can reduce the random deceleration probability. By the model, I get the different self-driving ratio of space-time distribution. I also simulate the case of making a lane separately for self-driving, compared to the former model. It is concluded that a single lane is more efficient in a certain interval. However, it is not recommended to offer a lane separately. However, the self-driving also faces the problem of hacker attacks and greater damage after fault. So, when self-driving ratio is higher than a certain value, the increase of traffic flow rate is small. In this article, that value is discussed, and the optimal proportion is determined. Finally, I give a nontechnical explanation of the problem.

Making the Traffic Operations Case for Congestion Pricing: Operational Impacts of Congestion Pricing

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

Chin, Shih-Miao; Hu, Patricia S; Davidson, Diane

2011-02-01

Congestion begins when an excess of vehicles on a segment of roadway at a given time, resulting in speeds that are significantly slower than normal or 'free flow' speeds. Congestion often means stop-and-go traffic. The transition occurs when vehicle density (the number of vehicles per mile in a lane) exceeds a critical level. Once traffic enters a state of congestion, recovery or time to return to a free-flow state is lengthy; and during the recovery process, delay continues to accumulate. The breakdown in speed and flow greatly impedes the efficient operation of the freeway system, resulting in economic, mobility, environmentalmore » and safety problems. Freeways are designed to function as access-controlled highways characterized by uninterrupted traffic flow so references to freeway performance relate primarily to the quality of traffic flow or traffic conditions as experienced by users of the freeway. The maximum flow or capacity of a freeway segment is reached while traffic is moving freely. As a result, freeways are most productive when they carry capacity flows at 60 mph, whereas lower speeds impose freeway delay, resulting in bottlenecks. Bottlenecks may be caused by physical disruptions, such as a reduced number of lanes, a change in grade, or an on-ramp with a short merge lane. This type of bottleneck occurs on a predictable or 'recurrent' basis at the same time of day and same day of week. Recurrent congestion totals 45% of congestion and is primarily from bottlenecks (40%) as well as inadequate signal timing (5%). Nonrecurring bottlenecks result from crashes, work zone disruptions, adverse weather conditions, and special events that create surges in demand and that account for over 55% of experienced congestion. Figure 1.1 shows that nonrecurring congestion is composed of traffic incidents (25%), severe weather (15%), work zones, (10%), and special events (5%). Between 1995 and 2005, the average percentage change in increased peak traveler delay, based on hours spent in traffic in a year, grew by 22% as the national average of hours spent in delay grew from 36 hours to 44 hours. Peak delay per traveler grew one-third in medium-size urban areas over the 10 year period. The traffic engineering community has developed an arsenal of integrated tools to mitigate the impacts of congestion on freeway throughput and performance, including pricing of capacity to manage demand for travel. Congestion pricing is a strategy which dynamically matches demand with available capacity. A congestion price is a user fee equal to the added cost imposed on other travelers as a result of the last traveler's entry into the highway network. The concept is based on the idea that motorists should pay for the additional congestion they create when entering a congested road. The concept calls for fees to vary according to the level of congestion with the price mechanism applied to make travelers more fully aware of the congestion externality they impose on other travelers and the system itself. The operational rationales for the institution of pricing strategies are to improve the efficiency of operations in a corridor and/or to better manage congestion. To this end, the objectives of this project were to: (1) Better understand and quantify the impacts of congestion pricing strategies on traffic operations through the study of actual projects, and (2) Better understand and quantify the impacts of congestion pricing strategies on traffic operations through the use of modeling and other analytical methods. Specifically, the project was to identify credible analytical procedures that FHWA can use to quantify the impacts of various congestion pricing strategies on traffic flow (throughput) and congestion.« less

How the propagation of heat-flux modulations triggers E × B flow pattern formation.

PubMed

Kosuga, Y; Diamond, P H; Gürcan, O D

2013-03-08

We propose a novel mechanism to describe E×B flow pattern formation based upon the dynamics of propagation of heat-flux modulations. The E × B flows of interest are staircases, which are quasiregular patterns of strong, localized shear layers and profile corrugations interspersed between regions of avalanching. An analogy of staircase formation to jam formation in traffic flow is used to develop an extended model of heat avalanche dynamics. The extension includes a flux response time, during which the instantaneous heat flux relaxes to the mean heat flux, determined by symmetry constraints. The response time introduced here is the counterpart of the drivers' response time in traffic, during which drivers adjust their speed to match the background traffic flow. The finite response time causes the growth of mesoscale temperature perturbations, which evolve to form profile corrugations. The length scale associated with the maximum growth rate scales as Δ(2) ~ (v(thi)/λT(i))ρ(i)sqrt[χ(neo)τ], where λT(i) is a typical heat pulse speed, χ(neo) is the neoclassical thermal diffusivity, and τ is the response time of the heat flux. The connection between the scale length Δ(2) and the staircase interstep scale is discussed.

A speed guidance strategy for multiple signalized intersections based on car-following model

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Yi, Zhi-Yan; Zhang, Jian; Wang, Tao; Leng, Jun-Qiang

2018-04-01

Signalized intersection has great roles in urban traffic system. The signal infrastructure and the driving behavior near the intersection are paramount factors that have significant impacts on traffic flow and energy consumption. In this paper, a speed guidance strategy is introduced into a car-following model to study the driving behavior and the fuel consumption in a single-lane road with multiple signalized intersections. The numerical results indicate that the proposed model can reduce the fuel consumption and the average stop times. The findings provide insightful guidance for the eco-driving strategies near the signalized intersections.

Effect of vehicular size on chain-reaction crash

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

2015-11-01

We present the dynamic model of the chain-reaction crash to take account of the vehicular size. Drivers brake according to taillights of the forward vehicle. We investigate the effect of the vehicular size on the chain-reaction crash (multiple-vehicle collision) in the traffic flow controlled by taillights. In the multiple-vehicle collision, the first crash induces more collisions. We investigate how the first collision induces the chain-reaction crash numerically. We derive, analytically, the transition points and the region maps for the chain-reaction crash in the traffic flow of vehicles with finite sizes. We clarify the effect of the vehicular size on the multiple-vehicle collision.

Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier.

PubMed

El-Sayed, Hesham; Sankar, Sharmi; Daraghmi, Yousef-Awwad; Tiwari, Prayag; Rattagan, Ekarat; Mohanty, Manoranjan; Puthal, Deepak; Prasad, Mukesh

2018-05-24

Heterogeneous vehicular networks (HETVNETs) evolve from vehicular ad hoc networks (VANETs), which allow vehicles to always be connected so as to obtain safety services within intelligent transportation systems (ITSs). The services and data provided by HETVNETs should be neither interrupted nor delayed. Therefore, Quality of Service (QoS) improvement of HETVNETs is one of the topics attracting the attention of researchers and the manufacturing community. Several methodologies and frameworks have been devised by researchers to address QoS-prediction service issues. In this paper, to improve QoS, we evaluate various traffic characteristics of HETVNETs and propose a new supervised learning model to capture knowledge on all possible traffic patterns. This model is a refinement of support vector machine (SVM) kernels with a radial basis function (RBF). The proposed model produces better results than SVMs, and outperforms other prediction methods used in a traffic context, as it has lower computational complexity and higher prediction accuracy.

Serial Network Flow Monitor

NASA Technical Reports Server (NTRS)

Robinson, Julie A.; Tate-Brown, Judy M.

2009-01-01

Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

Two level approach to safety planning incorporating the Highway Safety Manual (HSM) network screening : [summary].

DOT National Transportation Integrated Search

2014-04-01

In this project, University of Central Florida researchers combined two types of safety analysis, microscopic and macroscopic, to overcome their limitations. Microscopic models focus on traffic flows and related parameters. Macroscopic models are bas...

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

Discovering urban mobility patterns with PageRank based traffic modeling and prediction

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Applying Graph Theory to Problems in Air Traffic Management

NASA Technical Reports Server (NTRS)

Farrahi, Amir Hossein; Goldbert, Alan; Bagasol, Leonard Neil; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

Applying Graph Theory to Problems in Air Traffic Management

NASA Technical Reports Server (NTRS)

Farrahi, Amir H.; Goldberg, Alan T.; Bagasol, Leonard N.; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

Signal timing on a shoestring

DOT National Transportation Integrated Search

2005-03-01

The conventional approach to signal timing optimization and field deployment requires current traffic flow data, experience with optimization models, familiarity with the signal controller hardware, and knowledge of field operations including signal ...

Signal timing on a shoestring.

DOT National Transportation Integrated Search

2005-03-01

The conventional approach to signal timing optimization and field deployment requires current traffic flow data, experience with optimization models, familiarity with the signal controller hardware, and knowledge of field operations including signal ...

An improved car-following model accounting for the preceding car's taillight

NASA Astrophysics Data System (ADS)

Zhang, Jian; Tang, Tie-Qiao; Yu, Shao-Wei

2018-02-01

During the deceleration process, the preceding car's taillight may have influences on its following car's driving behavior. In this paper, we propose an extended car-following model with consideration of the preceding car's taillight. Two typical situations are used to simulate each car's movement and study the effects of the preceding car's taillight on the driving behavior. Meanwhile, sensitivity analysis of the model parameter is in detail discussed. The numerical results show that the proposed model can improve the stability of traffic flow and the traffic safety can be enhanced without a decrease of efficiency especially when cars pass through a signalized intersection.

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...

Linking pedestrian flow characteristics with stepping locomotion

NASA Astrophysics Data System (ADS)

Wang, Jiayue; Boltes, Maik; Seyfried, Armin; Zhang, Jun; Ziemer, Verena; Weng, Wenguo

2018-06-01

While properties of human traffic flow are described by speed, density and flow, the locomotion of pedestrian is based on steps. To relate characteristics of human locomotor system with properties of human traffic flow, this paper aims to connect gait characteristics like step length, step frequency, swaying amplitude and synchronization with speed and density and thus to build a ground for advanced pedestrian models. For this aim, observational and experimental study on the single-file movement of pedestrians at different densities is conducted. Methods to measure step length, step frequency, swaying amplitude and step synchronization are proposed by means of trajectories of the head. Mathematical models for the relations of step length or frequency and speed are evaluated. The problem how step length and step duration are influenced by factors like body height and density is investigated. It is shown that the effect of body height on step length and step duration changes with density. Furthermore, two different types of step in-phase synchronization between two successive pedestrians are observed and the influence of step synchronization on step length is examined.

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.

An improved Burgers cellular automaton model for bicycle flow

NASA Astrophysics Data System (ADS)

Xue, Shuqi; Jia, Bin; Jiang, Rui; Li, Xingang; Shan, Jingjing

2017-12-01

As an energy-efficient and healthy transport mode, bicycling has recently attracted the attention of governments, transport planners, and researchers. The dynamic characteristics of the bicycle flow must be investigated to improve the facility design and traffic operation of bicycling. We model the bicycle flow by using an improved Burgers cellular automaton model. Through a following move mechanism, the modified model enables bicycles to move smoothly and increase the critical density to a more rational level than the original model. The model is calibrated and validated by using experimental data and field data. The results show that the improved model can effectively simulate the bicycle flow. The performance of the model under different parameters is investigated and discussed. Strengths and limitations of the improved model are suggested for future work.

A new car-following model for autonomous vehicles flow with mean expected velocity field

NASA Astrophysics Data System (ADS)

Wen-Xing, Zhu; Li-Dong, Zhang

2018-02-01

Due to the development of the modern scientific technology, autonomous vehicles may realize to connect with each other and share the information collected from each vehicle. An improved forward considering car-following model was proposed with mean expected velocity field to describe the autonomous vehicles flow behavior. The new model has three key parameters: adjustable sensitivity, strength factor and mean expected velocity field size. Two lemmas and one theorem were proven as criteria for judging the stability of homogeneousautonomous vehicles flow. Theoretical results show that the greater parameters means larger stability regions. A series of numerical simulations were carried out to check the stability and fundamental diagram of autonomous flow. From the numerical simulation results, the profiles, hysteresis loop and density waves of the autonomous vehicles flow were exhibited. The results show that with increased sensitivity, strength factor or field size the traffic jam was suppressed effectively which are well in accordance with the theoretical results. Moreover, the fundamental diagrams corresponding to three parameters respectively were obtained. It demonstrates that these parameters play almost the same role on traffic flux: i.e. before the critical density the bigger parameter is, the greater flux is and after the critical density, the opposite tendency is. In general, the three parameters have a great influence on the stability and jam state of the autonomous vehicles flow.

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.

Enhanced stability of car-following model upon incorporation of short-term driving memory

NASA Astrophysics Data System (ADS)

Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

2017-06-01

Based on the full velocity difference model, a new car-following model is developed to investigate the effect of short-term driving memory on traffic flow in this paper. Short-term driving memory is introduced as the influence factor of driver's anticipation behavior. The stability condition of the newly developed model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Via numerical method, evolution of a small perturbation is investigated firstly. The results show that the improvement of this new car-following model over the previous ones lies in the fact that the new model can improve the traffic stability. Starting and breaking processes of vehicles in the signalized intersection are also investigated. The numerical simulations illustrate that the new model can successfully describe the driver's anticipation behavior, and that the efficiency and safety of the vehicles passing through the signalized intersection are improved by considering short-term driving memory.

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...

Network-optimized congestion pricing : a parable, model and algorithm

DOT National Transportation Integrated Search

1995-05-31

This paper recites a parable, formulates a model and devises an algorithm for optimizing tolls on a road network. Such tolls induce an equilibrium traffic flow that is at once system-optimal and user-optimal. The parable introduces the network-wide c...

Use of Cusp Catastrophe for Risk Analysis of Navigational Environment: A Case Study of Three Gorges Reservoir Area

PubMed Central

Hao, Guozhu

2016-01-01

A water traffic system is a huge, nonlinear, complex system, and its stability is affected by various factors. Water traffic accidents can be considered to be a kind of mutation of a water traffic system caused by the coupling of multiple navigational environment factors. In this study, the catastrophe theory, principal component analysis (PCA), and multivariate statistics are integrated to establish a situation recognition model for a navigational environment with the aim of performing a quantitative analysis of the situation of this environment via the extraction and classification of its key influencing factors; in this model, the natural environment and traffic environment are considered to be two control variables. The Three Gorges Reservoir area of the Yangtze River is considered as an example, and six critical factors, i.e., the visibility, wind, current velocity, route intersection, channel dimension, and traffic flow, are classified into two principal components: the natural environment and traffic environment. These two components are assumed to have the greatest influence on the navigation risk. Then, the cusp catastrophe model is employed to identify the safety situation of the regional navigational environment in the Three Gorges Reservoir area. The simulation results indicate that the situation of the navigational environment of this area is gradually worsening from downstream to upstream. PMID:27391057

Use of Cusp Catastrophe for Risk Analysis of Navigational Environment: A Case Study of Three Gorges Reservoir Area.

PubMed

Jiang, Dan; Hao, Guozhu; Huang, Liwen; Zhang, Dan

2016-01-01

A water traffic system is a huge, nonlinear, complex system, and its stability is affected by various factors. Water traffic accidents can be considered to be a kind of mutation of a water traffic system caused by the coupling of multiple navigational environment factors. In this study, the catastrophe theory, principal component analysis (PCA), and multivariate statistics are integrated to establish a situation recognition model for a navigational environment with the aim of performing a quantitative analysis of the situation of this environment via the extraction and classification of its key influencing factors; in this model, the natural environment and traffic environment are considered to be two control variables. The Three Gorges Reservoir area of the Yangtze River is considered as an example, and six critical factors, i.e., the visibility, wind, current velocity, route intersection, channel dimension, and traffic flow, are classified into two principal components: the natural environment and traffic environment. These two components are assumed to have the greatest influence on the navigation risk. Then, the cusp catastrophe model is employed to identify the safety situation of the regional navigational environment in the Three Gorges Reservoir area. The simulation results indicate that the situation of the navigational environment of this area is gradually worsening from downstream to upstream.

Communication efficiency and congestion of signal traffic in large-scale brain networks.

PubMed

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.

Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks

PubMed Central

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R.

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a “rich club” of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication. PMID:24415931

Review of modelling air pollution from traffic at street-level - The state of the science.

PubMed

Forehead, H; Huynh, N

2018-06-13

Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major source of atmospheric pollution in the parts of cities where people live, commute and work. Reducing exposure requires information about the distribution and nature of emissions. Spatially and temporally detailed data are required, because both the rate of production and the composition of emissions vary significantly with time of day and with local changes in wind, traffic composition and flow. Increasing computer processing power means that models can accept highly detailed inputs of fleet, fuels and road networks. The state of the science models can simulate the behaviour and emissions of all the individual vehicles on a road network, with resolution of a second and tens of metres. The chemistry of the simulated emissions is also highly resolved, due to consideration of multiple engine processes, fuel evaporation and tyre wear. Good results can be achieved with both commercially available and open source models. The extent of a simulation is usually limited by processing capacity; the accuracy by the quality of traffic data. Recent studies have generated real time, detailed emissions data by using inputs from novel traffic sensing technologies and data from intelligent traffic systems (ITS). Increasingly, detailed pollution data is being combined with spatially resolved demographic or epidemiological data for targeted risk analyses. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Davis, L. C.

2016-06-01

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

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Preventing Road Rage by Modelling the Car-following and the Safety Distance Model

NASA Astrophysics Data System (ADS)

Lan, Si; Fang, Ni; Zhao, Huanming; Ye, Shiqi

2017-11-01

Starting from the different behaviours of the driver’s lane change, the car-following model based on the distance and speed and the safety distance model are established in this paper, so as to analyse the impact on traffic flow and safety, helping solve the phenomenon of road anger.

Development of simulation techniques suitable for the analysis of air traffic control situations and instrumentation

NASA Technical Reports Server (NTRS)

1972-01-01

A terminal area simulation is described which permits analysis and synthesis of current and advanced air traffic management system configurations including ground and airborne instrumentation and new and modified aircraft characteristics. Ground elements in the simulation include navigation aids, surveillance radars, communication links, air-route structuring, ATC procedures, airport geometries and runway handling constraints. Airborne elements include traffic samples with individual aircraft performance and operating characteristics and aircraft navigation equipment. The simulation also contains algorithms for conflict detection, conflict resolution, sequencing and pilot-controller data links. The simulation model is used to determine the sensitivities of terminal area traffic flow, safety and congestion to aircraft performance characteristics, avionics systems, and other ATC elements.

Density waves in granular flow

NASA Astrophysics Data System (ADS)

Herrmann, H. J.; Flekkøy, E.; Nagel, K.; Peng, G.; Ristow, G.

Ample experimental evidence has shown the existence of spontaneous density waves in granular material flowing through pipes or hoppers. Using Molecular Dynamics Simulations we show that several types of waves exist and find that these density fluctuations follow a 1/f spectrum. We compare this behaviour to deterministic one-dimensional traffic models. If positions and velocities are continuous variables the model shows self-organized criticality driven by the slowest car. We also present Lattice Gas and Boltzmann Lattice Models which reproduce the experimentally observed effects. Density waves are spontaneously generated when the viscosity has a nonlinear dependence on density which characterizes granular flow.

Multiple logistic regression model of signalling practices of drivers on urban highways

NASA Astrophysics Data System (ADS)

Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

2015-05-01

Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

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

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.

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

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...

Concurrent Flow Lanes - Phase II

DOT National Transportation Integrated Search

2009-04-17

This report provides the findings from a research effort designed to ascertain whether or not a chosen simulation software platform, the VISSIM micro-simulation platform, provides a suitable environment for modeling and analyzing traffic operations, ...

Spatial Analysis of Urban Form and Pedestrian Exposure to Traffic Noise

PubMed Central

Sheng, Ni; Tang, U. Wa

2011-01-01

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

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

PubMed

Sheng, Ni; Tang, U Wa

2011-06-01

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

Modeling of Pedestrian Flows Using Hybrid Models of Euler Equations and Dynamical Systems

NASA Astrophysics Data System (ADS)

Bärwolff, Günter; Slawig, Thomas; Schwandt, Hartmut

2007-09-01

In the last years various systems have been developed for controlling, planning and predicting the traffic of persons and vehicles, in particular under security aspects. Going beyond pure counting and statistical models, approaches were found to be very adequate and accurate which are based on well-known concepts originally developed in very different research areas, namely continuum mechanics and computer science. In the present paper, we outline a continuum mechanical approach for the description of pedestrain flow.

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...

Multiple-vehicle collision induced by a sudden stop in traffic flow

NASA Astrophysics Data System (ADS)

Sugiyama, Naoki; Nagatani, Takashi

2012-04-01

We study the dynamic process of the multiple-vehicle collision when a vehicle stops suddenly in a traffic flow. We apply the optimal-velocity model to the vehicular motion. If a vehicle does not decelerate successfully, it crashes into the vehicle ahead with a residual speed. The collision criterion is presented by vi(t)/Δxi(t)→∞ if Δxi(t)→0 where vi(t) and Δxi(t) are the speed and headway of vehicle i at time t. The number of crumpled vehicles depends on the initial velocity, the sensitivity, and the initial headway. We derive the region map (or phase diagram) for the multiple-vehicle collision.

The feedback control research on straight and curved road with car-following model

NASA Astrophysics Data System (ADS)

Zheng, Yi-Ming; Cheng, Rong-Jun; Ge, Hong-Xia

2017-07-01

Taking account of the road consisting of curved part and straight part, an extended car-following model is proposed in this paper. A control signal including the velocity difference between the considered vehicle and the vehicle in front is taken into account. The control theory method is applied into analysis of the stability condition for the model. Numerical simulations are implemented to prove that the stability of the traffic flow strengthens effectively with an increase of the radius of curved road, and the control signal can suppress the traffic congestion. The results are in good agree with the theoretical analysis.

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 Critical Survey of Optimization Models for Tactical and Strategic Aspects of Air Traffic Flow Management

NASA Technical Reports Server (NTRS)

Bertsimas, Dimitris; Odoni, Amedeo

1997-01-01

This document presents a critical review of the principal existing optimization models that have been applied to Air Traffic Flow Management (TFM). Emphasis will be placed on two problems, the Generalized Tactical Flow Management Problem (GTFMP) and the Ground Holding Problem (GHP), as well as on some of their variations. To perform this task, we have carried out an extensive literature review that has covered more than 40 references, most of them very recent. Based on the review of this emerging field our objectives were to: (i) identify the best available models; (ii) describe typical contexts for applications of the models; (iii) provide illustrative model formulations; and (iv) identify the methodologies that can be used to solve the models. We shall begin our presentation below by providing a brief context for the models that we are reviewing. In Section 3 we shall offer a taxonomy and identify four classes of models for review. In Sections 4, 5, and 6 we shall then review, respectively, models for the Single-Airport Ground Holding Problem, the Generalized Tactical FM P and the Multi-Airport Ground Holding Problem (for the definition of these problems see Section 3 below). In each section, we identify the best available models and discuss briefly their computational performance and applications, if any, to date. Section 7 summarizes our conclusions about the state of the art.

NOx dispersion modelling around roundabout in a small city, example from Hungary

NASA Astrophysics Data System (ADS)

Farkas, Orsolya; Rákai, Anikó; Czáder, Károly; Török, Ákos

2013-04-01

The present paper focuses on the modelling of pollutant distribution and dispersion in an urban region that is located in a moderately industrialized town of Hungary, Székesfehérvár, with a population of 100,000. The study area is located close to the city centre, with different housing styles and different building elevations. High-rise buildings with 10 floors to small houses with gardens are found in the modelled area. The roundabout has 5 access roads; three major ones and two minor ones with different geometries and traffic load. The traffic load of the roads was defined by traffic count, while for the meteorological characteristics wind-statistics were created. Additional input parameters were the ground plan and the elevation of buildings. To simulate the airflow and the dispersion of pollutants a Computational Fluid Dynamics code called MISKAM was used. The background concentration was taken from the dataset of a nearby air quality monitoring station. According to vehicle counting the 5 roads of the roundabout have very different loads from 12 vehicles to more than 412 vehicles/hour. Three different grid systems were applied ranging from half million to 5 million cells. The difference in the results related to grid density was also evaluated. Wind speed distribution, wind turbulence and building wake flow patterns were identified by using the model. With the help of the simulation the NOx flow and dispersion of pollutants around the roundabout can be estimated and the critical locations with higher pollution concentration are presented. The results of the modelling can be more generalized and used in the design of the layout, development, traffic-control and environmental aspects of roundabouts located in small urban areas.

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.

The evaluation model of the design of toll

NASA Astrophysics Data System (ADS)

Feng, Shuting

2018-04-01

In recent years, the dramatic increase in traffic burden has highlighted the necessity of rational allocation of toll plaza. At the same time, the need to consider a lot of factors has enhanced the design requirements. In this background, we carry out research on this subject. We propose a reasonable assumption, and abstract the toll plaza into a model only related to B and L. By using the queuing theory and traffic flow theory, we define the throughput, cost and accident prevent with B and L to acquire the base model. By using the method of linear weighting in economics to calculate this model, the optimal B and L strategies are obtained.

Development of a dynamic traffic assignment model to evaluate lane-reversal plans for I-65.

DOT National Transportation Integrated Search

2010-05-01

This report presents the methodology and results from a project that studied contra-flow operations in support of : hurricane evacuations in the state of Alabama. As part of this effort, a simulation model was developed using the : VISTA platform for...

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…

[Modeling the vehicle pollution in the urban streets before and during the Beijing Olympic Games traffic control period].

PubMed

Wang, Ting; Xie, Shao-dong

2010-03-01

In order to investigate the vehicle pollution situation in the streets in Beijing and the abatement during the Olympic Games, the OSPM model was applied to calculate the concentrations of PM10, CO, NO2 and O3 inside the urban streets of Beijing before and during the Olympic traffic controlling period in July, 2008. The modeled concentrations before the traffic control are 146 micog/m3, 3.83 mg/m3, 114.4 microg/m3 and 4.71 x 10(-1), while after the traffic control are 112 microg/m3, 3.16 mg/m3, 102.4 microg/m3 and 5.31 x 10(-9) , with the reduction rates of 23.4%, 20.5%, 10.5% and -12.5%, respectively. The research on these concentration changes and the daily variations of the pollutants reveals: the concentration of PM10 is most influenced by the traffic control; the concentration of CO presents the most similar daily variation with the traffic flow; the reduction of NO2 concentration is limited, indicating the influence of other factors other than the traffic emission; the concentration of O3 increases after the traffic control, which means the traffic management measures can not abate the O3 pollution in the street. Furthermore, the comparison between the calculation results in different types of street canyons reveals that the fleet composition and street geometry impact the concentration changes. In a word, the vehicle pollution inside the streets of Beijing before the traffic control is relatively serious, as the concentrations of PM10, CO and NO2, all approach or exceed the Grade II National Air Quality Standard; the traffic control measures take effect in reducing the primary pollutants, but the secondary pollutants may increase after the traffic control.

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.

Droplet Traffic at a Simple Junction at Low Capillary Numbers

NASA Astrophysics Data System (ADS)

Engl, Wilfried; Roche, Matthieu; Colin, Annie; Panizza, Pascal; Ajdari, Armand

2005-11-01

We report that, when a train of confined droplets flowing through a channel reaches a junction, the droplets either are alternately distributed between the different outlets or all collect into the shortest one. We argue that this behavior is due to the hydrodynamic feedback of droplets in the different outlets on the selection process occurring at the junction. A “mean field” model, yielding semiquantitative results, offers a first guide to predict droplet traffic in branched networks.

JPRS Report, Science and Technology: Europe Twenty-Fourth ISATA International Symposium on Automotive Technology and Automation.

DTIC Science & Technology

1991-09-05

Traffic and Driving and Y Ishii, Oki Electric Industry, Japan " Mazda Car Communication System" Mazda Car Corporation , FRG IMPROVING TRAFFIC FLOW... Strategy to Reduce 151 Blocking-Back During Oversaturation using the Microsimulation Model Nemis" S Shepherd, Institute for Transport Studies, UK 910085...J Garber, C W Lynn and W S Ferguson, University of Virginia, USA 910087 "Ramp Metering Strategies for Motorways Incorporating Dynamic 177 Origin

Optimization design of urban expressway ramp control

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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 ...

Multiscale mobility networks and the spatial spreading of infectious diseases.

PubMed

Balcan, Duygu; Colizza, Vittoria; Gonçalves, Bruno; Hu, Hao; Ramasco, José J; Vespignani, Alessandro

2009-12-22

Among the realistic ingredients to be considered in the computational modeling of infectious diseases, human mobility represents a crucial challenge both on the theoretical side and in view of the limited availability of empirical data. To study the interplay between short-scale commuting flows and long-range airline traffic in shaping the spatiotemporal pattern of a global epidemic we (i) analyze mobility data from 29 countries around the world and find a gravity model able to provide a global description of commuting patterns up to 300 kms and (ii) integrate in a worldwide-structured metapopulation epidemic model a timescale-separation technique for evaluating the force of infection due to multiscale mobility processes in the disease dynamics. Commuting flows are found, on average, to be one order of magnitude larger than airline flows. However, their introduction into the worldwide model shows that the large-scale pattern of the simulated epidemic exhibits only small variations with respect to the baseline case where only airline traffic is considered. The presence of short-range mobility increases, however, the synchronization of subpopulations in close proximity and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multiscale framework.

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

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...

Traffic flow forecasting for intelligent transportation systems.

DOT National Transportation Integrated Search

1995-01-01

The capability to forecast traffic volume in an operational setting has been identified as a critical need for intelligent transportation systems (ITS). In particular, traffic volume forecasts will directly support proactive traffic control and accur...

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...

Probabilistic approach to damage of tunnel lining due to fire

NASA Astrophysics Data System (ADS)

Šejnoha, Jiří; Sýkora, Jan; Novotná, Eva; Šejnoha, Michal

2017-09-01

In this paper, risk is perceived as the probable damage caused by a fire in the tunnel lining. In its first part the traffic flow is described as a Markov chain of joint states consisting of a combination of trucks/buses (TB) and personal cars (PC) from adjoining lanes. The heat release rate is then taken for a measure of the fire power. The intensity λf reflecting the frequency of fires was assessed based on extensive studies carried out in Austria [1] and Italy [2, 3]. The traffic density AADT, the length of the tunnel L, the percentage of TBs, and the number of lanes are the remaining parameters characterizing the traffic flow. In the second part, a special combination of models originally proposed by Bažant and Thonguthai [4], and Künzel & Kiessl [5] for the description of transport processes in concrete at very high temperatures creates a basis for the prediction of the thickness of the spalling zone and the volume of concrete degraded by temperatures that exceed a certain temperature level. The model was validated against a macroscopic test on concrete samples placed into the furnace.

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

PubMed

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

2017-04-10

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

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

PubMed Central

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

2017-01-01

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

A Numerical Study of New Logistic Map

NASA Astrophysics Data System (ADS)

Khmou, Youssef

In this paper, we propose a new logistic map based on the relation of the information entropy, we study the bifurcation diagram comparatively to the standard logistic map. In the first part, we compare the obtained diagram, by numerical simulations, with that of the standard logistic map. It is found that the structures of both diagrams are similar where the range of the growth parameter is restricted to the interval [0,e]. In the second part, we present an application of the proposed map in traffic flow using macroscopic model. It is found that the bifurcation diagram is an exact model of the Greenberg’s model of traffic flow where the growth parameter corresponds to the optimal velocity and the random sequence corresponds to the density. In the last part, we present a second possible application of the proposed map which consists of random number generation. The results of the analysis show that the excluded initial values of the sequences are (0,1).

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...

Using Inspiration from Synaptic Plasticity Rules to Optimize Traffic Flow in Distributed Engineered Networks.

PubMed

Suen, Jonathan Y; Navlakha, Saket

2017-05-01

Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.

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 ...

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

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-05-01

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

Nuclear traffic and peloton formation in fungal networks

NASA Astrophysics Data System (ADS)

Roper, Marcus; Hickey, Patrick; Lewkiewicz, Stephanie; Dressaire, Emilie; Read, Nick

2013-11-01

Hyphae, the network of microfluidic pipes that make up a growing fungal cell, must balance their function as conduits for the transport of nuclei with other cellular functions including secretion and growth. Constant flow of nuclei may interfere with the protein traffic that enables other functions to be performed. Live-cell imaging reveals that nuclear flows are anti-congestive; that groups of nuclei flow faster than single nuclei, and that nuclei sweep through the colony in dense clumps. We call these clumps pelotons, after the term used to describe groups of cycle racers slip-streaming off each other. Because of the pelotons, individual hyphae transport nuclei only intermittently, producing long intervals in which hyphae can perform their other functions. Modeling reveals how pelotons are created by interactions between nuclei and the hyphal cytoskeleton, and reveal the control that the fungus enjoys over peloton assembly and timing.

Decentralized and Tactical Air Traffic Flow Management

NASA Technical Reports Server (NTRS)

Odoni, Amedeo R.; Bertsimas, Dimitris

1997-01-01

This project dealt with the following topics: 1. Review and description of the existing air traffic flow management system (ATFM) and identification of aspects with potential for improvement. 2. Identification and review of existing models and simulations dealing with all system segments (enroute, terminal area, ground) 3. Formulation of concepts for overall decentralization of the ATFM system, ranging from moderate decentralization to full decentralization 4. Specification of the modifications to the ATFM system required to accommodate each of the alternative concepts. 5. Identification of issues that need to be addressed with regard to: determination of the way the ATFM system would be operating; types of flow management strategies that would be used; and estimation of the effectiveness of ATFM with regard to reducing delay and re-routing costs. 6. Concept evaluation through identification of criteria and methodologies for accommodating the interests of stakeholders and of approaches to optimization of operational procedures for all segments of the ATFM system.

Keep Your Distance! Using Second-Order Ordinary Differential Equations to Model Traffic Flow

ERIC Educational Resources Information Center

McCartney, Mark

2004-01-01

A simple mathematical model for how vehicles follow each other along a stretch of road is presented. The resulting linear second-order differential equation with constant coefficients is solved and interpreted. The model can be used as an application of solution techniques taught at first-year undergraduate level and as a motivator to encourage…

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.

Microscale traffic simulation and emission estimation in a heavily trafficked roundabout in Madrid (Spain).

PubMed

Quaassdorff, Christina; Borge, Rafael; Pérez, Javier; Lumbreras, Julio; de la Paz, David; de Andrés, Juan Manuel

2016-10-01

This paper presents the evaluation of emissions from vehicle operations in a domain of 300m×300m covering a complex urban roundabout with high traffic density in Madrid. Micro-level simulation was successfully applied to estimate the emissions on a scale of meters. Two programs were used: i) VISSIM to simulate the traffic on the square and to compute velocity-time profiles; and ii) VERSIT+micro through ENVIVER that uses VISSIM outputs to compute the related emissions at vehicle level. Data collection was achieved by a measurement campaign obtaining empirical data of vehicle flows and traffic intensities. Twelve simulations of different traffic situations (scenarios) were conducted, representing different hours from several days in a week and the corresponding NOX and PM10 emissions were estimated. The results show a general reduction on average speeds for higher intensities due to braking-acceleration patterns that contribute to increase the average emission factor and, therefore, the total emissions in the domain, especially on weekdays. The emissions are clearly related to traffic volume, although maximum emission scenario does not correspond to the highest traffic intensity due to congestion and variations in fleet composition throughout the day. These results evidence the potential that local measures aimed at alleviating congestion may have in urban areas to reduce emissions. In general, scenario-averaged emission factors estimated with the VISSIM-VERSIT+micro modelling system fitted well those from the average-speed model COPERT, used as a preliminary validation of the results. The largest deviations between these two models occur in those scenarios with more congestion. The design and resolution of the microscale modelling system allow to reflect the impact of actual traffic conditions on driving patterns and related emissions, making it useful for the design of mitigation measures for specific traffic hot-spots. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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...

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

Modeling carbon emissions from urban traffic system using mobile monitoring.

PubMed

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

2017-12-01

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

Modeling pedestrian gap crossing index under mixed traffic condition.

PubMed

Naser, Mohamed M; Zulkiple, Adnan; Al Bargi, Walid A; Khalifa, Nasradeen A; Daniel, Basil David

2017-12-01

There are a variety of challenges faced by pedestrians when they walk along and attempt to cross a road, as the most recorded accidents occur during this time. Pedestrians of all types, including both sexes with numerous aging groups, are always subjected to risk and are characterized as the most exposed road users. The increased demand for better traffic management strategies to reduce the risks at intersections, improve quality traffic management, traffic volume, and longer cycle time has further increased concerns over the past decade. This paper aims to develop a sustainable pedestrian gap crossing index model based on traffic flow density. It focusses on the gaps accepted by pedestrians and their decision for street crossing, where (Log-Gap) logarithm of accepted gaps was used to optimize the result of a model for gap crossing behavior. Through a review of extant literature, 15 influential variables were extracted for further empirical analysis. Subsequently, data from the observation at an uncontrolled mid-block in Jalan Ampang in Kuala Lumpur, Malaysia was gathered and Multiple Linear Regression (MLR) and Binary Logit Model (BLM) techniques were employed to analyze the results. From the results, different pedestrian behavioral characteristics were considered for a minimum gap size model, out of which only a few (four) variables could explain the pedestrian road crossing behavior while the remaining variables have an insignificant effect. Among the different variables, age, rolling gap, vehicle type, and crossing were the most influential variables. The study concludes that pedestrians' decision to cross the street depends on the pedestrian age, rolling gap, vehicle type, and size of traffic gap before crossing. The inferences from these models will be useful to increase pedestrian safety and performance evaluation of uncontrolled midblock road crossings in developing countries. Copyright © 2017 National Safety Council and 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.

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 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.

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 ...

Optimizing location of manufacturing industries in the context of economic globalization: A bi-level model based approach

NASA Astrophysics Data System (ADS)

Wu, Shanhua; Yang, Zhongzhen

2018-07-01

This paper aims to optimize the locations of manufacturing industries in the context of economic globalization by proposing a bi-level programming model which integrates the location optimization model with the traffic assignment model. In the model, the transport network is divided into the subnetworks of raw materials and products respectively. The upper-level model is used to determine the location of industries and the OD matrices of raw materials and products. The lower-level model is used to calculate the attributes of traffic flow under given OD matrices. To solve the model, the genetic algorithm is designed. The proposed method is tested using the Chinese steel industry as an example. The result indicates that the proposed method could help the decision-makers to implement the location decisions for the manufacturing industries effectively.

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...