scholarly journals An Improved Car-Following Model Accounting for Impact of Strong Wind

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Dawei Liu ◽  
Zhongke Shi ◽  
Wenhuan Ai
Keyword(s):  
Fuel Consumption ◽  
Traffic Flow ◽  
Influence Factor ◽  
Driving Safety ◽  
Wind Condition ◽  
Strong Wind ◽  
Wind Force ◽  
Car Following ◽  
Car Following Model ◽  
The Stability

In order to investigate the effect of strong wind on dynamic characteristic of traffic flow, an improved car-following model based on the full velocity difference model is developed in this paper. Wind force is introduced as the influence factor of car-following behavior. Among three components of wind force, lift force and side force are taken into account. The linear stability analysis is carried out and the stability condition of the newly developed model is derived. Numerical analysis is made to explore the effect of strong wind on spatial-time evolution of a small perturbation. The results show that the strong wind can significantly affect the stability of traffic flow. Driving safety in strong wind is also studied by comparing the lateral force under different wind speeds with the side friction of vehicles. Finally, the fuel consumption of vehicle in strong wind condition is explored and the results show that the fuel consumption decreased with the increase of wind speed.

The effects of drivers’ aggressive characteristics on traffic stability from a new car-following model

2016 ◽  
Vol 30 (18) ◽  
pp. 1650243 ◽  
Author(s):  
Guanghan Peng ◽  
Li Qing
Keyword(s):  
Stability Analysis ◽  
Nonlinear Analysis ◽  
Traffic Flow ◽  
Linear Stability Analysis ◽  
Stable Condition ◽  
Mkdv Equation ◽  
Stable Region ◽  
Car Following ◽  
Car Following Model ◽  
The Stability

In this paper, a new car-following model is proposed by considering the drivers’ aggressive characteristics. The stable condition and the modified Korteweg-de Vries (mKdV) equation are obtained by the linear stability analysis and nonlinear analysis, which show that the drivers’ aggressive characteristics can improve the stability of traffic flow. Furthermore, the numerical results show that the drivers’ aggressive characteristics increase the stable region of traffic flow and can reproduce the evolution and propagation of small perturbation.

An Extended Car-Following Model in a Multi-Interaction Driving System

2012 ◽  
Vol 178-181 ◽  
pp. 2717-2720
Author(s):  
Man Xian Tuo
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Flow Model ◽  
Extended Model ◽  
Traffic Flow Model ◽  
Driving System ◽  
Car Following ◽  
Traffic Jams ◽  
Car Following Model ◽  
The Stability

An extended traffic flow model is proposed by introducing the multiple information of preceding cars. The linear stability condition of the extended model is obtained, which shows that the stability of traffic flow is improved by considering the interaction of preceding cars to the following car. Numerical simulation shows that the traffic jams are suppressed efficiently by taking into account the multiple information of the preceding cars.

Analysis of drivers' characteristics in car-following theory

2014 ◽  
Vol 28 (24) ◽  
pp. 1450191 ◽  
Author(s):  
Geng Zhang ◽  
Di-Hua Sun ◽  
Hui Liu ◽  
Min Zhao
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Mkdv Equation ◽  
Reductive Perturbation Method ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Car Following ◽  
Car Following Model ◽  
The Stability ◽  
The Impact

In recent years, the influence of drivers' behaviors on traffic flow has attracted considerable attention according to Transportation Cyber Physical Systems. In this paper, an extended car-following model is presented by considering drivers' timid or aggressive characteristics. The impact of drivers' timid or aggressive characteristics on the stability of traffic flow has been analyzed through linear stability theory and nonlinear reductive perturbation method. Numerical simulation shows that the propagating behavior of traffic density waves near the critical point can be described by the kink–antikink soliton of the mKdV equation. The good agreement between the numerical simulation and the analytical results shows that drivers' characteristics play an important role in traffic jamming transition.

scholarly journals Driver’s Anticipation and Memory Driving Car-Following Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Ammar Jafaripournimchahi ◽  
Lu Sun ◽  
Wusheng Hu
Keyword(s):  
Traffic Flow ◽  
Nonlinear Stability ◽  
Relative Velocity ◽  
Mkdv Equation ◽  
Signalized Intersection ◽  
Stability Conditions ◽  
Car Following ◽  
Car Following Model ◽  
Linear And Nonlinear ◽  
The Stability

We developed a new car-following model to investigate the effects of driver anticipation and driver memory on traffic flow. The changes of headway, relative velocity, and driver memory to the vehicle in front are introduced as factors of driver’s anticipation behavior. Linear and nonlinear stability analyses are both applied to study the linear and nonlinear stability conditions of the new model. Through nonlinear analysis a modified Korteweg-de Vries (mKdV) equation was constructed to describe traffic flow near the traffic near the critical point. Numerical simulation shows that the stability of traffic flow can be effectively enhanced by the effect of driver anticipation and memory. The starting and breaking process of vehicles passing through the signalized intersection considering anticipation and driver memory are presented. All results demonstrate that the AMD model exhibit a greater stability as compared to existing car-following models.

Stability analysis of car-following model on straight and curved roads considering the preceding vehicle’s velocity feedback control

2018 ◽  
Vol 32 (21) ◽  
pp. 1850238 ◽  
Author(s):  
Peng Tan ◽  
Di-Hua Sun ◽  
Dong Chen ◽  
Min Zhao ◽  
Tao Chen
Keyword(s):  
Feedback Control ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Velocity Feedback ◽  
Car Following ◽  
Car Following Model ◽  
Negative Feedback Control ◽  
The Stability ◽  
The Impact ◽  
Good Agreement

In order to reveal the impact of preceding vehicle’s velocity on traffic flow, an extended car-following model considering preceding vehicle’s velocity feedback control is proposed in this paper. The linear stability criterion of the new model is derived through control theory method and it shows that the feedback control signal impacts the stability of traffic flow. Numerical simulation results is in good agreement with the theoretical analysis, which prove that a smaller negative feedback control of the preceding vehicle’s velocity can enhance the stability of traffic flow, while a smaller positive feedback control of the preceding vehicle’s velocity can exacerbate traffic congestion. Moreover, the reaction coefficients of straight and curved road conditions also play an important role in the stability of traffic flow.

THE TDGL EQUATION FOR CAR-FOLLOWING MODEL WITH CONSIDERATION OF THE TRAFFIC INTERRUPTION PROBABILITY

2012 ◽  
Vol 23 (07) ◽  
pp. 1250053 ◽  
Author(s):  
HONG-XIA GE ◽  
YI-QIANG ZHANG ◽  
HUA KUANG ◽  
SIU-MING LO
Keyword(s):  
Traffic Flow ◽  
Reductive Perturbation Method ◽  
Ginzburg Landau ◽  
Car Following ◽  
Second Derivatives ◽  
Spinodal Line ◽  
Car Following Model ◽  
Tdgl Equation ◽  
The Stability ◽  
Derivatives Of

A car-following model which involves the effects of traffic interruption probability is further investigated. The stability condition of the model is obtained through the linear stability analysis. The reductive perturbation method is taken to derive the time-dependent Ginzburg–Landau (TDGL) equation to describe the traffic flow near the critical point. Moreover, the coexisting curve and the spinodal line are obtained by the first and second derivatives of the thermodynamic potential, respectively. The analytical results show that considering the interruption effects could further stabilize traffic flow.

scholarly journals Effects of Exchanging Battery on the Electric Vehicle’s Electricity Consumption in a Single-Lane Traffic System

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Shi-Chun Yang ◽  
Wen-Zhuang Gou ◽  
Tie-Qiao Tang ◽  
Hua-Yan Shang
Keyword(s):  
Electric Vehicle ◽  
Traffic Flow ◽  
Electric Vehicles ◽  
Electricity Consumption ◽  
Numerical Results ◽  
Traffic System ◽  
Car Following ◽  
Car Following Model ◽  
The Stability ◽  
Charging Stations

We propose a car-following model to explore the influences of exchanging battery on each vehicle’s electricity consumption under three traffic situations from the numerical perspective. The numerical results show that exchanging battery will destroy the stability of traffic flow, but the effects are related to each vehicle’s initial headway, the time that each electric vehicle exchanges the battery, the proportion of the electric vehicles that should exchange the battery, the number of charging stations, and the distance between two adjacent charging stations.

Burgers and mKdV equation for car-following model considering drivers’ characteristics on a gradient highway

2018 ◽  
Vol 32 (26) ◽  
pp. 1850314 ◽  
Author(s):  
Di-Hua Sun ◽  
Peng Tan ◽  
Dong Chen ◽  
Fei Xie ◽  
Lin-Hui Guan
Keyword(s):  
Stability Analysis ◽  
Traffic Flow ◽  
Burgers Equation ◽  
Mkdv Equation ◽  
Nonlinear Stability Analysis ◽  
Car Following ◽  
Jamming Transition ◽  
The Road ◽  
Car Following Model ◽  
The Stability

In this paper, we propose a new car-following model considering driver’s timid and aggressive characteristics on a gradient highway. Based on the control theory, the linear stability analysis of the model was conducted. It shows that the stability of traffic flow on the gradient highway varies with the drivers’ characteristics and the slope. Adopting nonlinear stability analysis, the Burgers equation and modified Korteweg–de Vries (mKdV) equation are derived to describe the triangular shock waves and kink–antikink waves, respectively. The theoretical and numerical results show that aggressive drivers tend to stabilize traffic flow but timid drivers tend to destabilize traffic flow on a gradient highway both on an uphill situation and on a downhill situation. Moreover, the slope of the road also plays an important role in traffic jamming transition.

An extended car-following model considering the low visibility in fog on a highway with slopes

2019 ◽  
Vol 30 (11) ◽  
pp. 1950090
Author(s):  
Jinhua Tan ◽  
Li Gong ◽  
Xuqian Qin
Keyword(s):  
Stability Analysis ◽  
Numerical Simulations ◽  
Traffic Flow ◽  
Linear Stability ◽  
Linear Stability Analysis ◽  
Neutral Stability ◽  
Car Following ◽  
Low Visibility ◽  
Car Following Model ◽  
The Stability

To depict the effect of low-visibility foggy weather upon traffic flow on a highway with slopes, this paper proposes an extended car-following model taking into consideration the drivers’ misjudgment of the following distance and their active reduction of the velocity. By linear stability analysis, the neutral stability curves are obtained. It is shown that under all the three road conditions: uphill, flat road and downhill, drivers’ misjudgment of the following distance will change the stable regions, while having little effect on the sizes of the stable regions. Correspondingly, drivers’ active reduction of the velocity will increase the stability. The numerical simulations agree well with the analytical results. It indicates that drivers’ misjudgment contributes to a higher velocity. Meanwhile, their active reduction of the velocity helps mitigate the influences of small perturbation. Furthermore, drivers’ misjudgment of the following distance has the greatest effect on downhill and the smallest effect on uphill, so does drivers’ active reduction of the velocity.

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