scholarly journals An Extended Car-Following Model Based on Visual Angle and Electronic Throttle Effect

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2879
Author(s):  
Hongxia Ge ◽  
Siteng Li ◽  
Chunyue Yan
Keyword(s):  
Visual Angle ◽  
Mkdv Equation ◽  
Ginzburg Landau ◽  
Electronic Throttle ◽  
Precise Control ◽  
Car Following ◽  
Preceding Vehicle ◽  
Car Following Model ◽  
The Stability ◽  
Parts Manufacturing

With the continuous advancement of electronic technology, auto parts manufacturing institutions are gradually applying electronic throttles to automobiles for precise control. Based on the visual angle model (VAM), a car-following model considering the electronic throttle angle of the preceding vehicle is proposed. The stability conditions are obtained through linear stability analysis. By means of nonlinear analysis, the time-dependent Ginzburg–Landau (TDGL) equation is derived first, and then the modified Korteweg-de-Vries (mKdV) equation is derived. The relationship between the two is thus obtained. Finally, in the process of numerical simulations and exploration, it is shown how the visual angle and electronic throttle affect the stability of traffic flow. The simulation results in MATLAB software verify the validity of the model, indicating that the visual angle and electronic throttle can improve traffic stability.

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

2018 ◽  
Vol 32 (01) ◽  
pp. 1750366 ◽  
Author(s):  
Zhizhan Jin ◽  
Zhipeng Li ◽  
Rongjun Cheng ◽  
Hongxia Ge
Keyword(s):  
Energy Consumption ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Density Wave ◽  
Mkdv Equation ◽  
Ginzburg Landau ◽  
Car Following ◽  
Car Following Model ◽  
The Stability ◽  
Improved Model

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.

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.

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.

Time-Dependent Ginzburg-Landau Equation in Car Following Model Considering the Traffic Interruption Probability

2012 ◽  
Vol 198-199 ◽  
pp. 843-847
Author(s):  
Yi Qiang Zhang ◽  
Rong Jun Cheng ◽  
Hong Xia Ge
Keyword(s):  
Landau Equation ◽  
Reductive Perturbation Method ◽  
Time Dependent ◽  
Ginzburg Landau ◽  
Car Following ◽  
Second Derivatives ◽  
Spinodal Line ◽  
Car Following Model ◽  
The Stability ◽  
Derivatives Of

This paper focuses on a car-following model which involves the effects of traffic interruption probability. The stability condition of the model is obtained through the linear stability analysis. The time-dependent Ginzburg-Landau (TDGL) equation is derived by the reductive perturbation method. In addition, the coexisting curve and the spinodal line are obtained by the first and second derivatives of the thermodynamic potential. The analytical results show that the traffic interruption probability indeed has an influence on driving behaviour.

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.

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.

A Car-Following Model Considering Effects of Weather and Road Conditions

2014 ◽  
Vol 488-489 ◽  
pp. 1289-1294
Author(s):  
Lu Jing ◽  
Peng Jun Zheng
Keyword(s):  
Vries Equation ◽  
Kdv Equation ◽  
Mkdv Equation ◽  
Reductive Perturbation Method ◽  
Neutral Stability ◽  
Traffic Jam ◽  
Car Following ◽  
The Kdv Equation ◽  
Car Following Model ◽  
The Stability

In this paper, a modified car-following model is proposed, in which, the weather and road conditions are taken into account. The stability condition of the model is obtained by using the control theory method. We investigated the property of the model using linear and nonlinear analyses. The Kortewegde Vries equation near the neutral stability line and the modified Kortewegde Vries equation around the critical point are derived by applying the reductive perturbation method. The traffic jam could be thus described by the KdV soliton and the kinkanti-kink soliton for the KdV equation and mKdV equation, respectively. Numerical simulations are carried out to verify the model, and good results are obtained with the new model.

scholarly journals A New Car-Following Model considering Driving Characteristics and Preceding Vehicle’s Acceleration

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Yong Zhang ◽  
Ping Ni ◽  
Minwei Li ◽  
Hao Liu ◽  
Baocai Yin
Keyword(s):  
Traffic Flow ◽  
Clustering Algorithm ◽  
Traffic Data ◽  
Velocity Difference ◽  
Car Following ◽  
The Past ◽  
Preceding Vehicle ◽  
Car Following Model ◽  
The Stability ◽  
Anticipation Effects

In the past decades, many improved car-following models based on the full velocity difference (FVD) model have been developed. But these models do not consider the acceleration of leading vehicle. Some of them consider individual anticipation behavior of drivers, but they either do not quantitatively determine the types of driving or artificially divide the driving types rather than deriving them from actual traffic data. In this paper, driver’s driving styles are firstly categorized based on actual traffic data via data mining and clustering algorithm. Secondly, a new car-following model based on FVD model is developed, taking into account individual anticipation effects and the acceleration of leading vehicle. The effect of driving characteristics and leading vehicle’s acceleration on car-following behavior is further analyzed via numerical simulation. The results show that considering the acceleration of preceding vehicle in the model improves the stability of traffic flow and different driving characteristics have different influence on the stability of traffic flow.

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