A novel car-following model by sharing cooperative information transmission delayed effect under V2X environment and its additional energy consumption

2021 ◽  
Author(s):  
Peng Guang-Han ◽  
Jia Teti ◽  
Kuang Hua ◽  
Tan Hui-Li ◽  
Chen Tao
Keyword(s):  
Energy Consumption ◽  
Information Transmission ◽  
Mkdv Equation ◽  
Hysteresis Phenomenon ◽  
Delayed Effect ◽  
Additional Energy ◽  
Car Following ◽  
Car Following Model ◽  
Simulation Results ◽  
The Stability

Abstract A novel car-following model is offered based on the cooperative information transmission delayed effect involving headway and velocity under V2X environment. The stability conditions and mKdV equation of the new model are obtained via the linear and nonlinear analysis. Through numerical simulation, the variation trend of headway and hysteresis phenomenon are researched. At the same time, we investigated the additional energy consumption of the vehicle during acceleration. In brief, theoretical analysis and simulation results confirm that the new car-following model based on the cooperative information transmission delayed effect can improve traffic stability and reduce additional energy consumption.

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.

scholarly journals Stability Analysis of Train Movement with Uncertain Factors

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
JingJing Ye ◽  
KePing Li ◽  
XueDong Jiang
Keyword(s):  
Relaxation Time ◽  
Stability Analysis ◽  
Fuzzy Theory ◽  
Traffic Model ◽  
Optimal Velocity ◽  
Car Following ◽  
Proposed Model ◽  
Car Following Model ◽  
Simulation Results ◽  
The Stability

We propose a new traffic model which is based on the traditional OV (optimal velocity) car-following model. Here, some realistic factors are regarded as uncertain quantity, such as the headway distance. Our aim is to analyze and discuss the stability of car-following model under the constraint of uncertain factors. Then, according to the principle of expected value in fuzzy theory, an improved OV traffic model is constructed. Simulation results show that our proposed model can avoid collisions effectively under uncertain environment, and its stability can also be improved. Moreover, we discuss its stability as some parameters change, such as the relaxation time.

Fractional order car-following model and its simulation

2018 ◽  
Vol 32 (19) ◽  
pp. 1850213 ◽  
Author(s):  
Yong Zhang ◽  
Jie-Mei Zhao
Keyword(s):  
Fractional Order ◽  
Order Differential Equation ◽  
Fractional Order Differential Equation ◽  
Optimal Velocity ◽  
Car Following ◽  
Car Following Model ◽  
Memory Characteristic ◽  
Simulation Results ◽  
The Stability ◽  
Caputo Fractional Order Derivative

In order to depict the effect of driver’s memory on car-following behavior, a new kind of car-following model is proposed by using fractional order differential equation in this paper. Its dynamic equation is defined by Caputo fractional order derivative. And the order of derivative is the measurement of driver’s memory. In addition, discrete formulas of the position and velocity of the new model are given. The Optimal Velocity (OV) model is taken as an example to introduce how to get the fractional order car-following model from an ordinary model. The simulation results show that the Fractional Order Optimal Velocity (FOOV) model is more stable, and it can avoid unrealistic acceleration values of the OV model in the cases of starting and braking processes. Moreover, magnitudes of the speed and headway fluctuation of the FOOV model with a suitable order are smaller than those of the OV model. This indicates that the memory characteristic of drivers increases the stability of 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.

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.

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.

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

2017 ◽  
Vol 28 (04) ◽  
pp. 1750046 ◽  
Author(s):  
Da-Wei Liu ◽  
Zhong-Ke Shi ◽  
Wen-Huan Ai
Keyword(s):  
Density Wave ◽  
Mkdv Equation ◽  
Difference Model ◽  
New Model ◽  
Car Following ◽  
Car Following Model ◽  
Vehicle Motion ◽  
Starting Process ◽  
The Stability ◽  
Traffic Behavior

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.

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