Car-following model of connected and autonomous vehicles considering both average headway and electronic throttle angle

2021 ◽  
pp. 2150257
Author(s):  
Liang Chen ◽  
Yun Zhang ◽  
Kun Li ◽  
Qiaoru Li ◽  
Qiang Zheng
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Flow Simulation ◽  
Electronic Throttle ◽  
Car Following ◽  
Traffic Efficiency ◽  
Angle Difference ◽  
Car Following Model ◽  
The Stability

The connected and automated vehicle (CAV) is regarded as an effective way to improve traffic efficiency and safety, which can utilize vehicle-to-vehicle (V2V) communication technology to obtain real-time status information from multiple preceding vehicles. In view of the car-following characteristic of CAV in a V2V communications environment, an extended car-following model AHT-FVD is proposed which takes both average headway and electronic throttle angle difference into account. The stability of this model is examined via linear stability analysis. It is found that the proposed model has a larger stability region than both the full velocity difference (FVD) model and throttle-based FVD (T-FVD) model. Namely, this AHT-FVD model can effectively stabilize traffic flow and alleviate traffic congestion in theory. Moreover, a series of numerical simulations are carried out to explore how average headway together with electronic throttle angle difference influences the stability of traffic flow. Simulation results show that increasing either the average headway weight or the electronic throttle angle difference control signal coefficients can yield higher traffic flow stability. Simulation result is highly consistent with theoretical analysis.

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.

scholarly journals A New Continuum Model considering Driving Behaviors and Electronic Throttle Effect on a Gradient Highway

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Yulei Jiao ◽  
Rongjun Cheng ◽  
Hongxia Ge
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Continuum Model ◽  
Density Wave ◽  
Linear Stability Theory ◽  
Flow Density ◽  
Neutral Stability ◽  
Electronic Throttle ◽  
Car Following ◽  
Car Following Model

In order to explore the potential impact of sloping road on traffic flow, an improved car-following model considering electronic throttle (ET) dynamics and driver’s driving characteristics on slope is proposed. Based on the improved car-following model, a new continuum model is established through the conversion relationship between microscopic variables and macroscopic variables. Firstly, the stability condition of the model is obtained by using the linear stability theory, after that the evolution process of traffic flow density wave near the neutral stability curve is studied by using the nonlinear analysis method, and we also get the improved KdV-Burgers equation. At the same time, numerical experiments and experimental verification of the model are carried out; the theoretical analysis and numerical results show that the ET effect and aggressive driving of drivers play an important role in alleviating traffic congestion to a certain extent.

A Control Method for Car Following Model Considering Changing Behaviors

2012 ◽  
Vol 198-199 ◽  
pp. 954-957
Author(s):  
Xiang Pei Meng ◽  
Rong Jun Cheng ◽  
Hong Xia Ge
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Control Method ◽  
Velocity Difference ◽  
Lane Changing ◽  
Traffic System ◽  
Car Following ◽  
Congested Traffic ◽  
Car Following Model ◽  
The Stability

We propose a simple control method to suppress two-lane traffic congestion for full velocity difference (for short, FVD) car-following model. The influence of lane changing behaviors is also studied in the stability of two-lane traffic flow under the boundary condition, and the friction interference which is from the neighbor lane has been taken into account. We derive the stability conditions by the control method. The feedback signals, which include vehicular information from both lanes, acting on the two-lane traffic system have been extended to the FVD car-following model. Theoretically, lane changing behaviors can break the stability of two-lane traffic flow and aggravate traffic perturbation, but it is proven that the congested traffic in two-lane traffic flow could be suppressed by using this control method.

An extended car-following model integrating average speed and electronic throttle dynamics of multiple preceding vehicles

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shihao Li ◽  
Rongjun Cheng ◽  
Hongxia Ge ◽  
Pengjun Zheng
Keyword(s):  
Theoretical Analysis ◽  
Traffic Flow ◽  
Electronic Throttle ◽  
Content Type ◽  
Average Speed ◽  
The Real ◽  
Car Following ◽  
Car Following Model ◽  
The Stability ◽  
Real Traffic

Purpose The purpose of this study is to explore the influence of the electronic throttle (ET) dynamics and the average speed of multiple preceding vehicles on the stability of traffic flow. Design/methodology/approach An extended car-following model integrating the ET dynamics and the average speed of multiple preceding vehicles is presented in this paper. The novel model’s stability conditions are obtained by using the thought of control theory, and the modified Korteweg–de Vries equation is inferred in terms of the nonlinear analysis method. In addition, some simulation experiments are implemented to explore the properties of traffic flow, and the results of these experiments confirm the correctness of theoretical analysis. Findings In view of the results of theoretical analysis and numerical simulation, traffic flow will become more stable when the average speed and ET dynamics of multiple preceding vehicles are considered, and the stability of traffic flow will also be enhanced by increasing the number of preceding vehicles considered. Research limitations/implications This study leaves the factors such as the mixed traffic flow, the multilane and so on out of account in real road environment, which more or less influences the traffic flow’s stability, so the real traffic environment is not fully reflected. Originality/value There is little research integrating ET dynamics and the average velocity of multiple preceding vehicles to study the properties of traffic flow. The enhanced model constructed in this study can better reflect the real traffic, which can also give some theoretical reference for the development of connected and autonomous vehicles.

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.

An improved car-following model considering the impact of safety messages

2018 ◽  
Vol 32 (32) ◽  
pp. 1850398 ◽  
Author(s):  
Tenglong Li ◽  
Fei Hui ◽  
Xiangmo Zhao
Keyword(s):  
Traffic Congestion ◽  
Dominant Factor ◽  
Velocity Difference ◽  
Car Following ◽  
Safety Message ◽  
Warning Messages ◽  
Gray Correlation ◽  
Car Following Model ◽  
The Stability ◽  
The Impact

The existing car-following models of connected vehicles commonly lack experimental data as evidence. In this paper, a Gray correlation analysis is conducted to explore the change in driving behavior with safety messages. The data mining analysis shows that the dominant factor of car-following behavior is headway with no safety message, whereas the velocity difference between the leading and following vehicle becomes the dominant factor when warning messages are received. According to this result, an extended car-following model considering the impact of safety messages (IOSM) is proposed based on the full velocity difference (FVD) model. The stability criterion of this new model is then obtained through a linear stability analysis. Finally, numerical simulations are performed to verify the theoretical analysis results. Both analytical and simulation results show that traffic congestion can be suppressed by safety messages. However, the IOSM model is slightly less stable than the FVD model if the average headway in traffic flow is approximately 14–20 m.

scholarly journals An Extended Car-Following Model considering the Driver’s Desire for Smooth Driving and Self-Stabilizing Control with Velocity Uncertainty

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Shihao Li ◽  
Ting Wang ◽  
Rongjun Cheng ◽  
Hongxia Ge
Keyword(s):  
Traffic Flow ◽  
Linear Stability ◽  
Traffic Congestion ◽  
The Self ◽  
Historical Time ◽  
Velocity Data ◽  
Car Following ◽  
Stabilizing Control ◽  
Car Following Model ◽  
Time Gap

In this paper, an extended car-following model with consideration of the driver’s desire for smooth driving and the self-stabilizing control in historical velocity data is constructed. Moreover, for better reflecting the reality, we also integrate the velocity uncertainty into the new model to analyze the internal characteristics of traffic flow in situation where the historical velocity data are uncertain. Then, the model’s linear stability condition is inferred by utilizing linear stability analysis, and the modified Korteweg-de Vries (mKdV) equation is also obtained to depict the evolution properties of traffic congestion. According to the theoretical analysis, we observe that the degree of traffic congestion is alleviated when the control signal is considered, and the historical time gap and the velocity uncertainty also play a role in affecting the stability of traffic flow. Finally, some numerical simulation experiments are implemented and the experiments’ results demonstrate that the control signals including the self-stabilizing control, the driver’s desire for smooth driving, the historical time gap, and the velocity uncertainty are of avail to improve the traffic jam, which are consistent with the theoretical analytical results.

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.

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