scholarly journals An Extended Car-Following Model Considering Generalized Preceding Vehicles in V2X Environment

2020 ◽  
Vol 12 (12) ◽  
pp. 216
Author(s):  
Junyan Han ◽  
Jinglei Zhang ◽  
Xiaoyuan Wang ◽  
Yaqi Liu ◽  
Quanzheng Wang ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Neutral Stability ◽  
State Information ◽  
Car Following ◽  
Motion State ◽  
Car Following Model ◽  
The Impact ◽  
Good Agreement

Vehicle-to-everything (V2X) technology will significantly enhance the information perception ability of drivers and assist them in optimizing car-following behavior. Utilizing V2X technology, drivers could obtain motion state information of the front vehicle, non-neighboring front vehicle, and front vehicles in the adjacent lanes (these vehicles are collectively referred to as generalized preceding vehicles in this research). However, understanding of the impact exerted by the above information on car-following behavior and traffic flow is limited. In this paper, a car-following model considering the average velocity of generalized preceding vehicles (GPV) is proposed to explore the impact and then calibrated with the next generation simulation (NGSIM) data utilizing the genetic algorithm. The neutral stability condition of the model is derived via linear stability analysis. Numerical simulation on the starting, braking and disturbance propagation process is implemented to further study features of the established model and traffic flow stability. Research results suggest that the fitting accuracy of the GPV model is 40.497% higher than the full velocity difference (FVD) model. Good agreement between the theoretical analysis and the numerical simulation reveals that motion state information of GPV can stabilize traffic flow of following vehicles and thus alleviate traffic congestion.

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.

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 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.

Effect of current vehicle’s interruption on traffic stability in cooperative car-following theory

2017 ◽  
Vol 31 (34) ◽  
pp. 1750317 ◽  
Author(s):  
Geng Zhang ◽  
Hui Liu
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Density Wave ◽  
Negative Influence ◽  
Mkdv Equation ◽  
Traffic Density ◽  
New Model ◽  
Car Following ◽  
Car Following Model ◽  
The Impact

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.

scholarly journals A New Car-Following Model with Consideration of Dynamic Safety Distance

2018 ◽  
Vol 2018 ◽  
pp. 1-5
Author(s):  
Tao Wang ◽  
Jing Zhang ◽  
Guangyao Li ◽  
Keyu Xu ◽  
Shubin Li
Keyword(s):  
Traffic Flow ◽  
Velocity Model ◽  
Safe Distance ◽  
Optimal Velocity ◽  
New Model ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Safety Distance ◽  
Car Following Model ◽  
The Impact

In the traditional optimal velocity model, safe distance is usually a constant, which, however, is not representative of actual traffic conditions. This paper attempts to study the impact of dynamic safety distance on vehicular stream through a car-following model. Firstly, a new car-following model is proposed, in which the traditional safety distance is replaced by a dynamic term. Then, the phase diagram in the headway, speed, and sensitivity spaces is given to illustrate the impact of a variable safe distance on traffic flow. Finally, numerical methods are conducted to examine the performance of the proposed model with regard to two aspects: compared with the optimal velocity model, the new model can suppress traffic congestion effectively and, for different safety distances, the dynamic safety distance can improve the stability of vehicular stream. Simulation results suggest that the new model is able to enhance traffic flow stability.

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 The Feasibility of Opening Communities -- Based on the Wiedemann Car-Following Model

2018 ◽  
Vol 11 (3) ◽  
pp. 57
Author(s):  
Xiao-Yan Cao ◽  
Bing-Qian Liu ◽  
Bao-Ru Pan ◽  
Yuan-Biao Zhang
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Gated Communities ◽  
Urban Traffic ◽  
Average Delay ◽  
Traffic Demand ◽  
Car Following ◽  
Car Following Model ◽  
Urbanization In China ◽  
The Impact

With the accelerating development of urbanization in China, the increasing traffic demand and large scale gated communities have aggravated urban traffic congestion. This paper studies the impact of communities opening on road network structure and the surrounding road capacity. Firstly, we select four indicators, namely average speed, vehicle flow, average delay time, and queue length, to measure traffic capacity. Secondly, we establish the Wiedemann car-following model, then use VISSIM software to simulate the traffic conditions of surrounding roads of communities. Finally, we take Shenzhen as an example to simulate and compare the four kinds of gated communities, axis, centripetal and intensive layout, and we also analyze the feasibility of opening communities.

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.

Sign in / Sign up

Export Citation Format

Share Document