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.

scholarly journals An Extended Car-Following Model at Signalised Intersections

2018 ◽  
Vol 2018 ◽  
pp. 1-26 ◽  
Author(s):  
Hongxing Zhao ◽  
Ruichun He ◽  
Changxi Ma
Keyword(s):  
Velocity Model ◽  
Measured Data ◽  
Velocity Difference ◽  
Optimal Velocity ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Trajectory Simulation ◽  
Car Following Model ◽  
Point Data ◽  
Isolated Point

An extended car-following model is proposed on the basis of experimental analysis to improve the performance of the traditional car-following model and simulate a microscopic car-following behaviour at signalised intersections. The new car-following model considers vehicle gather and dissipation. Firstly, the parameters of optimal velocity, generalised force and full velocity difference models are calibrated by measured data, and the problems and causes of the three models are analysed with a realistic trajectory simulation as an evaluation criterion. Secondly, an extended car-following model based on the full optimal velocity model is proposed by considering the vehicle gather and dissipation. The parameters of the new car-following model are calibrated by the measured data, and the model is compared with comparative models on the basis of isolated point data and the entire car-following process. Simulation results show that the optimal velocity, generalised force, and full velocity difference models cannot effectively simulate a microscopic car-following behaviour at signalised intersections, whereas the new car-following model can avoid a collision and has a high fit degree for simulating the measured data of the car-following behaviour at signalised intersections.

Impact of interruption probability of the current optimal velocity on traffic stability for car-following model

2021 ◽  
Author(s):  
Xiaoqin Li ◽  
Yanyan Zhou ◽  
Guanghan Peng
Keyword(s):  
Stable Condition ◽  
Velocity Model ◽  
Mkdv Equation ◽  
The Self ◽  
Optimal Velocity ◽  
Traffic Jam ◽  
Traffic System ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Car Following Model

Traffic interruption is one of the important factors resulting in traffic jam. Therefore, a new optimal velocity model is established involving the traffic interruption probability for self-expected velocity. Linear stable condition and mKdV equation are deduced with regard to the self-interruption probability of the current optimal velocity from linear stable analysis and nonlinear analysis, respectively. Moreover, numerical simulation reveals that the traffic self-interruption probability of the current optimal velocity can increase traffic stability, which certifies that the traffic self-interruption probability of the current optimal velocity plays important influences on traffic system.

Heterogeneous Drivers Car-Following Model and Stability Analysis

2012 ◽  
Vol 253-255 ◽  
pp. 1631-1636
Author(s):  
Jing Shan Pan ◽  
Li Dong Zhang
Keyword(s):  
Stability Analysis ◽  
Traffic Flow ◽  
Flow Characteristics ◽  
Velocity Model ◽  
Sensitivity Factor ◽  
Past Study ◽  
Optimal Velocity ◽  
Flow Models ◽  
Car Following ◽  
Optimal Velocity Model

Optimal Velocity Model (OVM) is one of the typical car-following traffic flow models. The driver’s sensitivity factor in OVM is always constant in the past study, which does not fully comply with practical traffic flow characteristics. To gain a more actual and objective model, we propose a kind of heterogeneous drivers car-following optimal velocity model, i.e. HDOVM. In this model, the constant driver’s parameter is substituted with driver type function, and every car in the queue has a corresponding value. After stability analysis with Laplace transform state space method, we make many types cars in the traffic queue numerical simulation to prove our supposition , the simulation results after many times show that the HDOVM model is more practical than traditional ones. Considering the diversity of traffic flow composition should be one of the major factors to find out the reason of traffic jam.

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 An Improved Car-Following Model considering Desired Safety Distance and Heterogeneity of Driver’s Sensitivity

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Lei Zhang ◽  
Shengrui Zhang ◽  
Bei Zhou ◽  
Shuaiyang Jiao ◽  
Yan Huang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Dynamic Performance ◽  
Velocity Function ◽  
Optimal Velocity ◽  
Car Following ◽  
Safety Distance ◽  
Proposed Model ◽  
Car Following Model ◽  
Optimal Velocity Function

We investigate the dynamic performance of traffic flow using a modified optimal velocity car-following model. In the car-following scenarios, the following vehicle must continuously adjust the following distance to the preceding vehicle in real time. A new optimal velocity function incorporating the desired safety distance instead of a preset constant is presented first to describe the abovementioned car-following behavior dynamically. The boundary conditions of the new optimal velocity function are theoretically analyzed. Subsequently, we propose an improved car-following model by combining the heterogeneity of driver’s sensitivity based on the new optimal velocity function and previous car-following model. The stability criterion of the improved model is obtained through the linear analysis method. Finally, numerical simulation is performed to explore the effect of the desired safety distance and the heterogeneity of driver’s sensitivity on the traffic flow. Results show that the proposed model has considerable effects on improving traffic stability and suppressing traffic congestion. Furthermore, the proposed model is compatible with the heterogeneity of driver’s sensitivity and can enhance the average velocity of traffic flow compared with the conventional model. In conclusion, the dynamic performance of traffic flow can be improved by considering the desired safety distance and the heterogeneity of driver’s sensitivity in the car-following model.

A New Car-Following Model with the Consideration of the Leader’s Acceleration

2015 ◽  
Vol 738-739 ◽  
pp. 489-492
Author(s):  
Tong Zhou ◽  
Yu Xuan Li ◽  
Zhan Wei Bai
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Linear Stability ◽  
Linear Stability Theory ◽  
Difference Model ◽  
Velocity Difference ◽  
Optimal Velocity ◽  
New Model ◽  
Car Following ◽  
Car Following Model

Based on the optimal velocity difference model (for short, OVDM) proposed by Peng et al., a new car-following model is presented by considering the leading cars’ acceleration. The linear stability condition of the new model is obtained by using the linear stability theory. Numerical simulation shows that the new model can avoid the disadvantage of negative velocity occurred in the OVDM by adjusting the coefficient of the leaders acceleration and can stabilize traffic flow more effectively.

STABILITY AND KINK–ANTIKINK SOLITON SOLUTION FOR TOTAL GENERALIZED OPTIMAL VELOCITY MODEL

2008 ◽  
Vol 19 (09) ◽  
pp. 1321-1335 ◽  
Author(s):  
WEN-XING ZHU ◽  
LEI JIA
Keyword(s):  
Soliton Solution ◽  
Kdv Equation ◽  
Velocity Model ◽  
Linear Analysis ◽  
Analysis Method ◽  
Optimal Velocity ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Car Following Model ◽  
Differential Difference Equation

We proposed a new car-following model named as total generalized optimal velocity model (TGOVM) based on the analysis of the previous models. TGOVM is superior to the previous models in stabilizing the uniform traffic flow by considering all the front influencing factors: headways, relative velocities, and interactions. The linear analysis result showed its superiority to the GOVM, FLOVM, and FLRVM. The nonlinear analysis method is adopted to analyze this model, which described by a differential-difference equation. The modified Korteweg-de Vries (KdV) equation is derived and the kink-antikink soliton solution is obtained near the critical point. The simulation results show that the stabilization is enhanced by the improvement.

scholarly journals Modeling for Micro Traffic Flow with the Consideration of Lateral Vehicle’s Influence

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Da-wei Liu ◽  
Zhong-ke Shi ◽  
Wen-Huan Ai
Keyword(s):  
Traffic Flow ◽  
Absolute Error ◽  
Velocity Model ◽  
Error Reduction ◽  
Driving Behavior ◽  
Actual Behavior ◽  
Cooperative Model ◽  
Optimal Velocity ◽  
Car Following ◽  
Optimal Velocity Model

In order to make the car-following model describe the driving behavior of vehicle on urban road more accurately, existing car-following models are simulated using measured traffic data. According to the analysis of the simulation result, two new improved car-following models based on the optimal velocity model (OVM) are proposed in this paper. The lateral vehicle’s influence is introduced as the influence factor of driving behavior. By using of linear stability analysis, stability conditions of improved car-following models are obtained. Nonlinear analysis is carried out to investigate the traffic performances near the critical point. The result of numerical simulation indicates that stability of traffic flow is under the influence from lateral vehicle; the lesser the influence, the greater the stability. New cooperative car-following models are verified by the traffic flow data collected in Xi’an city. It is shown that compared with the optimal velocity model, the simulation result of the second cooperative model, respectively, gets 62.89% unbiased variance reduction, 66.39% maximum absolute error reduction, and 33.4% minimum absolute error reduction. Therefore, the second cooperative model is more suitable to describe the vehicle’s actual behavior in car-following state.

scholarly journals Weakly nonlinear analysis for car-following model with consideration of cooperation and time delays

2018 ◽  
Vol 32 (21) ◽  
pp. 1850241 ◽  
Author(s):  
Dong Chen ◽  
Dihua Sun ◽  
Min Zhao ◽  
Yuchu He ◽  
Hui Liu
Keyword(s):  
Traffic Flow ◽  
Linear Stability ◽  
Time Delays ◽  
Kdv Equation ◽  
Cooperative Behavior ◽  
Optimal Velocity ◽  
Flow Models ◽  
Car Following ◽  
Cooperative Driving ◽  
Car Following Model

In traffic systems, cooperative driving has attracted the researchers’ attention. A lot of works attempt to understand the effects of cooperative driving behavior and/or time delays on traffic flow dynamics for specific traffic flow models. This paper is a new attempt to investigate analyses of linear stability and weak nonlinearity for the general car-following model with consideration of cooperation and time delays. We derive linear stability condition and study how the combinations of cooperation and time delays affect the stability of traffic flow. Burgers’ equation and Korteweg de Vries’ (KdV) equation for car-following model considering cooperation and time delays are derived. Their solitary wave solutions and constraint conditions are concluded. We investigate the property of cooperative optimal velocity (OV) model which estimates the combinations of cooperation and time delays about the evolution of traffic waves using both analytic and numerical methods. The results indicate that delays and cooperation are model-dependent, and cooperative behavior could inhibit the stabilization of traffic flow. Moreover, delays of sensing relative motion are easy to trigger the traffic waves; delays of sensing host vehicle are beneficial to relieve the instability effect to a certain extent.

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