An extended car-following model by considering the optimal velocity difference and electronic throttle angle

2019 ◽  
Vol 535 ◽  
pp. 122216
Author(s):  
Chunyue Yan ◽  
Hongxia Ge ◽  
Rongjun Cheng
Keyword(s):  
Velocity Difference ◽  
Electronic Throttle ◽  
Optimal Velocity ◽  
Car Following ◽  
Car Following Model

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.

scholarly journals Car-following Model of Connected Cruise Control Vehicles to Mitigate Traffic Oscillations

2019 ◽  
Vol 31 (6) ◽  
pp. 603-610
Author(s):  
Yanyan Qin ◽  
Hao Wang ◽  
Quan Chen ◽  
Bin Ran
Keyword(s):  
Cruise Control ◽  
Difference Model ◽  
Velocity Difference ◽  
Electronic Throttle ◽  
Car Following ◽  
Time Simulation ◽  
Proposed Model ◽  
Car Following Model ◽  
Traffic Oscillations ◽  
Better Than

With the aim of mitigating traffic oscillations, this paper extends a car-following model for Connected Cruise Control (CCC) systems by considering electronic throttle angles of multiple cars ahead. The linear stability condition of the proposed model is derived and numerical simulations are performed. It has been found that the proposed model is prominently better than the previous model, i.e. full velocity difference model, from the perspective of mitigating traffic oscillations. Additionally, the proposed model can also reduce fuel consumption, emissions, i.e. CO, HC and NOX, safety risk, and improve driving comfort at the same time. Simulation results suggest that the CCC car-following control design should consider the effect of multiple electronic throttle angles from the preceding cars.

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.

Nonlinear analysis of a new car-following model accounting for the global average optimal velocity difference

2016 ◽  
Vol 30 (27) ◽  
pp. 1650327 ◽  
Author(s):  
Guanghan Peng ◽  
Weizhen Lu ◽  
Hongdi He
Keyword(s):  
Nonlinear Analysis ◽  
Traffic Flow ◽  
Stable Region ◽  
Velocity Difference ◽  
Optimal Velocity ◽  
Car Following ◽  
Global Average ◽  
Car Following Model ◽  
The Stability ◽  
Difference Effect

In this paper, a new car-following model is proposed by considering the global average optimal velocity difference effect on the basis of the full velocity difference (FVD) model. We investigate the influence of the global average optimal velocity difference on the stability of traffic flow by making use of linear stability analysis. It indicates that the stable region will be enlarged by taking the global average optimal velocity difference effect into account. Subsequently, the mKdV equation near the critical point and its kink–antikink soliton solution, which can describe the traffic jam transition, is derived from nonlinear analysis. Furthermore, numerical simulations confirm that the effect of the global average optimal velocity difference can efficiently improve the stability of traffic flow, which show that our new consideration should be taken into account to suppress the traffic congestion for car-following theory.

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 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.

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.

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