An improved car-following model considering the immediately ahead car’s velocity difference

2016 ◽  
Vol 461 ◽  
pp. 446-455 ◽  
Author(s):  
Shaowei Yu ◽  
Xiangmo Zhao ◽  
Zhigang Xu ◽  
Zhongke Shi
Keyword(s):  
Velocity Difference ◽  
Car Following ◽  
Car Following Model

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.

Non-lane-based full velocity difference car following model

2010 ◽  
Vol 389 (21) ◽  
pp. 4654-4662 ◽  
Author(s):  
Sheng Jin ◽  
Dianhai Wang ◽  
Pengfei Tao ◽  
Pingfan Li
Keyword(s):  
Velocity Difference ◽  
Car Following ◽  
Car Following Model ◽  
Lane Based

scholarly journals A Modified Car-following Model Considering Traffic Density and Acceleration of Leading Vehicle

2020 ◽  
Vol 10 (4) ◽  
pp. 1268
Author(s):  
Xudong Cao ◽  
Jianjun Wang ◽  
Chenchen Chen
Keyword(s):  
Traffic Flow ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Neutral Stability ◽  
Difference Model ◽  
Velocity Difference ◽  
Car Following ◽  
Car Following Model ◽  
The Difference ◽  
Improved Model

Although the difference between the velocity of two successive vehicles is considered in the full velocity difference model (FVDM), more status information from preceding vehicles affecting the behavior of car-following has not been effectively utilized. For improving the performance of the FVDM, an extended modified car-following model taking into account traffic density and the acceleration of a leading vehicle (DAVD, density and acceleration velocity difference model) is presented under the condition of vehicle-to-vehicle (V2V) communications. Stability in the developed model is derived through applying linear stability theory. The curves of neutral stability for the improved model indicate that when the driver pays more attention to the traffic status in front, the traffic flow stability region is larger. Numerical simulation illustrates that traffic flow disturbance could be suppressed by gaining more information on preceding vehicles.

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.

Vehicle's exhaust emissions under car-following model

2014 ◽  
Vol 25 (06) ◽  
pp. 1450007 ◽  
Author(s):  
Tie-Qiao Tang ◽  
Jin-Gang Li ◽  
Dong Zhang ◽  
Yun-Peng Wang
Keyword(s):  
Exhaust Emissions ◽  
Numerical Results ◽  
Velocity Difference ◽  
Car Following ◽  
Car Following Model

In this paper, we explore each vehicle's exhaust emissions under the full velocity difference (FVD) model and the car-following model with consideration of the traffic interruption probability during three typical traffic situations. Numerical results show that the vehicle's exhaust emissions of the second model are less than those of the first model under the three typical traffic situations, which shows that the second model can reduce each vehicle's exhaust emissions.

Full velocity difference car-following model considering desired inter-vehicle distance

2018 ◽  
Vol 29 (02) ◽  
pp. 1850018
Author(s):  
Tong Xin ◽  
Liu Yi ◽  
Cheng Rongjun ◽  
Ge Hongxia
Keyword(s):  
Theoretical Analysis ◽  
Numerical Simulations ◽  
Traffic Congestion ◽  
Control Method ◽  
Stability Conditions ◽  
Velocity Difference ◽  
Car Following ◽  
Car Following Model ◽  
The Stability

Based on the full velocity difference car-following model, an improved car-following model is put forward by considering the driver’s desired inter-vehicle distance. The stability conditions are obtained by applying the control method. The results of theoretical analysis are used to demonstrate the advantages of our model. Numerical simulations are used to show that traffic congestion can be improved as the desired inter-vehicle distance is considered in the full velocity difference car-following model.

An extended car-following model considering the acceleration derivative in some typical traffic environments

2018 ◽  
Vol 32 (08) ◽  
pp. 1850020 ◽  
Author(s):  
Tong Zhou ◽  
Dong Chen ◽  
Weining Liu
Keyword(s):  
Traffic Congestion ◽  
Extended Model ◽  
Velocity Difference ◽  
Car Following ◽  
Jamming Transition ◽  
Traffic Jams ◽  
Car Following Model ◽  
Starting Process ◽  
The Stability ◽  
Space Time Evolution

Based on the full velocity difference and acceleration car-following model, an extended car-following model is proposed by considering the vehicle’s acceleration derivative. The stability condition is given by applying the control theory. Considering some typical traffic environments, the results of theoretical analysis and numerical simulation show the extended model has a more actual acceleration of string vehicles than that of the previous models in starting process, stopping process and sudden brake. Meanwhile, the traffic jams more easily occur when the coefficient of vehicle’s acceleration derivative increases, which is presented by space-time evolution. The results confirm that the vehicle’s acceleration derivative plays an important role in the traffic jamming transition and the evolution of traffic congestion.

Multiple-Factors Aware Car-Following Model for Connected and Autonomous Vehicles

2021 ◽  
pp. 036119812110452
Author(s):  
Huaqing Ma ◽  
Hao Wu ◽  
Yucong Hu ◽  
Zhiwei Chen ◽  
Jialing Luo
Keyword(s):  
Autonomous Vehicles ◽  
Transportation Systems ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Simulation Experiments ◽  
Velocity Difference ◽  
Car Following ◽  
Multiple Factors ◽  
Car Following Model ◽  
The Stability

The emergence of connected and autonomous vehicles (CAV) is of great significance to the development of transportation systems. This paper proposes a multiple-factors aware car-following (MACF) model for CAVs with the consideration of multiple factors including vehicle co-optimization velocity, velocity difference of multiple PVs, and space headway of multiple PVs. The Next Generation Simulation (NGSIM) dataset and the genetic algorithm are used to calibrate the parameters of the model. The stability of the MACF model is first theoretically proved and then empirically verified via numerical simulation experiments. In addition, the VISSIM software is partially redeveloped based on the MACF model to analyze mixed traffic flows consisting of human-driven vehicles and CAVs. Results show that the integration of CAVs based on the MACF model effectively improves the average velocity and throughput of the system.

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