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.

A Control Method Considering Two Velocity Difference Effect in the Car Following Model

2012 ◽  
Vol 198-199 ◽  
pp. 962-965
Author(s):  
Jian Yu ◽  
Rong Jun Cheng ◽  
Hong Xia Ge
Keyword(s):  
Traffic Congestion ◽  
Control Method ◽  
Velocity Difference ◽  
Traffic System ◽  
Car Following ◽  
Traffic State ◽  
Control Signals ◽  
Car Following Model ◽  
The Stability ◽  
Difference Effect

A modified car following model is put forward considering the headway distance of two successive vehicles in front. A control method to suppress traffic congestion is proposed for car following model. According to the control theory, the stability conditions are derived. The feedback signals, which act on our traffic system, consider two velocity difference effect. The control signals will play an effect only if the traffic state is in congestion. The corresponding numerical simulation results are agree well with our theoretical analysis.

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 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.

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.

The new car following model considering vehicle dynamics influence and numerical simulation

2015 ◽  
Vol 26 (07) ◽  
pp. 1550081 ◽  
Author(s):  
Dihua Sun ◽  
Hui Liu ◽  
Geng Zhang ◽  
Min Zhao
Keyword(s):  
Numerical Simulation ◽  
Traffic Congestion ◽  
Vehicle Dynamics ◽  
Velocity Difference ◽  
Car Following ◽  
Car Following Model ◽  
Simulation Results ◽  
Starting Process ◽  
The Stability ◽  
Real Traffic

In this paper, the car following model is investigated by considering the vehicle dynamics in a cyber physical view. In fact, that driving is a typical cyber physical process which couples the cyber aspect of the vehicles' information and driving decision tightly with the dynamics and physics of the vehicles and traffic environment. However, the influence from the physical (vehicle) view was been ignored in the previous car following models. In order to describe the car following behavior more reasonably in real traffic, a new car following model by considering vehicle dynamics (for short, D-CFM) is proposed. In this paper, we take the full velocity difference (FVD) car following model as a case. The stability condition is given on the base of the control theory. The analytical method and numerical simulation results show that the new models can describe the evolution of traffic congestion. The simulations also show vehicles with a more actual acceleration of starting process than early models.

Flow and Density Difference Lattice Model and its Numerical Simulations Analysis

2012 ◽  
Vol 605-607 ◽  
pp. 2461-2465
Author(s):  
Hao Dai ◽  
Zhen Zhou Yuan ◽  
Jun Fang Tian
Keyword(s):  
Numerical Simulations ◽  
Lattice Model ◽  
Density Difference ◽  
Linear Stability Theory ◽  
Traffic Jam ◽  
Car Following ◽  
Car Following Model ◽  
Traffic Flow Stability ◽  
The Stability ◽  
Difference Effect

Based on Nagatani’s model, an extended car following model named flow and density difference lattice model (FDDLM) was proposed. Using the linear stability theory, the stability condition of the new model was obtained. The phase diagram presents that density difference effect is more efficiently than flow difference effect in improving the traffic flow stability and FDDLM could suppress traffic jam effectively. The numerical simulations are consonant with the analytical results and show that considering the flow and density difference leads to the stabilization of the system.

scholarly journals Driver’s Anticipation and Memory Driving Car-Following Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Ammar Jafaripournimchahi ◽  
Lu Sun ◽  
Wusheng Hu
Keyword(s):  
Traffic Flow ◽  
Nonlinear Stability ◽  
Relative Velocity ◽  
Mkdv Equation ◽  
Signalized Intersection ◽  
Stability Conditions ◽  
Car Following ◽  
Car Following Model ◽  
Linear And Nonlinear ◽  
The Stability

We developed a new car-following model to investigate the effects of driver anticipation and driver memory on traffic flow. The changes of headway, relative velocity, and driver memory to the vehicle in front are introduced as factors of driver’s anticipation behavior. Linear and nonlinear stability analyses are both applied to study the linear and nonlinear stability conditions of the new model. Through nonlinear analysis a modified Korteweg-de Vries (mKdV) equation was constructed to describe traffic flow near the traffic near the critical point. Numerical simulation shows that the stability of traffic flow can be effectively enhanced by the effect of driver anticipation and memory. The starting and breaking process of vehicles passing through the signalized intersection considering anticipation and driver memory are presented. All results demonstrate that the AMD model exhibit a greater stability as compared to existing car-following models.

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.

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.

An extended car-following model considering the low visibility in fog on a highway with slopes

2019 ◽  
Vol 30 (11) ◽  
pp. 1950090
Author(s):  
Jinhua Tan ◽  
Li Gong ◽  
Xuqian Qin
Keyword(s):  
Stability Analysis ◽  
Numerical Simulations ◽  
Traffic Flow ◽  
Linear Stability ◽  
Linear Stability Analysis ◽  
Neutral Stability ◽  
Car Following ◽  
Low Visibility ◽  
Car Following Model ◽  
The Stability

To depict the effect of low-visibility foggy weather upon traffic flow on a highway with slopes, this paper proposes an extended car-following model taking into consideration the drivers’ misjudgment of the following distance and their active reduction of the velocity. By linear stability analysis, the neutral stability curves are obtained. It is shown that under all the three road conditions: uphill, flat road and downhill, drivers’ misjudgment of the following distance will change the stable regions, while having little effect on the sizes of the stable regions. Correspondingly, drivers’ active reduction of the velocity will increase the stability. The numerical simulations agree well with the analytical results. It indicates that drivers’ misjudgment contributes to a higher velocity. Meanwhile, their active reduction of the velocity helps mitigate the influences of small perturbation. Furthermore, drivers’ misjudgment of the following distance has the greatest effect on downhill and the smallest effect on uphill, so does drivers’ active reduction of the velocity.

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