Dissipation Characteristics of Vehicle Queue in V2X Environment Based on Improved Car-Following Model

Abstract

In recent years, the technology of Internet of Vehicles has developed rapidly, among which vehicle to everything (V2X) technology is provided with a quite important promotion value in the intelligent transportation field. In V2X environment, the driver can receive real-time information of the motion status of adjacent vehicles and the signal duration of the intersection, and take the decision-making action of manipulating the vehicle in advance, which has a certain impact on the evolution process of queue dissipation. This paper studies the improved OV model based on V2X environment and considering the driver’s early response time selects the intersection queue dissipation efficiency as the index to analyze the intersection traffic efficiency and studies the impact of different initial headway, maximum speed, and safety distance on the intersection traffic flow. The simulation results show that compared with the traditional OV model and the OV model considering driver’s reaction delay, the model proposed in this paper greatly improves the efficiency of traffic flow recovery after green light, so the model proposed in this paper can promote the stability of traffic flow. The linear stability of the proposed model was analyzed by using the linear stability theory to obtain the stability conditions of the improved model. Furthermore, a simulation environment was established to analyze the vehicle queue dissipation at intersections and to simulate the improved V2X car-following model as well as the platoon dissipation state under different traffic parameters. The research results show that vehicle drivers can obtain traffic flow operation status in real-time through V2X equipment and change the operation of the vehicle itself in a targeted manner, which can significantly improve the safety and stability of traffic flow operation, and greatly raise the dissipation efficiency of the platoon. The method proposed in this paper can increase the queue dissipation rate and shorten the recovery time of the traffic system, respectively.

Nonlinear Analysis of the Car-Following Model considering Delay under the V2X Environment

“…Many scholars [2][3][4][5][6][7][8] have investigated various factors and behaviors in intelligent transportation systems, such as delayed feedback [9], two-lane information interaction [10], and other behaviors [11][12][13][14][15]. For example, Ge et al [11] analyzed the infuence of the rear-view mirror efect on driving behavior.…”