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.
Highlights
Affected by such information as the state of traffic lights at intersections and the real-time movement of adjacent vehicles, periodic accumulation and dissipation of vehicle queues will appear on the road. e microscopic car-following behavior plays an important role in the formation and dissipation mechanism of queuing during the process of vehicle queuing at intersections
The effectiveness of the model is verified through simulation analysis. e research results in this paper show the following: (1) e proposed improved V2X car-following model has a positive effect on the stability of traffic flow. e stability analysis of the model found that with the increase of tf, the operation of the traffic flow becomes more and more stable
Before reaching the critical reaction time tfmax, with the increase of tf, the efficiency of restoring stability of the traffic flow system at intersections is significantly improved after the green light is on. e longer the initial headway, the higher the maximum speed reached during the early start state
Summary
Affected by such information as the state of traffic lights at intersections and the real-time movement of adjacent vehicles, periodic accumulation and dissipation of vehicle queues will appear on the road. e microscopic car-following behavior plays an important role in the formation and dissipation mechanism of queuing during the process of vehicle queuing at intersections. With the support of V2X communication, the bus can send a priority request before entering the intersection and activate real-time signal priority control at the preceding intersection before the bus reaches the intersection In this TSP strategy, the queuing time was estimated based on the traffic wave theory [4]. E whole road traffic information will change drivers’ reaction flexibility to vehicle manipulation and microscopic car-following behavior, and further affect the process of vehicle queuing accumulation and dissipation.
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