Study On Single-lane Following Model In Mixed Traffic Environment Of Connected And Non-connected Vehicles

In recent years,the automobile industry has ushered in a new period of development,and the intelligent network connection has gradually become the mainstream of automobile development,and the market penetration rate has been continuously improved.In the process of popularization of networked vehicles,there must be a coexistence stage of networked vehicles and non-networked vehicles,and it has been in this stage for a long time,which has a great impact on the traditional traffic flow.Therefore,it is necessary to study the mixed traffic flow composed of networked vehicles and non-networked vehicles.Car-following,as the most basic vehicle driving behavior,is the basis of studying traffic flow.Car-following model can deeply analyze the characteristics of traffic flow,understand the operation mechanism of traffic flow,and provide basis for the organization and management of traffic flow,thus effectively solving traffic congestion and other problems.On the basis of previous research on car-following models,this paper constructs a car-following model suitable for networked environment,and deduces a mixed traffic flow model by combining IDM model,and analyzes the influence of different networked vehicle proportions on traffic flow.Then,the car-following model is combined with cellular automata theory,and the model is simulated and analyzed.The main work of this paper is as follows:(1)According to the car-following characteristics of networked vehicles,based on the car-following model of optimized speed,this paper comprehensively considers the factors that affect the car-following vehicles,such as the optimized speed between the vehicle and the adjacent rear vehicle,the speed difference between adjacent front vehicles,the optimal speed difference among multiple front vehicles,and the sensor sensitivity coefficient of networked vehicles.A car-following model based on networked environment is constructed,and the linear stability analysis and parameter calibration of the model are carried out.The results show that compared with the classic OV model and FVD model,the car-following model constructed in this paper improves the anti-interference ability of the system and makes the traffic flow more stable.(2)The improved car-following model and intelligent driver(IDM)model are used as car-following models for networked vehicles and non-networked vehicles,respectively.The mixed traffic flow model is derived from these two models,and the changing characteristics of mixed traffic flow with different proportions of networked vehicles are studied and analyzed.It is concluded that the road capacity and average speed increase with the increasing proportion of networked vehicles in mixed traffic flow.(3)Combining the car-following model with one-dimensional cellular automata model,different evolution rules of networked vehicles and non-networked vehicles are formulated,and the basic diagram and Shi Kongtu of single-lane mixed traffic flow under different conditions are realized through programming simulation.From the simulation diagram,it can be seen that the proportion of networked vehicles and the probability of random slowing down of vehicles have a great impact on traffic flow.Increasing the proportion of networked vehicles and reducing the random slowing down of vehicles in the process of driving can significantly improve the road capacity and the average speed of traffic flow.The simulation results show that the car-following model constructed in this paper is reasonable,and has certain practical significance for the study of mixed traffic flow characteristics.