Analysis And Research On Lane Change Model And Lane Change Track Of Urban Expressway

With the continuous development of urbanization in China,urban expressway has become the main artery of the city.It has become the first choice for people to travel.The occurrence of Expressway congestion not only results in the reduction of road capacity,but also prone to traffic accidents.In this paper,based on the background of this problem,the characteristics of vehicle lane change are obtained through the micro level analysis of traffic flow theory,and the lateral trajectory of vehicle lane change is planned to obtain the optimal lane change trajectory.Firstly,this paper introduces the traffic flow theory and cellular automata model in the micro model.Through the study of single lane cellular automata,the characteristics and phenomena of traffic flow under different defined rules are obtained by simulation.The advantages and disadvantages of single lane cellular automata model are compared by analyzing vehicle time-space diagram,vehicle evolution process and basic diagram.Based on the analysis of the two lane cellular automata model with lane changing rules,an improved model considering different acceleration is proposed.Through the time-space diagram obtained by simulation,the flow density and speed density curve are analyzed,and compared with other two lane cellular automata models,it can be seen that in the simulation of the improved model,the vehicle speed in the road is faster than other models,.In the same time,there are more passing vehicles and less congestion,which makes full use of road resources and reduces traffic congestion.In this paper,we use the database of us-101 highway based on ngsim project as the source of traffic flow measurement data,and analyze the characteristics of lane changing vehicles.This paper introduces different planning methods of lane changing track.In Frenet coordinate system,the lateral track of lane changing is planned with quintic polynomial curve,and the optimal track of vehicle lane changing is obtained when there are obstacles.