Research On The Intelligent Connected Vehicle Lane Changing Strategies Of Freeway Mixed Traffic Environment

Intelligent connected vehicles are one of the ideal solutions to improve road traffic efficiency and driving safety.However,its full commercial reach is still far away.Therefore,freeway mixed traffic will become a traffic pattern for a long time in future.The research on freeway mixed traffic characteristics is not clear.How to carry out the research on Intelligent connected vehicles lane changing strategies based on freeway mixed traffic macroscopic characteristics need to be solved urgently.Therefore,carry out macroscopic characteristics of freeway mixed traffic environment and lane changing strategies of Intelligent connected vehicles has great social value and practical significance for the large-scale promotion and application of Intelligent connected vehicles in future.Firstly,in order to clarify the macroscopic characteristics of freeway mixed traffic,an improved model based on the basic NaSch cellular automata model is constructed by adding lane changing rules、congestion ratio、lane numbers and vehicle types to analyze the freeway mixed traffic efficiency under Intelligent connected vehicles different penetration rates.Based on expected following distance,the Markov chain algorithm is used to calculate the freeway mixed traffic capacity.It is found that in the ordinary freeway scene,compared with the pure human-driving traffic flow,when the penetration rate of Intelligent connected vehicles reaches80%,the road average speed can be increased by 48.4%,and the congestion ratio can be reduced by 55.7%.When the penetration rate of Intelligent connected vehicles is higher than 51.5%,the setting of dedicated lanes has positive significance.Secondly,in order to ensure safe and efficient lane changing of Intelligent connected vehicles,whether the road capacity reaches the maximum is taken as one of the lane changing feasibility conditions,and Intelligent connected vehicles lane changing decision model based on speed guidance is established to analyze vehicles lane changing decision when the dedicated lane is the target lane.A double matrix Intelligent connected vehicles lane changing decision model based on game theory is established to analyze vehicles lane changing decision when the ordinary lane is the target lane.At the same time,considering the safety constraints,a multiobjective trajectory optimization algorithm based on quintic polynomial is established.The simulation results show that,compared with the existing model algorithms,the trajectory planning algorithm proposed in this paper can reduce the longitudinal driving distance of the target vehicle by 0.77% and the lateral acceleration by 7.21%,which reduces lane changing influence to road and improves lane changing comfort.Finally,in order to verify the effectiveness of the lane changing decision models,the Prescan and Simulink co-simulation platform is built to verify the lane changing decision models for dedicated lane and ordinary lane.The simulation results show that,compared with the existing model algorithm,when the target lane is a dedicated lane,the lane changing efficiency of the proposed model is improved by 6%.When the target lane is an ordinary lane,the lane changing efficiency of the proposed model is improved by 3.38%.