Modeling Of Mixed Traffic Flow And Analysis Of Characteristics Under The Influence Of Connected And Autonomous Vehicle

Connected and Autonomous Vehicles(CAV)can relieve traffic congestion and improve traffic safety.However,the conditions for large-scale industrialization of CAV are still immature in the short term,and the traffic system will transition to mixed traffic of CAV and Human-Driven Vehicles(HDV)for a long time.The evolution mechanism of the mixed traffic flow characteristics is widely concerned by academia.However,many mechanisms have not yet reached a consensus.The capacity,stability,and safety are the basic characteristics of mixed traffic flow under different CAV aggregation strategies.In this paper,the evolution mechanism of mixed traffic flow characteristics has been studied to provide a theoretical method for future mixed traffic flow management and control strategies under different traffic conditions.(1)Modeling and analysis of road capacity of mixed traffic flow under different strategies.The distribution expression of space headway under randomly mixed traffic is deduced by using probability theory for CAV randomly mixed environment.The mixed traffic flow management strategy is proposed for CAV dedicated lane environment.assuming CAV autonomous formation,the distance characterization function of space headway is constructed by using the Markov chain.Therefore,the basic diagrams of mixed traffic flow are established respectively under three traffic conditions.The evolutionary mechanism of road capacity is analyzed deeply under different traffic conditions.Numerical analysis shows that the mixing of CAV can improve the capacity under any traffic condition.However,the effect is not significant when the penetration rate is lower than 30%.(2)Analysis of mixed traffic flow stability under different strategies.The discriminative equation of mixed traffic flow stability is constructed by using the velocity perturbation transfer function,and then a mixed traffic flow stability analysis method considering the time delay is proposed to construct a highly applicable mixed traffic flow stability discriminative framework.Subsequently,three highway research scenarios of CAV random mixed traffic,setting dedicated lanes,and autonomous formation are constructed to study the evolution of mixed traffic flow stability.The results show that the mixed traffic flow stability is poor when the penetration rate is low.In addition,vehicle formation and lane management cannot improve the mixed traffic flow stability.(3)Safety analysis of mixed traffic flow under different strategies.SUMO is used to simulate the operational state of on-ramp bottleneck sections under the implementation of different CAV clustering strategies.The traffic safety posture is evaluated using a traffic flow surrogate safety assessment model.The results show that the mixing of CAVs will instead aggravate the risk of tail collision of mixed traffic flow when the CAV penetration rate is lower than 30%.The safety can be significantly improved if the CAVs have the ability of group autonomous formation.