Research On Congestion Characteristics And Control Strategy Of Freeway Traffic Flow Under Abnormal Events

As an important part of the comprehensive transportation system,the freeway is the main carrier of traffic demand and the key bond of regional connection,which plays an important role in the development of social economy.In recent years,with the growth of freeway mileage and the continuous development of urbanization in China,the travel demand of residents has increased rapidly,and the freeway environment has become increasingly complex,which has brought severe challenges to the traffic management of freeway in China.Due to the freeway characteristics of closed structure,fast speed vehicles and large traffic volume,once some special abnormal events have happened,such as severe weather,traffic accidents and temporary maintenance,the losses will be incalculable without timely control measures.Therefore,for the scenario of abnormal events happened on the freeway,it is urgent to explore the propagation characteristics of congestion and formulate reasonable control measures to reduce the impact of abnormal events and improve the traffic state.In addition,in the context of the rapid development of intelligent transportation,intelligent and connected driving technology has brought new ideas to traffic management.By making use of the advantages of information sharing,efficiency,safety and other characteristics of connected and automated vehicles,timely and active control of the freeway where abnormal events occurred can effectively improve the traffic efficiency and the stability of the traffic system.In order to reduce the impact of abnormal events on the freeway,improve the traffic efficiency and ensure the driving safety of vehicles,this dissertation takes the freeway with abnormal events as the research object,analyzes the propagation characteristics of congestion and quantifies the interference intensity of abnormal events on traffic flow.This dissertation puts forward traffic control measures under the mixed flow environment with connected and automated vehicles and human vehicles,as well as the vehicle trajectory optimization model under the fully automatic driving environment in the future.Specifically,the main contents of this dissertation are as follows:(1)Research on the propagation characteristics of freeway congestion under abnormal events.Firstly,the propagation law of congestion is studied,meanwhile the mutation point is defined to represent the change of traffic state by using the speed map,and an algorithm is designed to determine the spatiotemporal impact region of traffic congestion.Secondly,the weather,environment,road attributes and other factors are introduced,and the causal inference method is used to model the impact of abnormal events,quantify the interference intensity of the abnormal event on traffic flow.Finally,an example with real freeway abnormal event data is used to verify the model.The results show that for most of the affected links,the average causal effect caused by the abnormal event generally increases first and then decreases.(2)Speed control of connected and automated vehicles on the freeway with an abnormal event in the mixed traffic flow environment.In the mixed traffic flow condition,where human vehicles and connected and automated vehicles exist at the same time,connected and automated vehicles can not only be regarded as traffic participants,but also as traffic managers.Based on the principle that properly increasement of the vehicle speed at the bottleneck can effectively improve the traffic capacity of the freeway,a method to determine the connected and automated vehicles’ control speed is proposed according to the real-time macroscopic traffic flow characteristics and the historical traffic flow.Several simulation experiments are designed to analyze the feasibility of this method under different traffic demand and different connected and automated vehicle proportion.The simulation results show that when the traffic demand is 6000 vehicle/hour or when the traffic demand is 4500vehicle/hour with the low connected and automated vehicle proportion,the improvement effect of this method on the traffic system is obvious.For example,when the traffic demand is 6000 vehicle/hour and the connected and automated vehicle proportion is 0.6,the improvement of vehicle efficiency by this method is 31.7%.(3)Local cooperative management and control of connected and automated vehicles under the freeway with an abnormal event in the mixed traffic flow environment.It is analyzed that the traffic capacity in the mixed flow is not only related to the connected and automated vehicle proportion,but also affected by the arrangement of connected and automated vehicles.A local cooperative management and control method of connected and automated vehicles considering the intensity of the connected and automated vehicle platoon is proposed.Firstly,according to the location of the abnormal event lane,with the objective of increasing the platoon intensity "in the vicinity",the merging sequence of connected and automated vehicles in different lanes is given.Secondly,for vehicles that have formed a platoon,the goal of maintaining a minimum safe distance between vehicles is used for cooperative management and control;for heterogeneous human vehicles and connected and automated vehicles that are not in a platoon,the vehicle’s behavior is characterized according to the existing car-following and lane changing models.Lastly,several simulation experiments are designed to further analyze the impact of the method on the traffic system.The simulation results show that when the traffic demand is 6500 vehicle/hour or 4500vehicle/hour,the improvement of the performance on the traffic system is obvious.When the traffic demand is 6500 vehicle/hour and the connected and automated vehicle proportion is 0.6,the improvement of the average travel time of vehicles can be 40.9%.(4)Vehicle trajectory optimization for the freeway with an abnormal event in the fully autonomous driving environment.In order to relieve traffic congestion and ensure the smooth operation of vehicles,it is necessary to optimize the moving trajectories of vehicles.In the environment where all vehicles are connected and autonomous vehicles,the advantages of vehicle regulation and sensitive response provide a strong guarantee for optimizing vehicle trajectories.Firstly,in order to reduce the complexity of the merging problem,the upstream of abnormal event area is divided into longitudinal position regulation area and lateral merging area.Secondly,in the longitudinal position regulation area,the optimization model is established to improve the capacity of accommodating merging vehicles on the normal lanes,and a two-stage algorithm is designed to obtain the longitudinal trajectory;in the lateral merging area,in order to make all vehicles complete lane changing before the merging point,the lateral merging control model is established,and the sorting algorithm is applied to obtain the vehicle merging trajectory.Lastly,several simulation experiments are designed to analyze the impact of this method on traffic efficiency in different scenarios.The results show that under different traffic scenarios,this method is better than the existing methods such as early merge and late merge.