Research On Multi-user Mixed Network Equilibrium Models With Electric Vehicles

Electric vehicle(EV)is an important tool for urban transportation in the future.It can be predicted that the transportation network will be in a mixed state of electric vehicle and fuel vehicle for a long time.Therefore,it is of great practical significance for traffic managers to study the mixed traffic assignment problem of electric vehicles and fuel vehicles,understand the traffic flow distribution of the future traffic network,further evaluate the status of the road network.Considering the wide participation of EVs in the traffic network,this dissertation took EV users as the main research object,studied the mixed traffic assignment problem under given travel demand,and explored the influence of EV users' risk preference and time utility on the equilibrium of mixed traffic network.In addition,this dissertation further explored the mixed user equilibrium problem when the travel demand of the EV was an endogenous variable.More details are listed follows.Firstly,the main shortcomings of EV were summarized.Then,this dissertation analyzed the characteristics of EV users' travel behavior and pointed out the impact of range anxiety and charging anxiety.A mixed traffic network equilibrium model of electric vehicle and fuel vehicle was constructed when the travel demand of electric vehicle and fuel vehicle was given.Secondly,by considering different risk preferences among EV users,this dissertation extended the mixed network equilibrium under given demand to a multi-user equilibrium problem which considered the difference of EV users'risk preferences.Moreover,a corresponding solving algorithm was proposed,and a numerical example was provided to illustrate the application of the proposed model and algorithm.It was found that with the increase of the degree of risk aversion,the charging time of EV users will increase.Thirdly,considering the difference of EV users'time utility,the mixed network equilibrium was extended to another multi-user mixed equilibrium problem,and a traffic assignment model considering the time utility difference among EV users was constructed.A corresponding model solving algorithm was proposed,and the rationality of the model and algorithm was verified by a numerical example.It was found that equilibrium results considering EV travelers with different time utility changed.With the increase of charging time utility,EV travelers tend to choose the path with less electricity consumption.Finally,this dissertation formulated a mixed equilibrium model of fuel vehicles and electric vehicles considering the endogenous penetration of EV.Besides,a model solving algorithm was proposed,and both the model and the algorithm was applicated by a numerical example.It was found that with the increase of EV penetration,the total cost of network travel decreased first and then increased.The EV penetration which minimal the total cost of travelers was the endogenous penetration rate.Comprehensively speaking,this dissertation constructed two mixed traffic assignment models considering multi-class EV users and a mixed traffic assignment model considering endogenous market penetration of EVs.Relevant research results are of great significance for traffic managers to fully understand the traffic flow of road network,better respond to the demand of EVs and urban traffic planning and management.