Research On Urban Road Network Traffic Flow Model And Algorithm Under The Condition Of Electric Vehicle Mixing

With the implementation of the restriction policy on the use of gasoline vehicles,new energy vehicles have been popularized and developed on a larger scale.It can be expected that in the near future,electric vehicles will become an important choice for urban residents to travel,and electric vehicles will also become an important part of urban road network traffic flow.Due to the lack of charging facilities and long charging time in the use of electric vehicles,electric vehicle travelers have range anxiety during travel,and their travel behavior is also different from that of gasoline vehicle travelers.This paper considers electric vehicle travelers with different range anxiety levels in the road network,uses safe electricity to quantify the range anxiety level of electric vehicle travelers,constructs a mixed urban traffic network of electric vehicle travelers and gasoline vehicle travelers,and studies the traffic flow distribution of urban road network under the condition of electric vehicle mixing.The main contents of this paper are as follows :Firstly,according to the travel decision scenarios of electric vehicles and gasoline vehicles in the road network,considering the relevant decision variables and factors,the travel cost function of road network travelers is determined.On this basis,considering the influence of initial power on the optional path,a user equilibrium model under the condition of electric vehicle mixing is constructed,and the uniqueness of the model solution is proved.Based on the Frank-Wolfe algorithm,a solution algorithm is designed,and the effectiveness of the model and algorithm is verified by an example.Secondly,based on the research of user equilibrium model,the stochastic user equilibrium condition and its equivalent variational inequality model under the condition of electric vehicle mixing are constructed,and the uniqueness of the model solution is proved.Based on the MSA algorithm,a solution algorithm is designed to solve the example network,and the influence of the change of initial power and charging station service capacity on the number of charging vehicles and the total travel time of the road network is analyzed.Finally,the results of the same example solved by the two models are compared and analyzed,and the path selection and link flow distribution of travelers in each network under the two models are compared.The results show that the proposed road network user equilibrium model under the condition of electric vehicle mixing and the road network random user equilibrium model under the condition of electric vehicle mixing are effective.The degree of range anxiety of electric vehicle travelers will affect their travel behavior decision-making.Compared with electric vehicle travelers with a lower degree of range anxiety of 0 k Wh,electric vehicle travelers with a higher degree of mileage anxiety of 3 k Wh will choose to spend 2.01 minutes more charging time on the way to alleviate the range anxiety caused by the exhaustion of electricity.Keeping the initial power at 17 k Wh can effectively reduce the charging frequency of electric vehicle travelers.The reasonable setting value of charging station service capacity is 40 pcu.Compared with the user equilibrium model,the traffic distribution on the links and paths allocated by the stochastic user equilibrium model is more uniform.Some links in the solution results of stochastic user equilibrium model and user equilibrium model will form congestion.