Research On Rail Transit Passenger Flow Assignment Based On Mental Accounting

With the acceleration of the pace of China’s urban rail transit construction planning,the scale of rail transit networks in major cities in China has continued to expand,and urban rail transit operations have gradually entered the networked era.In order to facilitate passengers’ travel,improve operation quality and management level,domestic urban rail transit mostly adopts the "seamless transfer" mode,which causes the passenger’s travel process to become a "black box problem" that only enters and departs from the terminal.Its transfer information cannot be obtained in time,so it is difficult to know the characteristics and rules of passenger flow distribution on the network,and the operational management of urban rail transit becomes very hard.Therefore,studying the path selection behaviors of passengers in urban rail transit and scientifically and rationally assigning network passenger flows will help to more accurately grasp the characteristics and rules of passenger flow distribution on the rail transit network,and for the construction planning and operation management of urban rail transit is of great significance.Aiming at the problem of passenger flow distribution in the urban rail transit network,this paper considers the incomplete rational decision-making behaviors of passengers,and establishes an urban rail transit passenger flow distribution model based on mental accounting theory.First,the network structure and storage method of urban rail transit are described and analyzed with graph theory.The existing path search algorithms are summarized and compared,and an algorithm suitable for rail transit path search is proposed.Then,outline the types of mental accounts,design the route selection problem in the context of urban rail transit travel,and prove that passengers will spontaneously use Topical Accounts in the rail transit route decision problem,which effectively explains the changes in passenger selection results as the decision background changes phenomenon.The Chengdu metro transit passenger travel intention survey questionnaire was designed.The questionnaire survey was carried out by combining the network and the field.It was concluded that travel time and transfer times are the key factors that most affect the passenger route decision.Analyze the characteristics of path travel time and number of transfers in urban rail transit,clarify that passengers mainly rely on the value function to evaluate the path utility.Based on this,considering the influence of the two to construct the path value function,use the revenue split method to integrate the gains or losses of different accounts,and then determine the mathematical form of the transaction utility function,construct the passenger flow distribution model based on the mental account theory,and propose a path-based passenger flow distribution method.Finally,use Chengdu rail transit as an example to build a network model,and selects the morning peak OD passenger flow matrix for a working day in April 2018 for example.Use C ++ software to realize the distribution of passenger flow throughout the network,display the distribution results in the transcad software,compare and analyze the model calculation results of three pairs of OD pairs with the calculation results of the MNL model and survey results to illustrate the feasibility and effectiveness of the model.The empirical results show that compared with the traditional MNL model,the passenger flow distribution model based on mental account theory can more accurately describe the passenger’s path selection behaviors,and the obtained passenger flow distribution results are more in line with the actual situation.