Research On The Dynamic Flow Assignment Model Based On Train Schedule For Urban Subway Network

With the sustained construction of urban subway in China, the urban subway network will beenlarged gradually in metropolis.Compared to single or several subway lines, passengers’ behaviorsconsisting of line choice, route choice and transfer choice changed greatly. In accordance with the Beijingsubway tickets and fare policy, there is no dditional charge for transfer, the challenge to the operation andmanagement of such system is how to predict the nonlinear growth of travel demand and simulate thepassengers’ behaviors consisting of line choice, route choice and transfer choice. In such conditions, it is akey problem for its operation and management to predict scientifically passenger flow assignment throughurban railway transport network.This thesis focused on the passenger flow assignment problem in the urban subway network. Throughthe analysis for the travel survey of Beijing subway passengers, this paper considered the main factorsaffecting passenger’s path-choice and analyzed the correlation between the passenger’s properties and thepath-choice behavior. Based on survey data, the classification of all passengers was determined. Then thesocio-economic attributes based choice probability models are given. Subsequently, the correspondingassignment process is proposed for urban subway network. Similarly, the Beijing subway network in2010is used as example to illustrate the applicaiotn of proposed model and algorithm. At the same time, thispaper considered the dynamic properties of the urban subway network and proposed both of concept and itsmodel of schedule-based subway space-time extended network. On the base of these, a schedule-baseddynamic assignment model and algorithm for subway network was presented with its solution algorithm inthis paper. Finally, the feasibility and effectiveness of the model and algorithm were tested by a simpleexample. The contents of this paper are summarized as follows:(1) In practice, the flow assignment partern through urban rail transport network is resulted with theaggregation of all passengers’ cmbined choices. Therefore, understanding and mastering the passenger’schoice psychology is the the foundation of modeling the passenger’s route choice and flow assignmentthrough whole network. In order to fully grasp the characteristics of the passenger route choice behavior,meanwhile, in order to provide reliable data for future research support and related parameter estimation,this paper designed a questionnaire of passengers’ choice behavior and gives fully data statistical analysisof Beijing subway network.(2) Based on the survey data, this paper analyzed the correlation between the passenger’s propertiesand path-choice behavior by using the chi-square test. According to the analysis results, only threeproperties including the occupation, the trip purpose and personal income have strong correlations with thepassenger’s route-choice behavior. Each attribute was divided into two major categories and eight types ofpassengers were found by cross-classification of these three attributes. Finally, the categories with therelatively small sample size were merged and resulted in five categories of all passengers.(3) According to survey data, the passengers with different socio-economic attributes will havedifferent standards and preferences of traffic choices. This paper considers the different choice behaviors between different passengers fully and establishes the generalized travel cost functions for different typesof passengers. Then the socio-economic attributes based choice probability models are given. Subsequently,the corresponding assignment process is proposed for urban subway network. Similarly, the Beijing subwaynetwork in2010is used as example to illustrate the applicaiotn of proposed model and algorithm. Thefollowing conclusions were draw from this research: the calculation results from the socio-economicattributes based assignment method were closer to the actual case with respect to the method withoutpassenger classification; through sensitivity analysis, it is shown that the parameters that desribed thepassenger’s familiarity of the network had relatively small impact on the calculation results, while theexpansion coefficients for effective path as well as the transfer penalty parameters had more impacts on thecalculation results; due to the second class and the third class passengers had different path-choicepreferences compared to the other categories, the changes of these two types of passengers share wouldimpact the flow assignment results. These conclusions expained that the reasonableness and necessity ofthe socio-economic attributes based assignment method.(4) This paper summed up the time-varying characteristics of both the subway network and O-Ddemand and proposed the definition of the spatial structure of the subway network based on the physicalsite and interval. Combined with the train schedule, this paper presented the space-time extended networkas well as the concept of space-time path. On this basis, this paper proposed a method to build thespace-time extended network for urban subway system based on the schedule information and gave thedefinition and description of the basic elements in such network.(5) The major factors that influence passenger flow pattern in urban subway network are taken intoaccount. The timeliness of the impact on passenger travel choice was analyzed. Based on the space-timeextended network for urban subway system, the factors in term of travel time, transfer as well as thecongestion in vehicle were fully considered in order to build a generalized cost function for passenger’stravel path. On the base of this, this paper proposed a schedule-based dynamic assignment model for theurban subway network. The MSA algorithm was used to solve such model. Simultaneously, an improvedshortest path search algorithm was given for the space-time extended network. Finally, a simple numericalexample was used to illustrate validation and effection of the proposed model and algorithm.