Research On Passenger Distribution Of Intercity High-speed Railway Based On Disaggregate Model

With the rapid development of China’s economy, the passenger demand is growing fast,passenger rail line construction started its rapid development, effectively alleviating thepressure of the passenger market. And the intercity high-speed railway is a kind of passengerrail line, In the early stage of intercity high-speed railway operations, passenger flow can’tguarantee the load factor of intercity trains, But through years of development, the growth rateof passenger traffic significantly improved, and the intercity high-speed railway passengertraffic soared. Passenger distribution significant fluctuations, it is an important basis for thepromotion of intercity high-speed railway development to effectively control passenger flowand passenger distribution. The research of this subject has an important significance for thedevelopment of intercity high-speed railway.Intercity high-speed railway passenger was selected for the study of this paper, studyingintercity high-speed railway sharing rates through comparing the effectiveness of differentways to travel. And it was based on the impact factors of passenger’s travel time selection toanalyze to determine the different properties of intercity passenger travel time to choose, andthen achieved getting the distribution of intercity high-speed railway passenger based on thedistribution of property.The basic line of research in this paper was:(1) Research on the theory of railwaypassenger flow analysis by summarizing the research methods and the distribution ofpassenger, identifying the theoretical methods to intercity high-speed railway passengersharing rate and the distribution for research; System analysis and summary of the impactfactors of intercity high-speed railway passenger traveling behavior, and explained theintercity high-speed railway passenger distribution of day, Week and holiday based on theactual situation;(2) The introduction of disaggregate model meticulous theoretical dependingon the distribution of random utility including Logit model, nested Logit models and Logisticregression models, analyzing to determine the application characteristics of each model;(3)Take the Beijing-Tianjin intercity high-speed railway for example, applying maximum utilitymodels to study the share rate of travel modes based on actual passenger demand to determinethe impact of factors-services and fees. In order to achieve calculating the sharing rate of theBeijing-Tianjin Intercity Railway in2018;(4) Application binomial logistic regression modelsin distribution of intercity rail passenger, it achieved interactive analysis of passenger traveltime selected and passenger flow properties by SP, and achieved the calculation and testing ofvariable parameters by software SPSS to determine the utility function. And the feasibility ofthe model was verified by the results of the calculation;(5) Study the intercity high-speedrailway passenger distribution of week using nested logit model. It selected weekdays andweekends for the virtual layer, analyzing realization of personal property and property oftravel impacting travel date chosen through SP passenger survey, and application of SPSS software to calculate and test parameter variables to determine the utility function effectively.And the feasibility of the model was verified by the results of the calculation;(6)Summarizing the research results and problems and make feasible suggestions based on theresults of the Beijing-Tianjin intercity high-speed railway passenger distribution studies.