| With the development of high-speed railway, the service level of railway transportation is continuously improving. The travel demand of railway passengers has been satisfied to a certain extent, however, travelers hope to be safer, faster, cheaper, more comfortable and more convenient in their journey. Travelers who have different travel demand pay close attention to different travel fare and service level. In order to meet passengers’demands, we investigate railway passenger travel choice behavior and traveling scheme choice behavior. To provide high quality travel services for travelers, we analyze passenger flow assignment of railway passenger transportation networks, adjust transportation organization scheme based on the results of assignment and transportation needs.In this paper, railway passenger travel choice behavior and passenger flow assignment approach of railway passenger transportation network have been studied in micro-level, meso-level and macro-level. First, railway transport diversity of supply and demand and factors of railway passenger travel choice behavior are analyzed, also individual travelers travel choice behavior is analyzed in micro level.Secondly, the travel choice behavior of one kind of passengers is analyzed in meso level. In order to objectively provide the best traveling scheme for railway passengers who have different travel demand, evaluation index system of passenger traveling scheme selection is established, considering the factors of traveling scheme choice behavior. The evaluation index system is optimized using cluster analysis and the index weights are determined by combination weighting method. Then, traveling scheme selection decision model is developed based on gray correlation analysis.In additional, railway passenger travel network is constructed based on train timetable, passenger travel time and residual capacity of train in macro level. Both the generalized cost function we developed and the residual train capacity are considered to be the foundation of path searching procedure. The railway passenger travel network topology is analyzed based on residual train capacity. Considering the total travel time, the total travel cost and the total number of passengers, we propose an optimal path searching algorithm based on residual train capacity in railway passenger travel network. The rationale of the railway passenger travel network and the optimal path generation algorithm are verified positively by case study. Then, passenger flow characteristics of the high-speed railway are analyzed, and variation of passenger flow in the adjacent period is summed up. Passenger flow change rate is divided into different grades and fuzzified. Also, fuzzy k-nearest neighbor passenger flow prediction model is established, which lay a foundation for passenger flow assignment of railway passenger transportation network.Finally, railway passenger transportation network is developed by many OD (origin-destination) passenger travel paths. Allowing for passenger transportation capacity in different railway line section and total impedance of passenger travel path, passenger transportation capacity saturation entropy in different railway line section and total impedance entropy of passenger travel path and other new concept are proposed in accordance of passenger allocation of railway passenger transportation network. Also, passenger allocation optimization model is built for making railway passenger transportation capacity match demand for passenger travel as much as possible. Passenger allocation iterative optimization algorithm based on entropy optimization is developed by taking into account the importance of the passenger transportation capacity and total impedance of passenger travel path. Numerical example results reveal that more effective and more detailed railway passenger allocation scheme of different travel path is established by adopting passenger allocation model and algorithm developed in this paper. |
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