Timetable Optimization Of Urban Rail Transit Network Based On Dynamic Passenger Flow

There are many characters of urban rail transit that can not be replaced by other trip modes, such as big passenger handling capacity, quick, efficiency and punctuality, which make it become the most effective tool to relieve the city’s traffic pressure and become the dominant of the modern city public traffic system gradually. Urban rail transit timetable is an indispensable and important component in organization and management of urban rail transit system, which clearly stipulates the train frequency and the running space-time track. A scientific and reasonable urban rail transit timetable can effectively improve the equipment utilization rate and greatly reduce the passengers’ delay in the station and in the train. Passenger flow of urban rail transit belongs to dynamic flow, which is basis of designing the timetable and changes with the change of the time and space. Therefore, making and optimizing the timetable based on dynamic passenger flow can effectively keep the balance between the supply and the demand. What’s more, it has realistic significance and applied value to meet the practical requirements and operation management.In the paper, taking the actual passenger trip data which is collected in urban rail transit automatic fare collection system as sample data, and referring to schedule design theory, the theory of passengers’ trip choices and urban rail transit system own characteristics. In addition, optimized timetable model of urban rail transit network based on dynamic passenger flow is researched and related algorithm is designed to solve the problem. Finally, applying Beijing urban rail transit network to verify the model and algorithm. The main work is as follows. (1) Researching the theory knowledge of urban rail transit passenger flow formation, the factors of influencing passenger flow, and the passengers’ time and space distribution characteristics. In the meantime, analyzing the distribution characteristic of AFC data of Beijing urban rail transit system. All of which can be used in the consequent model establishment and the optimization research of timetable. (2) Analyzing passengers’waiting behavior in the urban rail transit process and how train departure intervals affect passengers’ waiting time. Aiming to the regularity distribution of check-in flow for each station, which change by time. And building the model of urban rail transit system timetable based on the dynamic passenger flow to minimize passengers’waiting time. The suggested model and algorithm are applied to Beijing urban rail transit system. The results show that the established model and algorithm can effectively improve the utilization rate of trains and reduce passengers’waiting time.(3) Some studies show that the passengers’total calories consumption is different when passengers are traveling or waiting, what’s more, which is changing because of the degree of environmental crowding. Analyzing consumed calories of passengers (called passengers’travel energy consumption) in urban rail transit process. Building the model of urban rail transit timetable based on passengers’travel energy consumption, and designing the corresponding algorithm. The suggested model and algorithm are applied to Yizhuang line of Beijing urban rail transit system. The results show that the established model and algorithm which can minimize passengers’total travel energy consumption and provide theoretical references for operation and management department to administrate scientifically.