Study On The Operation Mode And Timetabling Of Rural Public Transport

Rural public transport is an important tool for providing public transit service in rural areas. Currently, the operation management model backwardness and the low service level of rural public transport is a common phenomenon and needs to be improved. To solve the problem, firstly an organization mode for the rural public transport is proposed based on the current situation and demand, in order to improve the management problems. And then on the basis of such organization model, the optimal model for departing headway and the solution approach based on Biogeography-Based Optimization is designed to compile the timetable and to improve the service level of rural public transport. The specific research contents are as follows:(1) According to the current situation and the direction of future development of the rural public transport, the operation mode is built with the combination of current research, which includes three aspects: the management system mode, line organization mode and vehicle scheduling strategy respectively. In the management system mode, the three management levels that contain the government, the transportation department and the transport enterprise are closely integrated. Meanwhile, suggestions are provided to clear the responsibilities of each management level. The line organization mode is designed with regional operation model which could effectively combine the cold and hot line. Moreover, the vehicle scheduling strategy is designed for the cold and hot line respectively.(2) To propose a method of timetabling aiming at improving the efficiency of the operation and level of service of the rural public transport. Through the classic methods for deciding departing headway calculate the initial departing, the optimal model for departing headway which takes minimizing operation costs and passenger travel costs as objective function is established to adjust the initial departing headway and then compiles the timetable. Furthermore, a solution approach is designed to solve the optimization model based on Biogeography-Based Optimization. The solution approach includes two steps: migration and variation. Among them, the variation distance and greedy strategy is introduced to reduce the search range and improve the search speed of the algorithm. Finally, the feasibility of the algorithm and optimization model is validated with an example.