Transit Vehicles Intelligent Scheduling Optimization Based on the Division of Characteristic Periods

Abstract

Vehicle scheduling problem (VSP) is a vital part of the bus scheduling scheme based on the bus timetables. In this paper, the various basic problems that influence the vehicle scheduling scheme are analyzed. Then, the characteristic periods are divided by using the ordered samples clustering of travel time based on vehicle real-time GPS data. According to the parameters such as the vehicle headways, vehicle turnaround time, the first and last stations’ layover time in different characteristic periods, the vehicles scheduling optimization model is established with the object of the minimum vehicles quantity and the minimum total operating costs. The single depot vehicle scheduling problem is converted to the general fixed job scheduling matters; the practical method of vehicle dispatch and vehicle operational method are given. Finally, the model is applied with the actual running data of an example bus line and the corresponding vehicle turnover program is given.