Scheduling a high-speed railway model with explicit consideration of passenger choices

Abstract

In the recent years, high-speed railway has become one of the main intercity travel modes in many countries. A better railway timetable for high-speed railway can provide a more convenient and reliable service to passengers, which may attract more consumers transferring from domestic air flights and cars. Mass passenger data (e.g., ticket data, data from apps used for planning trips, etc.) provide the opportunity to study how to plan this kind of timetable for daily use. In this study, an iterative high-speed train scheduling approach is proposed. This approach inputs passenger data and the initial timetable with a track allocation plan to the extended passenger choice model to simulate passenger reaction to the timetable. Considering the simulation results, the scheduling integer linear program adjusts the timetable with the track allocation plan to minimize the system passenger travel cost. The algorithm iterates through the extended passenger choice model and the scheduling integer linear program until a balance is reached.