Timetable Optimization for Metro Lines Connecting to Intercity Railway Stations to Minimize Passenger Waiting Time

In major metropolitan cities, metro and intercity rail services usually share stations or have stations in close proximity to facilitate smooth connections for passengers. A large number of passengers may arrive on metro platforms within a short period of time upon the arrivals of intercity trains, while the number may drop significantly afterward. This injected passenger demand is not coped well by the metro timetable with the commonly adopted regular train headway. Focusing on metro lines connecting to intercity railways, this study puts forward a timetable model to optimize train headways at each station, assuming all passengers board the first train available. The objective is to minimize the total waiting time of passengers at platforms throughout the metro line, without changing the number of vehicle trips. To calculate the passenger waiting time accurately, a mathematical model is proposed to obtain the number of transfer passengers arriving at metro platform in each time interval, based on arrivals of intercity trains and transfer facilities at the station. A genetic algorithm, combined with interior-point algorithm, is developed to obtain the solution of the proposed timetable model. Real-life case studies show that the optimized timetable reduces the total passenger waiting time when compared with the current timetable and the solution of another model optimizing train departure times at the first station only. In addition, the peak number of passengers congregating at metro platforms drops significantly, which relieves passenger crowding on the platform.

Automated summary

The study proposed an optimized timetable model for metro lines connecting to intercity railways, aiming to minimize the total passenger waiting time at platforms. By using a mathematical model and a genetic algorithm combined with an interior-point algorithm, the optimized timetable significantly reduced passenger waiting time and alleviated platform congestion.