Urban Rail Transit System Operation Optimization A Game Theoretical Methodology

TL;DR

This paper introduces a game-theoretical model for optimizing train departure schedules in urban rail transit, balancing operational costs and passenger service quality, demonstrated through data from Nanjing subway.

Contribution

It develops a Stackelberg game model to determine optimal departure frequencies, addressing the tradeoff between service quality and operational costs in URT systems.

Findings

Model improves traffic efficiency significantly.

Optimal schedules balance passenger service and costs.

Numerical examples validate the approach.

Abstract

The Urban Rail Transit (URT) has been one of the major trip modes in cities worldwide. As the passengers arrive at variable rates in different time slots, e.g., rush and non-rush hours, the departure frequency at a site directly relates to perceived service quality of passengers; the high departure frequency, however, incurs more operation cost to URT. Therefore, a tradeoff between the interest of railway operator and the service quality of passengers needs to be addressed. In this paper, we develop a model on the operation method of train operation scheduling using a Stackelberg game model. The railway operator is modeled as the game leader and the passengers as the game follower, and an optimal departure frequency can be determine the tradeoff between passengers' service quality and operation cost. We present several numerical examples based on the operation data from Nanjing transit subway at China. The results demonstrate that the proposed model can significantly improve the traffic efficiency.