On Time-Dependent Critical Platforms and Tracks in Metro Systems

Abstract

Metro systems play an important role in the public transportation system, and metro safety and passenger satisfaction are of great concern to urbanized societies. Identifying critical platforms and tracks is a fundamental and significant step to improving a metro system's safety and passenger satisfaction, which has never been examined in the literature. Typical critical link analysis for road networks cannot be applied to metro network systems because of the different characteristics of these two transportation modes, such as vehicle operation. In addition, the existing studies on critical stations for metro networks cannot reveal the different importance of platforms involved in one station. This study proposes a novel framework to identify critical platforms and tracks for a metro system with consideration of its spatial characteristics and temporal dynamics using smart card data. We first develop an entirely directed model to describe a metro system where nodes and arcs represent platforms and tracks, respectively. Critical platforms and tracks are then defined and assessed based on dynamic waiting time and onboard crowdedness. The proposed approach is validated by historical smart card data of the Shenzhen Metro system, and the results show time-variant rankings of critical platforms and tracks over the time of the day and the day of the week.