Subway Station Capacity Maintained by Optimizing a Maintenance Schedule of Key Equipment

Sai Li,Xiukun Wei,Junyan Yu,Zhe Zhang,Limin Jia

doi:10.3390/app9071386

Abstract

The service capacity of each station has a direct impact on the capacity of a subway line and also the whole subway network. Therefore, it is critically important to keep the station capacity above a certain level in its full life cycle. This paper aims at keeping subway station capacity in a certain level range. In consideration of key equipment failure, the expected station capacity model is established. After that the lower bound of equipment reliability is determined by sensitivity analysis based on the equipment reliability-expected station capacity curve. Finally, the maintenance schedule optimization model is also proposed. The validity and practicability of the proposed method are demonstrated by a simulation case study.

Highlights

Subway stations play an important role in urban rail transit networks since passengers gather for boarding or alight at these locations
Gathering and scattering process of the subway station and the travel time of passengers is taken as indicator
In consideration of key equipment failure, the expected dynamical subway station capacity (DSSC) model is on the idea of binomial distribution and mathematical expectation

Summary

Introduction

Subway stations play an important role in urban rail transit networks since passengers gather for boarding or alight at these locations. The service capacity of each station has a direct impact on the capacity of subway line and on the whole subway network. It is critically important to keep the station service capacity above an acceptable level in its full life cycle. The station equipment’s performance deteriorates and its reliability decreases over time. Station capacity declines and the travel time of passengers increases, especially during rush hour periods. How to optimize key equipment maintenance schedule to maintain the station capacity in the full life cycle is significantly important for subway operation companies

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Conclusion