Online Passenger Flow Control in Metro Lines
成果类型：
Article
署名作者：
Liang, Jinpeng; Lyu, Guodong; Teo, Chung-Piaw; Gao, Ziyou
署名单位：
Dalian Maritime University; Hong Kong University of Science & Technology; National University of Singapore; National University of Singapore; Beijing Jiaotong University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.2022.2417
发表日期：
2023
页码：
768-775
关键词：
摘要：
Crowd management during peak commuting hours is a key challenge facing oversaturated metro systems worldwide, which results in serious safety concerns and uneven service experience for commuters on different origin-destination (o-d) pairs. This paper develops realtime passenger flow control policies to manage the inflow of crowds at each station, to optimize the total load carried or revenue earned (efficiency), and to ensure that adequate service is provided to passengers on each o-d pair (fairness), as much as possible. For given train capacity, we use Blackwell's approachability theorem and Fenchel duality to characterize the attainable service level of each o-d pair. We use these insights to develop online policies for crowd control problems. Numerical experiments on a set of transit data from Beijing show that our approach performs well compared with existing benchmarks in the literature.
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