Online Passenger Flow Control in Metro Lines

Jinpeng Liang (), Guodong Lyu (), Chung-Piaw Teo () and Ziyou Gao ()
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Jinpeng Liang: School of Transportation Engineering, Dalian Maritime University, Dalian, Liaoning 116026, China
Guodong Lyu: School of Business and Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Chung-Piaw Teo: Institute of Operations Research and Analytics, National University of Singapore, Singapore 117602; NUS Business School, National University of Singapore, Singapore 119245
Ziyou Gao: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100080, China

Operations Research, 2023, vol. 71, issue 2, 768-775

Abstract: 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 real-time 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.

Keywords: Transportation; metro system oversaturation; passenger flow control; online algorithm; fairness (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:71:y:2023:i:2:p:768-775

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