Online Passenger Flow Control in Metro Lines
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.
Funding: This work was supported in part by the National Natural Science Foundation of China [Grants 72288101 and 72101042], the Natural Science Foundation of Chongqing, China [Grant CSTB2022NSCQ-MSX1667], and the 2019 Academic Research Fund Tier 3 of the Ministry of Education—Singapore [Grant MOE-2019-T3-1-010].
Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2022.2417.
