Optimizing train stopping patterns for congestion management

Tatsuki Yamauchi, Mizuyo Takamatsu () and Shinji Imahori ()
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Tatsuki Yamauchi: Internet Initiative Japan Inc.
Mizuyo Takamatsu: Chuo University
Shinji Imahori: Chuo University

Public Transport, 2023, vol. 15, issue 1, No 1, 29 pages

Abstract: Abstract In this paper, we optimize train stopping patterns during the morning rush hour in Japan. Since trains are extremely crowded, we need to determine stopping patterns based not only on travel time but also on congestion rates of trains. We exploit a Wardrop equilibrium model to compute passenger flows subject to congestion phenomena and present an efficient local search algorithm to optimize stopping patterns which iteratively computes a Wardrop equilibrium. The framework of the proposed algorithm is extended to solve the problem of optimizing the number of services for each train type. We apply our algorithms to railway lines in Tokyo including the Keio Line with six types of trains and demonstrate that we succeed in relaxing congestion.

Keywords: Train stopping pattern; Wardrop equilibrium; Local search algorithm; Event-activity network (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s12469-021-00286-w

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