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Optimizing Train Stopping Patterns for Congestion Management

Authors Tatsuki Yamauchi, Mizuyo Takamatsu, Shinji Imahori

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Tatsuki Yamauchi
Mizuyo Takamatsu
Shinji Imahori

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Tatsuki Yamauchi, Mizuyo Takamatsu, and Shinji Imahori. Optimizing Train Stopping Patterns for Congestion Management. In 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2017). Open Access Series in Informatics (OASIcs), Volume 59, pp. 13:1-13:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017) https://doi.org/10.4230/OASIcs.ATMOS.2017.13

Abstract

In this paper, we optimize train stopping patterns during 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. We apply our algorithm to railway lines in Tokyo including Keio Line with six types of trains and succeed in relaxing congestion with a small effect on travel time.

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Keywords
  • Train stopping pattern
  • Wardrop equilibrium
  • Congestion management
  • Local search algorithm
  • Event-activity network

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