Traffic jam mitigation by the policy of maximum velocity limitation

Junya Masaka, Fumi Sueyoshi, Md. Anowar Hossain and Jun Tanimoto
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Junya Masaka: ��Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-Koen, Kasuga-Shi, Fukuoka 816-8580, Japan
Fumi Sueyoshi: ��Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-Koen, Kasuga-Shi, Fukuoka 816-8580, Japan
Md. Anowar Hossain: ��Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-Koen, Kasuga-Shi, Fukuoka 816-8580, Japan
Jun Tanimoto: ��Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-Koen, Kasuga-Shi, Fukuoka 816-8580, Japan†Faculty of Engineering Sciences, Kyushu University, Fukuoka 816-8580, Japan

International Journal of Modern Physics C (IJMPC), 2024, vol. 35, issue 06, 1-11

Abstract: This study explored whether a policy with maximum velocity limitation prior to each jam point in a traffic flow system can mitigate jam situations in a highway. To quantify this question, a new cellular automata traffic model based on the Revised S-NFS model was established. We perused two specific scenarios: a jam naturally brought by a high traffic density, and one brought by a lane-closed section placed as an explicit bottleneck. The result of multi-agent simulation (MAS) reveals that such maximum velocity limitation policy can certainly mitigate jam situations when each jam is naturally bought up not by a bottleneck, as proved by several statistics, and cannot improve the traffic flux.

Keywords: Traffic jam; traffic flow; cellular automaton; evolutionary game (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S012918312450075X

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