Review on the Application of the SIR Model in Predicting Urban Traffic Congestion: Successes and Future Directions

DOI

10.2991/978-94-6463-516-4_2How to use a DOI?

Keywords

infectious disease control; SIR epidemic model; transportation networks

Abstract

Simulating the propagation of congestion in urban rail transit systems is a complex and multifaceted task, especially when dealing with periods of excessive overcrowding. This study aims to address this challenge by presenting a predictive model for traffic congestion based on the SIR (Susceptible, Infected, Recovered) model commonly used in epidemiology. By formalizing the phenomenon of congestion as a process of susceptibility recovery, we hope to provide a more comprehensive understanding of how it spreads within urban rail networks.

In developing our predictive model, we have identified six key contributing factors that influence the rate at which congestion spreads. These factors include passenger flow, train intervals, ease of passenger transfers between lines or stations, timing of congestion events throughout the day, initial station affected by congestion, and overall station capacity. By considering these factors in our model, we aim to provide transit authorities and planners with valuable insights into how they can effectively manage and mitigate congestion within their systems.

To illustrate the potential impact of our SIR-based model on managing urban rail transit congestion, we offer an illustrative example that demonstrates its practical application. Through this example scenario, we hope to showcase how our approach can enhance existing strategies for addressing overcrowding and improving overall system efficiency.

Ultimately, our goal is to contribute to the development of more effective solutions for managing congestion in urban rail transit systems through data-driven modeling and analysis. We believe that by leveraging advanced predictive models such as the SIR framework, transit authorities can make informed decisions that lead to better service reliability and improved passenger experiences.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yiming Teng
AU  - Wo Wei
PY  - 2024
DA  - 2024/09/17
TI  - Review on the Application of the SIR Model in Predicting Urban Traffic Congestion: Successes and Future Directions
BT  - Proceedings of the 2024 5th International Conference on Urban Construction and Management Engineering (ICUCME 2024)
PB  - Atlantis Press
SP  - 4
EP  - 13
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-516-4_2
DO  - 10.2991/978-94-6463-516-4_2
ID  - Teng2024
ER  -