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An Analysis of the Ripple Effect of Congestion in a Specific Section Using the Robustness Sensitivity of the Traffic Network

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2023, 28(4), pp.83-91
  • DOI : 10.9708/jksci.2023.28.04.083
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : December 19, 2022
  • Accepted : January 26, 2023
  • Published : April 28, 2023

Chi-Geun Han 1 Sung-Geun Lee 1

1경희대학교

Accredited

ABSTRACT

In this paper, we propose a robustness sensitivity index (RSI) of highway networks to analyze the effect of congestion in a specific section on the entire highway. The newly proposed RSI is defined as the change in the total mileage of the transportation network per extended unit length when the length of a particular section is extended. When the RSI value is large, traffic congestion in the section has a worse effect on the entire network than in other sections. The existing network robustness index (NRI) simply observes changes in transportation networks with and without specific sections, but the RSI proposed in this study is a kind of performance indicator that allows quantitative analysis of the ripple effect of the entire network according to the degree of congestion in a specific section. While changing the degree of congestion in a particular section, it is possible to calculate how the traffic volume increases, decreases, and the size and location of the congestion section change. This analysis proves the superiority of RSI as it cannot be analyzed with NRI. Various properties of RSI are analyzed using data from the domestic highway network. In addition, using the RSI concept, it is shown that the ripple effect on other sections in which a change in the degree of congestion of a specific section occurs can be analyzed.

Citation status

* References for papers published after 2022 are currently being built.