search for




 

A study on traffic impact by heavy rain using betweenness centrality analysis
Journal of the Korean Data & Information Science Society 2021;32:49-61
Published online January 31, 2021;  https://doi.org/10.7465/jkdi.2021.32.1.49
© 2021 Korean Data and Information Science Society.

Okyu Kwon1 · Byung Sik Kim2 · Seung Kwon Jung3

1National Institute for Mathematical Science

2Kangwon National University

3International Center for Urban Water Hydroinformatics Research & Innovation
Correspondence to: 1Researcher, National Institute for Mathematical Science, Daejeon 34114, Korea.
2Professor, Kangwon National University, Samcheok 25913, Korea.
3Corresponding author: International Center for UrbanWater Hydroinformatics Research & Innovation, Incheon 21999, Korea. E-mail: skjung6779@gmail.com

This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI 2018-03013.
Received October 24, 2020; Revised December 3, 2020; Accepted December 7, 2020.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
We propose a technique to measure the impact of loss of traffic function in a particular area to surrounding areas. The proposed method is applied to the city of Seoul, which is the capital of South Korea with a population of about ten million. Based on the actual road network in Seoul, we construct an abstract road network between 1km×1km grid cells. The link weight of the abstract road network is re-adjusted considering traffic volume measured at several survey points. On the modified abstract road network, we evaluate the traffic vulnerability by calculating a network measure of betweenness centrality (BC) for every single grid cells. This study analyzes traffic impacts caused by road dysfunction due to heavy rainfall in urban areas.
Keywords : Betweenness centrality, heavy rain, road network, traffic impact.