An innovative gravity-based approach to assess vulnerability of a Hazmat road transportation network: A case study of Guangzhou, China. (July 2018)

• Record Type: Journal Article
• Authors: Zhong, Huiling; Wang, Jun; Yip, Tsz Leung; Gu, Yimiao
• Is Part Of: Transportation research. Volume 62(2018)
• Page Start: 659
• Page End: 671
• Publication Date: 2018-07
• Subjects: Vulnerability -- Hazmat transportation -- Road transportation -- Gravity model -- Guangzhou/China; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2018.03.003
• Languages: English
• ISSNs: 1361-9209

Abstract

Abstract: The transportation of hazardous material (hereinafter referred to as Hazmat) is different from general cargo. If a Hazmat road transportation accident occurs, it will not only cause significant casualties and road network damage but also threaten the safety of the lives and property of the residents near the road. Therefore, a quantitative vulnerability analysis of the Hazmat road transportation network is developed to assess the vulnerability of each link, which can help improve the road transportation risk management level. First, we propose an indicator to measure the relevance between two links based on comprehensive analysis of the road transportation network topology and Hazmat road transportation risk characteristics. Second, we discover that we cannot identify road vulnerability using only topology and risk characteristics alone. Thus, an Impact Strength model is developed to assess Hazmat road transportation vulnerability. This model is based on the classical Gravity model and considers both topology and risk characteristics. Relevant algorithms are proposed accordingly. Third, we use Guangzhou's Hazmat highway transportation as a case study to verify our Impact Strength model. The related statistics data are collected, and ArcGIS software is employed. By using this model, we can calculate the Impact Strength of each link in the whole transportation network. The empirical results verify that this innovative Impact Strength model can help to identify the links with significant vulnerabilities, which can thus help to reduce road transportation risk in advance and build the road transportation risk early-warning mechanism. This innovative model can also be used to support the relevant decision-making process for further analysis.