Understanding Hazardous Materials Transportation Accidents Based on Higher-Order Network Theory

Cuiping Ren, Bianbian Chen, Fengjie Xie, Xuan Zhao (), Jiaqian Zhang and Xueyan Zhou
Additional contact information
Cuiping Ren: School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
Bianbian Chen: School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
Fengjie Xie: School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
Xuan Zhao: Key Laboratory of Transportation Industry of Automotive Transportation Safety Enhancement Technology, Chang’an University, Xi’an 710064, China
Jiaqian Zhang: School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
Xueyan Zhou: School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China

IJERPH, 2022, vol. 19, issue 20, 1-13

Abstract: In hazardous materials transportation systems, accident causation analysis is important to transportation safety. Complex network theory can be effectively used to understand the causal factors of and their relationships within accidents. In this paper, a higher-order network method is proposed to establish a hazardous materials transportation accident causation network (HMTACN), which considers the sequences and dependences of causal factors. The HMTACN is composed of 125 first- and 118 higher-order nodes that represent causes, and 545 directed edges that denote complex relationships among causes. By analyzing topological properties, the results show that the HMTACN has the characteristics of small-world networks and displays the properties of scale-free networks. Additionally, critical causal factors and key relationships of the HMTACN are discovered. Moreover, unsafe tank or valve states are important causal factors; and leakage, roll-over, collision, and fire are most likely to trigger chain reactions. Important higher-order nodes are discovered, which can represent key relationships in the HMTACN. For example, unsafe distance and improper operation usually lead to collision and roll-over. These results of higher-order nodes cannot be found by the traditional Markov network model. This study provides a practical way to extract and construct an accident causation network from numerous accident investigation reports. It also provides insights into safety management of hazardous materials transportation.

Keywords: higher-order network; hazardous materials transportation accident; accident causation analysis; topological properties (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/19/20/13337/pdf (application/pdf)
https://www.mdpi.com/1660-4601/19/20/13337/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:19:y:2022:i:20:p:13337-:d:943696

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().