Bayesian analysis of school bus accidents: a case study of China

Jiansong Wu (), Weipeng Fang, Xing Tong, Shuaiqi Yuan and Weiqi Guo
Additional contact information
Jiansong Wu: China University of Mining & Technology
Weipeng Fang: China University of Mining & Technology
Xing Tong: China University of Mining & Technology
Shuaiqi Yuan: China University of Mining & Technology
Weiqi Guo: China University of Mining & Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2019, vol. 95, issue 3, No 3, 463-483

Abstract: Abstract Prevention and control of school bus accidents have been a hot spot topic around the world. The catastrophic accident can result in severe casualties associated with negative social impacts. In this study, a Bayesian network (BN) model is established for school bus accident assessments considering the influential factors including human error, vehicle failure, environmental impacts and management deficiency. The conditional probabilities of a few root nodes are statistically obtained based on school bus accidents that occurred in the past decade in China. The conditional probabilities of other BN nodes are determined by expert knowledge with treatment by the Dempster–Shafer evidence theory. The consequences of different scenarios of school accidents are estimated via changing the state values of some BN nodes. Furthermore, by conducting sensitivity analysis to the proposed BN, it is identified that “overload” is the most influential factor causing a school accident. The results of the proposed model indicate that the integration of Bayesian network and the Dempster–Shafer evidence theory is an effective framework for school bus accident assessment, which could provide more practical analysis for school bus accidents. This study could contribute to providing technical supports for school bus safety particularly in developing countries.

Keywords: School bus accident; Overload; Human error; Vehicle failure; Bayesian network (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-018-3491-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:nathaz:v:95:y:2019:i:3:d:10.1007_s11069-018-3491-9

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-018-3491-9

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().