Evaluating Highway Traffic Safety: An Integrated Approach

Yang, Yanqun; Easa, Said M.; Lin, Zhibin; Zheng, Xinyi

doi:10.1155/2018/4598985

Evaluating Highway Traffic Safety: An Integrated Approach

Yang, Yanqun; Easa, Said M.; Lin, Zhibin; Zheng, Xinyi

Authors

Yanqun Yang

Said M. Easa

Professor Zhibin Lin zhibin.lin@durham.ac.uk
Professor

Xinyi Zheng

Abstract

This paper presents a novel methodology for determining the overall highway safety level by integrating statistical analysis and analytic network process (ANP) with set pair analysis (SPA) which is applied in the evaluation of the overall highway safety for the first time. The methodology accounts for both quantitative and qualitative factors that contribute to traffic safety. The statistical analysis uses crash, alignment, intersection, and other data to determine the significant indices (variables) that affect safety. These indices are then combined with the planning (qualitative) indices to determine the weights of all indices based on expert opinions using ANP. Finally, the overall safety level of the highway is determined using SPA. The methodology is illustrated using data collected from two highways in China. The results demonstrate that the proposed methodology is sound and reliable. The methodology is applicable to existing or new highways and can help to effectively evaluate the overall safety of a highway and develop long-term strategies for safety improvements.

Citation

Yang, Y., Easa, S. M., Lin, Z., & Zheng, X. (2018). Evaluating Highway Traffic Safety: An Integrated Approach. Journal of Advanced Transportation, 2018, Article 4598985. https://doi.org/10.1155/2018/4598985

Journal Article Type	Article
Acceptance Date	Mar 12, 2018
Online Publication Date	Jun 4, 2018
Publication Date	Jun 4, 2018
Deposit Date	Jul 12, 2018
Publicly Available Date	Jul 12, 2018
Journal	Journal of Advanced Transportation
Print ISSN	0197-6729
Electronic ISSN	2042-3195
Publisher	Hindawi
Peer Reviewed	Peer Reviewed
Volume	2018
Article Number	4598985
DOI	https://doi.org/10.1155/2018/4598985
Public URL	https://durham-repository.worktribe.com/output/1321404

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2018 Yanqun Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.