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Evaluating Highway Traffic Safety: An Integrated Approach

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

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Authors

Yanqun Yang

Said M. Easa

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

Files

Published Journal Article (2 Mb)
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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.






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