Identification of Road Crash Severity Ranking by Integrating the Multi-Criteria Decision-Making Approach

7Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

Abstract

This research aims to provide a novel approach for analysing road crash severity ranking by integrating all injury classified crash types. The road crash data of all Indian states (i.e., Andhrapradesh, Arunachal Pradesh, Bihar, etc.) for 2019 were incorporated to analyse severity rankings by using multi-criteria decision-making (MCDM) methods. Two of these methods – the Analytical Hierarchy Process (AHP) and Technique for Order Performance by Similarity to an Ideal Solution (TOPSIS) – were applied. The application of MCDM methods easily incorporated the injury classified crash data and provided clear rankings. Further, the correlation analysis of rankings provided by both MCDM methods proved the validity of the proposed research. Therefore, this approach is considered to have great potential to reform conventional severity ranking practices.

Cite

CITATION STYLE

APA

Trivedi, P., & Shah, J. (2022). Identification of Road Crash Severity Ranking by Integrating the Multi-Criteria Decision-Making Approach. Journal of Road Safety, 33(2), 33–44. https://doi.org/10.33492/JRS-D-21-00055

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free