Assessment of Significant Factors Affecting Frequent Lane-Changing Related to Road Safety: An Integrated Approach of the AHP–BWM Model

Danish Farooq, Sarbast Moslem, Arshad Jamal, Farhan Muhammad Butt, Yahya Almarhabi, Rana Faisal Tufail and Meshal Almoshaogeh
Additional contact information
Danish Farooq: Department of Civil Engineering, Comsats University Islamabad, Wah Campus, Wah 47040, Pakistan
Sarbast Moslem: Department of Transport Technology and Economics, Budapest University of Technology and Economics, 1111 Budapest, Hungary
Arshad Jamal: Department of Civil and Environmental Engineering, College of Design and Built Environment, King Fahd University of Petroleum & Minerals, KFUPM Box 5055, Dhahran 31261, Saudi Arabia
Farhan Muhammad Butt: Transportation and Traffic Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31451, Saudi Arabia
Yahya Almarhabi: Center of Excellence in Trauma and Accidents, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Rana Faisal Tufail: Department of Civil Engineering, Comsats University Islamabad, Wah Campus, Wah 47040, Pakistan
Meshal Almoshaogeh: Department of Civil Engineering, College of Engineering, Qassim University, Buraydah 51452, Saudi Arabia

IJERPH, 2021, vol. 18, issue 20, 1-17

Abstract: Frequent lane changes cause serious traffic safety concerns for road users. The detection and categorization of significant factors affecting frequent lane changing could help to reduce frequent lane-changing risk. The main objective of this research study is to assess and prioritize the significant factors and sub-factors affecting frequent lane changing designed in a three-level hierarchical structure. As a multi-criteria decision-making methodology (MCDM), this study utilizes the analytic hierarchy process (AHP) combined with the best–worst method (BWM) to compare and quantify the specified factors. To illustrate the applicability of the proposed model, a real-life decision-making problem is considered, prioritizing the most significant factors affecting lane changing based on the driver’s responses on a designated questionnaire survey. The proposed model observed fewer pairwise comparisons (PCs) with more consistent and reliable results than the conventional AHP. For level 1 of the three-level hierarchical structure, the AHP–BWM model results show “traffic characteristics” (0.5148) as the most significant factor affecting frequent lane changing, followed by “human” (0.2134), as second-ranked factor. For level 2, “traffic volume” (0.1771) was observed as the most significant factor, followed by “speed” (0.1521). For level 3, the model results show “average speed” (0.0783) as first-rank factor, followed by the factor “rural” (0.0764), as compared to other specified factors. The proposed integrated approach could help decision-makers to focus on highlighted significant factors affecting frequent lane-changing to improve road safety.

Keywords: frequent lane-changing; road safety; prioritize; multi-criteria decision making; analytic hierarchy process; best–worst method (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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