Volume List  / Volume 9 (4)



DOI: 10.7708/ijtte.2019.9(4).02

9 / 4 / 365 - 375 Pages


Danish Farooq - Department of Transport Technology and Economics, Budapest University of Technology and Economics, 1111 Budapest, Műegyetem rakpart 3, Hungary -

Sarbast Moslem - Department of Transport Technology and Economics, Budapest University of Technology and Economics, 1111 Budapest, Műegyetem rakpart 3, Hungary -

Rana Faisal Tufail - College of Architecture and Environment, Sichuan University 610065, China -


Driver behavior has been found one of the most influential factors on road safety. Driver behavior identification is key to solve road safety issues related to driver behavior. This study aims to identify and quantify the significant driver behavior factors affecting road safety by using Analytic Network Process applications. The driver behavior dataset is collected from a self-reported questionnaire survey from novice and experienced drivers. The ANP pairwise comparison results are utilized to rank the driver behavior factors based on normalized weights. The ANP results showed that “driving without alcohol use” was the most significant driver behavior criteria for both groups. For experienced drivers, the lowest rank observed driver behavior criteria is “maintain safe gap between vehicles”. While for novice drivers the lowest rank observed driver behavior criteria is “use personal intelligent assistant”. Furthermore, the Analytic network process (ANP) model found that most of driver behavior factors are interrelated based on driver groups responses. Finally, the Kendall’s rank correlation is applied to estimate the concordant degree between evaluator groups. The results evaluated that there is a medium correlation between the driver groups but not a perfect agreement. The study results can help traffic safety authorities to focus on significant driver behavior criteria to solve road issues.

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