The assessment of significant factors affecting risk perception analysis road safety is critical to avoid road accidents. This study evaluates and prioritizes the main factors and sub factors influencing road safety among Novice and Experienced driver groups using the Spherical Fuzzy Analytic Hierarchy Process (SFAHP). A two-level hierarchical structure was utilized to analyse the main factors and sub-factors contributing to road safety. To collect data, the questionnaire survey designed on fuzzy scale utilized for two groups of drivers having different driving experience. SFAHP was applied for specified driver groups to rank the main factors and sub factors in a two-level hierarchical structure. The study results showed that for Novice drivers in Level 1, ‘Adverse geometric condition’ was identified as the most influential factor as compared to other observed factors. For Experienced drivers in Level 1, SFAHP results showed ‘Poor road surface condition’ as first rank factor based on measured weights. While ‘Inappropriate traffic operational control’ was observed as the last rank factor for both novice and experienced drivers. For novice drivers in level 2 with respect to “Adverse geometric condition”, results showed ‘Improper sight distance’ as first rank factor followed by ‘Improper road width’ based on measured weights. For experienced drivers in level 2 with respect to “Adverse geometric condition”, the results showed ‘Improper road width’ as first rank factor followed by ‘Improper gradient’ based on measured weights. For novice drivers in level 2 with respect to “Poor road surface condition”, results showed ‘High rut depth’ as first rank factor followed by ‘Inadequate skid resistance’ based on measured weights. For experienced drivers in level 2 with respect to “Poor road surface condition”, results showed ‘Inadequate skid resistance’ as first rank factor followed by ‘High rut depth’ based on measured weights. For level 2 with respect to “Improper traffic operation control”, results showed ‘Improper traffic signal’ as first rank factor for both novice and experienced driver groups. These findings highlight age-specific behavioral tendencies and provide insight for developing tailored interventions to improve road safety. Expanding the model to include real time environmental inputs and driver-vehicle interactions could also improve the predictive capability of future studies.Abs
Farooq et al. (Fri,) studied this question.
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