Human Factors and Road Safety

Ghaidaa Abdulwahab  Majeed; Abeer Khudhur Jameel

doi:10.71229/vm66h821

Authors

Ghaidaa Abdulwahab Majeed Highway and Transportation Engineering Department, College of Engineering, Mustansiriyah University, Baghdad, Iraq
Abeer Khudhur Jameel Highway and Transportation Engineering Department, College of Engineering, Mustansiriyah University, Baghdad, Iraq

DOI:

https://doi.org/10.71229/vm66h821

Keywords:

Human factors, , Risk perception,, Motorcycle safety,, Three-wheelers,, Machine learning

Abstract

Human factors play a critical role in road safety, particularly among vulnerable road users such as motorcycle and three-wheeler operators. This review examines the theoretical and methodological foundations of driver safety behavior and risk perception and evaluates their emerging integration with machine-learning approaches. The review covers Driver Behavior Theory, Risk Compensation Theory, the Theory of Planned Behavior, questionnaire-based safety assessment, self-reported driving behavior, behavioral safety indices, and machine-learning-based risk prediction. The reviewed literature demonstrates that attitudes, risk perception, behavioral intentions, traffic-rule compliance, and other rider characteristics are important determinants of safety-related behavior. However, existing studies remain dominated by cross-sectional self-reported surveys and traditional statistical approaches, with many focusing on specific rider populations. The review identifies four major research gaps: limited integration of subjective safety indicators with machine learning, potential biases associated with self-reported behavior, insufficient linkage between subjective safety measures and crash-related outcomes, and a lack of integrated frameworks combining behavioral, perceptual, demographic, and crash-related information. Future research should develop and validate integrated predictive frameworks that combine these dimensions to improve rider-risk classification and support targeted road-safety interventions for motorcycle and three-wheeler users.

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