A study of the factors affecting driving risk perception using the Bivariate Ordered Probit model.

Area of Science:

• Transportation Science
• Psychology
• Road Safety

Background:

• Driving risk perception is crucial for road safety.
• Understanding factors influencing risk perception can inform safety interventions.
• Previous research has not sufficiently explored these factors in the Iranian context.

Purpose of the Study:

• To identify key factors influencing driving risk perception among Iranian drivers.
• To compare the driving risk perception between passenger car drivers and truck drivers in Iran.

Main Methods:

• Surveys were conducted with passenger car drivers and truck drivers in Iran.
• Driving risk perception was assessed using Probability of Having a Road Accident (PHRA) and Probability of it being Fatal or causing Severe Injury (PFSI).
• A Bivariate Ordered Probit model was employed to analyze the data, considering correlations between PHRA and PFSI.

Main Results:

• Vehicle type, vehicle age, driving experience, sleep quality, at-fault accidents, safety equipment, and education level significantly impact driving risk perception.
• Truck drivers reported higher PHRA and PFSI compared to passenger car drivers.
• The Bivariate Ordered Probit model effectively explained variations in driving risk perception.

Conclusions:

• Specific driver and vehicle characteristics significantly influence driving risk perception in Iran.
• Truck drivers exhibit a heightened awareness of accident and injury risks.
• Findings can guide policymakers in developing targeted road safety regulations for different driver groups.