Behind the Wheel of a Truck Simulator: Comparison of Self-Reported, Performance-Based, and Simulation Methods for...

Area of Science:

• Occupational Health
• Psychology
• Transportation Safety

Background:

• Traffic violations are a major public health issue, with professional drivers posing significant risks.
• Assessing driver behavior is crucial for enhancing road safety and preventing accidents.

Purpose of the Study:

• To compare the predictive validity of different assessment methods for traffic offenses in professional truck drivers.
• To identify the most effective tools for screening potentially unsafe drivers.

Main Methods:

• A pilot study involving 27 professional truck drivers.
• Utilized self-report questionnaires (Impulsiveness-Venturesomeness-Empathy Questionnaire, Road Traffic Behaviours Questionnaire), the Vienna Risk-Taking Test Traffic, and a truck driving simulator.
• Assessed performance based on speed variations in decision-making scenarios.

Main Results:

• The Road Traffic Behaviours Questionnaire (KZD) showed the strongest group differentiation between drivers with higher and lower self-reported offenses.
• Simulator performance differed significantly, with offense-reporting drivers exhibiting smaller speed reductions.
• Higher empathy scores were associated with fewer traffic offenses, indicating a role for social-emotional factors.

Conclusions:

• Domain-specific questionnaires and behavioral assessments are more effective than general personality measures for identifying at-risk drivers.
• A tiered screening approach, starting with cost-effective questionnaires and followed by simulator assessments for high-risk individuals, is recommended.
• These methods can help transport companies and regulatory bodies proactively identify and manage unsafe professional drivers.