[A comprehensive evaluation on psychological quality among automobile drivers]

Area of Science:

• Psychology
• Traffic Safety
• Data Science

Context:

• Automobile drivers' psychological quality is crucial for road safety.
• Existing evaluation methods may not comprehensively assess psychological factors.
• Accident proneness is a significant concern in professional driving.

Purpose:

• To develop and validate a comprehensive evaluation system for automobile drivers' psychological quality.
• To establish reliable metrics for assessing psychological and physiological indexes.
• To identify potential accident-prone drivers through a robust evaluation framework.

Summary:

• A seven-index system, incorporating psychological and physiological measures, was created using the Delphi method and statistical analysis.
• Data from over 14,000 drivers (occupational and trainees) across five Chinese cities were analyzed.
• Analytical Hierarchy Process (AHP) determined index weights, leading to evaluation equations for different driver groups.

Impact:

• The developed comprehensive evaluation equations demonstrated significant differences between drivers with and without accident histories.
• The system proved reliable, with a high consistency rate (92.99%) and kappa value (0.85).
• This evaluation tool is deemed reasonable and feasible for detecting potentially accident-prone drivers, contributing to proactive safety measures.