Estimation of Safety Margin Based on the Personality Traits Aiming at the Personalized Driving Assistance System

Key Points

• This research aims to predict the safety margin of drivers based on their personality traits without using driving data.
• Conducted experiments using a driving simulator to collect data during lane changes.
• Calculated a risk level metric that reflects each driver's acceptable risk.
• Developed a predictive model using partial least squares regression with personality traits as predictors.
• The predictive model showed high accuracy without needing personalized driving data.
• The approach suggested effectiveness in adapting driving assistance systems for individuals.
• It indicated potential improvements over existing methods that require extensive data collection.