Introduction: Driver error is a major factor in many traffic accidents, with cognitive capacity being the primary direct cause. Since not all drivers are risky (accident-prone), the best way to prevent collisions is to identify “dangerous” drivers—those with impaired cognitive function—before a collision happens and to what extent they are impaired while driving. The goal of this study is to identify drivers’ innate cognitive patterns as the main contributor to traffic accidents.
The participants in this study were divided into three cognitive E-S types (Type E, B, and S), using the Empathizing-Systemizing (E-S) model and its Empathy Quotient (EQ) and Systemizing Quotient (SQ) scales as indicators of cognitive traits to detect the relationship between traffic accidents/near misses experienced in the past.
Results: Based on the results, we were able to distinguish between a “safe” driver (Type E) and a “dangerous” driver (Type S), who had the largest number of close calls. Under the driving simulation environment incorporating the rUFOV approach, we could detect those variations and assess in terms of the driver’s visual attention capability (gaze reaction speed) .
Since not all drivers are equally “hazardous,” it is possible to test the “degree of accident-proneness” prior to driving and identify the possibility of a poor cognitive style using the E-S type. Then, we suggest include the E-S model in the driving aptitude exam (before a licence provision).
Toyota InfoTechnology Center, Co., Ltd., Tokyo, Japan.
Please see the link here: https://stm.bookpi.org/NTPSR-V7/article/view/7786
Keywords: Dangerous driver empathizing-systemizing, gaze response speed, traffic accident, near-miss