Highway safety is still a concerning issue despite different safety strategies, improvements in infrastructure, and in-vehicle technologies. Connected and Automated Vehicle (CAV) technology offers the possibility of improving highway safety through data exchange. Using a driving simulator and an eye-tracking system, this study investigates drivers’ behavior while influenced by certain CAV functions near a work zone. Driving speed, acceleration/deceleration and Takeover Reaction time (ToRt) when approaching and driving through a work zone with and without CAV capabilities are compared. The eye-tracking heat map proves that all participants noticed the takeover request (TOR) and responded accordingly. The analysis of variance (ANOVA) results indicate that the driving performance in two scenarios is different within the work zone and a buffer zone segment. The jerk analysis results suggest that the participants tend to drive with a lower frequency of acceleration and deceleration rate in the base scenario that has no autonomous feature. Regression analysis shows that participants who drive more mileages annually, have a shorter ToRt. Interestingly, ToRt decreases by age, and participants who trust CAV features have longer ToRt.
Publisher: Transportation Research Board
Publication Date: 2021
Source URL: Link to URL
Publication Types: Books, Reports, Papers, and Research Articles
Topics: Behavior; Connected Vehicles; Driver Performance; Driving Simulators; Work Zone Safety; Work Zones