Using psychophysiological metrics for understanding drivers’ mental workload and visual attention when overtaking automated truck platoons

The automated truck platoon is one of the most promising connected autonomous vehicle technologies and is expected to become mainstream in the future. It is foreseeable that automated truck platoons and human drivers will share the roads and interact regularly. As a new traffic element, the truck platoon may influence other drivers’ behaviors and mental states, potentially compromising the safety of mixed traffic. While existing studies have extensively explored drivers’ behavioral responses to truck platoons, little is known about their psychophysiological states during such interactions, particularly how platoon organization influences drivers’ mental workload and attention. To address this gap, a comprehensive set of platoon organization factors was considered, and a high-fidelity driving simulator experiment was conducted. The study employed a 2 (platoon speed: 80 km/h vs. 100 km/h) × 2 (platoon size: three vs. five trucks) × 2 (inner gap: 5 m vs. 25 m) × 2 (traffic environment: presence vs. absence of a lead vehicle) within-subjects factorial design. Drivers’ heart rate, pupil diameter, gaze dispersion, and subjective mental workload ratings were recorded and analyzed, with data collected from 35 participants. Results showed that compared to the baseline, drivers’ horizontal gaze dispersion was more concentrated during interactions with the truck platoon. Furthermore, an inner gap of 5 m can significantly increase drivers’ mental workload compared to an inner gap of 25 m, as indicated by mean heart rate and mean pupil diameter. Regarding platoon speed, drivers’ horizontal gaze was more dispersed at a platoon speed of 100 km/h compared to 80 km/h, likely due to greater attention to maintain lateral distance from the median divider and the platoon. Moreover, drivers’ mental workload showed a significant decreasing trend with repeated interactions with the truck platoon. These findings provide insights into the operational strategies of truck platoons from a human factors perspective.