Citation

Wu Y, Kihara K, Takeda Y, Sato T, Akamatsu M, Kitazaki S, Nakagawa K, Yamada K, Oka H, Kameyama S. Transp. Res. F Traffic Psychol. Behav. 2021; 81: 355-363.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.trf.2021.06.017

PMID

unavailable

Abstract

For automated driving at SAE level 3 or lower, driver performance in responding to takeover requests (TORs) is decisive in providing system safety. A driver state monitoring system that can predict a driver's performance in a TOR event will facilitate a safer control transition from vehicle to driver. This experimental study investigated whether driver eye-movement measured before a TOR can predict driving performance in a subsequent TOR event. We recruited participants (N = 36) to obtain realistic results in a real-vehicle study. In the experiment, drivers rode in an automated vehicle on a test track for about 32 min, and a critical TOR event occurred at the end of the drive. Eye movements were measured by a camera-based driver monitoring system, and five measures were extracted from the last 2-min epoch prior to the TOR event. The correlations between each eye-movement measure and driver reaction time were examined, and a multiple regression model was built using a stepwise procedure. The results showed that longer reaction time could be significantly predicted by a smaller number of large saccades, a greater number of medium saccades, and lower saccadic velocity. The implications of these relationships are consistent with previous studies. The present real-vehicle study can provide insights to the automotive industry in the search for a safer and more flexible interface between the automated vehicle and the driver.

Language: en

Keywords

Automated driving; Driver monitoring system; Eye movements; Real-vehicle study; Saccades; Takeover performance