| Literature DB >> 32174362 |
Damee Choi1, Toshihisa Sato2, Takafumi Ando3, Takashi Abe4, Motoyuki Akamatsu2, Satoshi Kitazaki2.
Abstract
The present study investigated effects of cognitive and visual loads on driving performance after take-over request (TOR) in an automated driving task. Participants completed automated driving in a driving simulator without a non-driving related task, with an easy non-driving related task, and with a difficult non-driving related task. The primary task was to monitor the environment and the system state. An N-back task and a Surrogate Reference Task (SuRT) were adapted to induce cognitive and visual loads respectively. The system followed a front vehicle automatically. Driving performance was measured by responses to a critical event (appearance of a broken-down car) after the automated system issued TOR and then terminated. High subjective difficulty of the N-back task was related to increased time and increased steering angle variance in the time course from onset of steering control to lane change, while high subjective difficulty of SuRT was related to increased steering angle variance in the time course after lane change. This suggests that both cognitive and visual loads affect driving performance after TOR in automated driving, but the effects appear in different time courses.Entities:
Keywords: Automated driving; Cognitive load; Driving performance; Take-over request; Visual load
Mesh:
Year: 2020 PMID: 32174362 DOI: 10.1016/j.apergo.2020.103074
Source DB: PubMed Journal: Appl Ergon ISSN: 0003-6870 Impact factor: 3.661