An autonomous vehicle simulation study : the misunderstood impact of a night driving environment on takeover performance

Abstract

Recent studies that have examined the takeover process for autonomous vehicles relied on the theory of situational awareness as the foundation for driving performance. However, when thoroughly examined, situational awareness is found to work in a system of processes which is influenced by both the driver and the surrounding environment in context to driving. As previous studies have found the night driving environment to decrease driving performance in manual driving, the present study aims to examine such effects on the takeover process in an automated vehicle. Additionally, this study also considered the influence of different hazard types on takeover performance. The measures of driving performance examined include the mean takeover time, collision rate and takeover quality. A total of 32 participants (22 men, 11 women) completed the study. The participants went through a total of seven driving trials, of which consisted of three practice trials and four test trials. All participants were engaged with a media tablet before the takeover process. Their takeover performance was recorded with the UC-win/Road software with a precision of 0.1 seconds. Results indicate that, in the night driving environment, participants show a significantly higher mean takeover time and higher collision rate as compared to the day driving condition. Moreover, results also show that when facing a person hazard, participants had a significantly higher collision rate and different takeover quality as compared to facing a car hazard. This suggested that drivers showed worse takeover performance in the night driving environment or when facing person hazards.