Back to School: Impact of Training on Driver Behavior and State in Autonomous Vehicles

摘要

Many producers of automated vehicle systems have begun testing autonomous vehicles on the road. In order to ensure safety and prevent crashes, human drivers are enlisted to monitor autonomous vehicles. However, operators of autonomous systems exhibit negative behavior adaptations in response to prolonged supervision of automation. To prevent the onset of undesirable behaviors in safety drivers, we must investigate driver state and behavior changes during the operation of highly automated vehicles. In the study presented here, we examine the effects of theoretical and practical training on the drivers' response to potentially critical situations in a longitudinal driving simulator study. We also present the effects of encountering a failure of the automated vehicle on driver state and behavior. We conducted a two-part panel driving simulator study (N=28), with an interval of 20–30 days between the training and testing sessions. We found that while participants with training are better prepared for a potential failure of the automation, participants in both conditions show a rise in sleepy or drowsy behavior before a potential failure of automation.