Vibrotactile Take-over Requests in Highly Automated Driving

Abstract

Highly automated vehicle has the possibility in getting stuck with edge scenarios where the automation cannot handle. Under this circumstance, sending out a takeover request and dragging the driver back into the control loop are required to avoid traffic accidents. Among various possible modalities for alerting drivers about take-over requests, vibrotactile alerts provide significant advantages. A driver-in-the-loop and hardware-in-the loop driving simulator was designed for the investigation of take-over performance. In this simulator, take-over signal was provided the vibration motors embedded in the vibrotactile seat. Moreover, body pressure mapping test illustrated that the vibration motors fixed in the vibrotactile seat would not reduce seating comfort. Twenty-four vibration patterns were generated via the vibration motors embedded in the backrest and cushion of the vibrotactile seat. Besides, Eighteen participants were recruited to take part in the experiment, which consisted of three sessions: 1) baseline (no driving task), 2) HAD (driving a highly automated vehicle and getting ready for the respond to the take-over request), 3) N-back (performing the same task with mental demanding task added in). Specifically, in baseline session, participants need the only answer regarding the type of vibration pattern. However in HAD and N-Back session, participants had to perform the maneuver (steering left/right or braking) according to the coding directional information of vibration patterns. Correct response rate and reaction time of each participant in each session were recorded and analysed. The results indicated that dynamic patterns yielded significantly higher correct response rate than static patterns. In addition, reaction times for dynamic patterns were faster than those for static patterns, but the effect was not statistically significant. Moreover, ANOVA tests illustrated that mental-demanding non-driving task had no significant effect on take-over performance.