Directional vibrotactile takeover requests on a wrist-worn device: effects of age, pattern type, and urgency in automated driving.

Drivers are still required to perform the takeover task in highly automated vehicles. This task, which is cognitively and physically demanding, may present challenges for older adults due to general age-related declines in perception and cognition. Tactile modalities that may not be occupied by many non-driving-related tasks could serve as a potential solution for delivering takeover requests. Among these, directional vibrotactile stimuli presented via a wrist-worn device represent a promising approach. However, the effects of the two common types of directional vibrotactile patterns, dynamic patterns that vibrate sequentially at different locations and static patterns that vibrate at fixed locations, are still unknown. Therefore, this study aimed to investigate the effect of age (younger and older adults), vibrotactile pattern types (Baseline, Full-Dynamic, Semi-Dynamic, and Static), and interpulse interval (shorter (300 ms) and longer (800 ms)) on takeover performance. Forty participants (20 younger and 20 older adults) were engaged in the SAE Level 3 driving simulator study. Overall, Static and Baseline patterns were associated with faster reaction and takeover times and were perceived as more useful and satisfactory compared to the Full-Dynamic and Semi-Dynamic patterns. Shorter interpulse intervals (300 ms) for vibrotactile takeover requests resulted in better takeover performance, as indicated by shorter reaction and takeover times compared to longer interpulse intervals (800 ms). Finally, younger adults reacted faster to vibrotactile takeover requests than older adults did. The findings from the current study may inform the design of human-machine interfaces on wearable devices for next-generation automated vehicles.