To Inform or to Instruct? An Evaluation of Meaningful Vibrotactile Patterns to Support Automated Vehicle Takeover Performance

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IEEE Transactions on Human-Machine Systems




Automated vehicles may occasionally require drivers to take over. The complexity of the takeover process warrants the design of effective human–machine interfaces that assist drivers in regaining control, especially when the visual and auditory sensory modalities are occupied. Vibrotactile displays, which can represent information about the status, direction, and position of driving environment elements, have been suggested as one promising approach, but their effectiveness to aid in takeover transitions has not been fully evaluated. This study investigated the effects of meaningful tactile signal patterns, used as takeover requests, on automated vehicle takeover performance. Forty participants rode in a simulated SAE Level 3 automated vehicle and completed a series of takeover tasks with two tactile pattern formats, i.e., informative (which displayed status information of surrounding vehicles) and instructional (that displayed the appropriate takeover maneuver), and three in-vehicle locations (seat back, seat pan, and a seat back and seat pan combination). Takeover response options included lane changes only or brake applications followed by changing lanes, depending on the locations of surrounding vehicles. Results indicate that only meaningful instructional tactile signals, in either the seat back or seat pan, were associated with worse takeover response time and maximum resulting acceleration compared to signals without any patterns. Additionally, tactile information presented on the seat back was perceived as the most useful and satisfying. Findings from this study can inform the development of next-generation human–machine interfaces that utilize tactile stimulation in a wide range of environments with automation.


Automated driving, Brakes, haptics, human–machine interfaces, Lead, Protocols, tactile displays, takeover, Task analysis, Time factors, Vehicles, Visualization


Industrial and Systems Engineering