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Journal Article

Citation

Maggi D, Romano R, Carsten O. Hum. Factors 2020; ePub(ePub): ePub.

Copyright

(Copyright © 2020, Human Factors and Ergonomics Society, Publisher SAGE Publishing)

DOI

10.1177/0018720820946183

PMID

32865032

Abstract

OBJECTIVE: A driving simulator study explored how drivers behaved depending on their initial role during transitions between highly automated driving (HAD) and longitudinally assisted driving (via adaptive cruise control).

BACKGROUND: During HAD, drivers might issue a take-over request (TOR), initiating a transition of control that was not planned. Understanding how drivers behave in this situation and, ultimately, the implications on road safety is of paramount importance.

METHOD: Sixteen participants were recruited for this study and performed transitions of control between HAD and longitudinally assisted driving in a driving simulator. While comparing how drivers behaved depending on whether or not they were the initiators, different handover strategies were presented to analyze how drivers adapted to variations in the authority level they were granted at various stages of the transitions.

RESULTS: Whenever they initiated the transition, drivers were more engaged with the driving task and less prone to follow the guidance of the proposed strategies. Moreover, initiating a transition and having the highest authority share during the handover made the drivers more engaged with the driving task and attentive toward the road.

CONCLUSION: Handover strategies that retained a larger authority share were more effective whenever the automation initiated the transition. Under driver-initiated transitions, reducing drivers' authority was detrimental for both performance and comfort.

APPLICATION: As the operational design domain of automated vehicles (Society of Automotive Engineers [SAE] Level 3/4) expands, the drivers might very well fight boredom by taking over spontaneously, introducing safety issues so far not considered but nevertheless very important.


Language: en

Keywords

driver behavior; vehicle automation; autonomous driving; human–automation interaction; intelligent vehicle systems

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