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Evaluation of Imminent Take-Over Requests With Real Automation on a Test Track
Philipp Wintersberger1,2, Clemens Schartmüller2,3, Shadan Sadeghian4
1TU Wien, Austria.
Objective:
Investigating take-over, driving, non-driving related task (NDRT) performance, and trust of conditionally automated vehicles (AVs) in critical transitions on a test track.
Background:
Most experimental results addressing driver take-over were obtained in simulators. The presented experiment aimed at validating relevant findings while uncovering potential effects of motion cues and real risk.
Method:
Twenty-two participants responded to four critical transitions on a test track. Non-driving related task modality (reading on a handheld device vs. auditory) and take-over timing (cognitive load) were varied on two levels. We evaluated take-over and NDRT performance as well as gaze behavior. Further, trust and workload were assessed with scales and interviews.
Results:
Reaction times were significantly faster than in simulator studies. Further, reaction times were only barely affected by varying visual, physical, or cognitive load. Post-take-over control was significantly degraded with the handheld device. Experiencing the system reduced participants' distrust, and distrusting participants monitored the system longer and more frequently. NDRTs on a handheld device resulted in more safety-critical situations.
Conclusion:
The results confirm that take-over performance is mainly influenced by visual-cognitive load, while physical load did not significantly affect responses. Future take-over request (TOR) studies may investigate situation awareness and post-take-over control rather than reaction times only. Trust and distrust can be considered as different dimensions in AV research.
Application:
Conditionally AVs should offer dedicated interfaces for NDRTs to provide an alternative to using nomadic devices. These interfaces should be designed in a way to maintain drivers' situation awareness.
PréCis:
This paper presents a test track experiment addressing conditionally automated driving systems. Twenty-two participants responded to critical TORs, where we varied NDRT modality and take-over timing. In addition, we assessed trust and workload with standardized scales and interviews.
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