Context-Adaptive Availability Notifications for an SAE Level 3 Automation

Danner, Simon; Feierle, Alexander; Manger, Carina; Bengler, Klaus · 2021 · Crossref

DOI: 10.3390/mti5040016

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Summary

This study investigates the efficacy of context-adaptive availability notifications for SAE Level 3 automated driving systems, addressing the problem of "automation surprise." When drivers develop mental models of system availability based on past experiences, unexpected changes in availability—either sudden non-availability when expected, or sudden availability when not expected—can lead to frustration, decreased acceptance, and increased mental workload. The authors hypothesized that a context-adaptive Human-Machine Interface (HMI), which explicitly informs drivers of these deviations from their expected patterns, would improve acceptance and usability, reduce frustration, decrease gaze deviation from the road during manual driving, and accelerate the activation of the automation when it unexpectedly becomes available. The research was conducted using a within-subjects design in a static driving simulator with 30 participants. Participants completed five simulated journeys representing a weekly commute, allowing them to establish expectations regarding ADS availability on specific highway segments. The experimental conditions involved two scenarios where availability patterns deviated from the established norm: one where the ADS was unexpectedly unavailable, and another where it was unexpectedly available. Participants experienced both a standard HMI and a context-adaptive HMI, which provided explicit notifications about the changed availability status. Data collection included subjective ratings of acceptance, usability, and frustration, as well objective measures of gaze behavior (frequency of looking at the instrument cluster) and ADS activation times. The results failed to statistically confirm any of the five hypotheses. Contrary to expectations, the context-adaptive HMI did not improve acceptance or usability ratings, nor did it reduce frustration levels. Regarding gaze behavior, the study found opposite effects to those hypothesized; participants using the context-adaptive HMI exhibited increased distraction, indicated by more frequent glances at the instrument cluster, rather than reduced gaze deviation. While there was a non-significant trend toward faster ADS activation times with the context-adaptive notifications in cases of unexpected availability, this effect was not statistically robust. The study concludes that context-adaptive availability notifications are not universally beneficial and may inadvertently increase driver distraction. The findings suggest that while transparency is important, the specific implementation of context-adaptive notifications in this study induced negative side effects. The authors imply that more salient notifications might be advantageous specifically for unexpected availability scenarios to ensure drivers recognize the opportunity to engage the automation, but caution that such adaptations must be carefully designed to avoid increasing cognitive load or visual distraction. This research highlights the complexity of designing HMIs that manage driver expectations and mental models in automated driving contexts.

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• automation surprise