Safety Compensation for Improving Driver Takeover Performance in Conditionally Automated Driving

Yao, Hua; An, Suyang; Zhou, Huiping; Itoh, Makoto; Department of Risk Engineering, Graduate School of Systems and Information Engineering, University of Tsukuba 1-1-1 Tennodai, Tsukuba 305-8573, Japan; Faculty of Engineering, Information and Systems, University of Tsukuba 1-1-1 Tennodai, Tsukuba 305-8573, Japan · 2020 · Crossref

DOI: 10.20965/jrm.2020.p0530

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Summary

This study investigates the efficacy of "safety compensation"—specifically, automatic vehicle deceleration triggered by a Request to Intervene (RTI)—on driver takeover performance in conditionally automated driving (SAE Level 3). The research addresses the challenge that drivers engaged in non-driving related tasks (NDRT) may lack the situational awareness required for timely and safe manual control resumption. The authors hypothesized that automatic deceleration would act as a trigger for faster response and improve takeover quality, potentially varying across different driving scenarios. The experiment utilized a high-fidelity Mitsubishi driving simulator with 16 licensed participants (ages 21–34). A within-subjects design was employed, where each participant completed six trials across three distinct takeover scenarios: fog, route choosing, and lane closing. In half of the trials, the system executed an automatic brake stroke (−1.11 m/s²) upon RTI issuance; in the other half, no compensation occurred. Participants performed a Tetris game on an iPad during automated driving to simulate distraction. The time budget from RTI to a critical event was fixed at 7 seconds. Performance metrics included takeover time, maximum driver brake input, time to event (TTE), maximum steering wheel angle, and maximum lateral acceleration. Results indicated that safety compensation did not significantly reduce takeover time, nor did it affect maximum steering wheel angle. However, it significantly improved longitudinal driving performance. Specifically, safety compensation led to a significantly higher TTE and reduced maximum driver brake input across all scenarios, indicating that the automatic deceleration provided a larger safety margin and reduced the physical braking effort required by the driver. Regarding lateral performance, safety compensation significantly reduced maximum lateral acceleration only in the high-emergency "lane closing" scenario, with no significant effects observed in the fog or route choosing scenarios. The findings suggest that while automatic deceleration does not accelerate the driver's cognitive response or initial reaction time, it effectively enhances the safety of the transition by extending the time available before a critical event and mitigating harsh braking maneuvers. This implies that safety compensation is a valuable strategy for ensuring safe handovers in conditionally automated vehicles, particularly in scenarios requiring immediate lateral maneuvers, such as lane closures. The study highlights that while drivers may not react faster to the RTI itself, the system's proactive speed reduction compensates for delayed human response, thereby maintaining vehicle safety.

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Topics

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• takeover transitions
• automation
• manual
• automation surprise
• situational awareness
• hands on hands off engagement

Information type

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• Empirical Findings: behavioral performance data
• Methodological Resource: measurement protocol
• Theoretical Contribution: conceptual framework