Design and Development of a Tactile Takeover Warning System Using a Tactile Seat for Automated Driving

Shi, Jinlei; Zhang, Wei; Fan, Hao; Chai, Chunlei · 2025 · Crossref

DOI: 10.54941/ahfe1006531

archive: archived pipeline: cataloged verified

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Summary

This study addresses the critical safety challenge of designing effective takeover request (TOR) systems for conditionally automated vehicles (SAE Level 3). As these systems allow drivers to engage in non-driving-related tasks, a robust mechanism is required to prompt timely control resumption when the vehicle exceeds its operational design domain. The authors argue that tactile modality offers distinct advantages over visual and auditory alerts, as it avoids interference from concurrent visual or auditory tasks and utilizes independent cognitive resources, thereby facilitating more efficient driver response. To leverage these advantages, the researchers designed and developed a seat-based tactile warning system integrating ten vibrotactile motors: six on the seat pan and four on the seat back. The system encodes information through two dimensions: location and timing. Directional cues indicate the required action (steering left/right or braking) by activating motors on the corresponding side of the seat. Urgency is conveyed dynamically through a "looming" effect, where the inter-pulse interval decreases as the time-to-collision (TTC) with a hazard shortens. The relationship between pulse interval and TTC was modeled mathematically to ensure the perceived urgency accurately reflected the proximity to the hazard. The system’s effectiveness was evaluated using a simulated driving experiment with 24 licensed participants. The study employed a within-subjects design comparing the novel tactile system against a baseline condition featuring standard, fixed-interval tactile pulses. Participants performed a Tetris game as a non-driving-related task while the simulator presented takeover events requiring braking or lane changes. The experimental conditions varied by urgency (urgent with TTC = 4 s vs. non-urgent with TTC = 8 s) and weather visibility (sunny, light fog, and heavy fog). Data were analyzed using linear mixed models to assess takeover time. The results demonstrated that the novel tactile takeover warning system significantly reduced driver takeover time compared to the baseline, regardless of event urgency or weather conditions. Specifically, takeover times decreased across all scenarios, with the most pronounced improvements observed in non-urgent situations and heavy fog conditions. For instance, in heavy fog, the mean takeover time dropped from 2.67 seconds in the baseline to 1.85 seconds with the novel system. The authors conclude that the combination of directional guidance and dynamic urgency mapping enhances driver awareness and response efficiency. While the study highlights the system's potential for improving safety in automated driving, it notes that future research should investigate the impact of real-world vehicle vibrations, which may mask tactile cues.

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Topics

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• haptic feedback
• takeover transitions
• automation
• hands on hands off engagement
• automation surprise
• feedback modes

Information type

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• Applied Guidance: design guidelines
• Methodological Resource: measurement protocol
• Theoretical Contribution: conceptual framework