Is Users’ Trust during Automated Driving Different When Using an Ambient Light HMI, Compared to an Auditory HMI?

Gonçalves, Rafael Cirino; Louw, Tyron; Lee, Yee Mun; Madigan, Ruth; Kuo, Jonny; Lenné, Mike; Merat, Natasha · 2023 · Crossref

DOI: 10.3390/info14050260

archive: archived pipeline: cataloged verified

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Summary

This study investigates whether ambient light-based Human-Machine Interfaces (HMIs) differ from traditional auditory HMIs in influencing driver trust, perceived safety, and takeover performance during SAE Level 3 automated driving. The research addresses a critical human factors challenge: ensuring drivers engaged in Non-Driving-Related Tasks (NDRTs) can safely and timely resume control when requested. While auditory alerts are common, they may be masked by noise or difficult to interpret, whereas dashboard visual cues may be missed if drivers are not looking forward. The authors hypothesized that peripheral ambient light displays could effectively capture attention and maintain trust without disrupting NDRT engagement. The experiment utilized a fully motion-based driving simulator with 41 participants. Drivers completed two experimental drives on a UK motorway, engaging in a visual "Arrows" NDRT during automated segments. The study employed a within-participant design comparing two HMI conditions for Takeover Requests (TORs): a flashing Light-band display and an auditory warning (880 Hz, 0.2 s). Each drive included five non-safety-critical takeover scenarios, comprising one hard cut-in event (deceleration of 2.4 m/s²) and four subtle cut-in events (~1.16 m/s²). Eye-tracking data recorded gaze behavior, while subjective measures assessed trust and perceived safety. Results indicated that drivers’ trust in automation and perceived safety were similar across both HMI conditions in most scenarios, with the exception of the hard cut-in event, where differences emerged. There were no significant differences in overall takeover performance or general gaze distribution between the Light-band and Auditory conditions. However, gaze analysis revealed that drivers using the Light-band HMI were more likely to direct their initial attention to the center of the road after a takeover request, compared to those using the auditory alert. Although both conditions elicited frequent glances toward the dashboard, the ambient light signal appeared more effective at guiding visual attention toward the forward roadway, which is critical for safe re-entry into the driving loop. The findings suggest that ambient light HMIs offer a viable alternative to auditory alerts for facilitating transitions of control in Level 3 automated vehicles. By leveraging peripheral vision, these displays can help redirect driver attention to the road environment without requiring constant monitoring of the dashboard. This supports the design principle of keeping drivers in the loop while allowing engagement in NDRTs. The study implies that integrating ambient lighting into vehicle interiors can enhance the safety and efficiency of takeover processes, particularly by optimizing the initial visual search pattern after a request to intervene.

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Topics

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• automation
• ehmi external hmi
• trust calibration
• automation surprise
• mode awareness
• vru facing ehmi

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• Applied Guidance: design guidelines
• Empirical Findings: self report data
• Theoretical Contribution: conceptual framework