Attitudes of Person at Driver’s Seat of Level 3–4 Automated Vehicle Affect Human Driver Entering Roadway

Saeki, Hidehiro; Shidoji, Kazunori · 2025 · Crossref

DOI: 10.1007/s13177-024-00459-4

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Summary

This study investigates how the attitudes of a person seated in the driver’s seat of a Level 3–4 automated vehicle affect the driving maneuvers and psychological perceptions of a human driver attempting to merge onto a mainline. As automated vehicles cannot rely on conventional communication methods like eye contact or gestures, the authors explore the necessity of external human-machine interfaces (eHMI) to convey intent. The research specifically examines whether the posture of the occupant in an automated vehicle influences a manual driver’s hesitation and subjective evaluation of merging smoothness. The experiment utilized a driving simulator with 19 participants holding valid driver’s licenses. Participants drove a vehicle exiting an off-road facility and merging onto a mainline where an automated vehicle was present. The study employed a within-subjects design with two scene factors: the mainline vehicle either stopped completely or decelerated to yield. Three attitude factors for the occupant of the mainline vehicle were tested: "eye gaze" (looking at the participant), "hand sign" (explicit yielding gesture), and "smartphone gaze" (looking down at a phone, indicating disengagement). Data collected included the time to release brakes, the time until the participant’s vehicle entered the mainline, and subjective ratings of merging smoothness using a Visual Analog Scale. Results indicated that the attitude of the occupant significantly affected the time required to merge and subjective smoothness ratings. The "hand sign" condition resulted in the shortest time to enter the mainline and the highest subjective smoothness scores, as it provided a clear, unambiguous signal of intent to yield. Conversely, the "smartphone gaze" condition yielded the lowest smoothness ratings and increased hesitation, as participants perceived the occupant as unaware of their presence, forcing them to rely solely on vehicle behavior rather than interpersonal communication. Interestingly, the "eye gaze" condition, while not the fastest, was rated higher in smoothness than the smartphone condition but lower than the hand sign. The scene factor also influenced behavior; participants reacted faster when the mainline vehicle was already stopped compared to when it was decelerating, likely due to reduced uncertainty about the vehicle's immediate motion. The findings suggest that in mixed traffic environments, manual drivers heavily rely on the visible attitudes of occupants in other vehicles to infer driving intent. When an occupant appears disengaged (e.g., using a smartphone), it creates ambiguity that hinders smooth traffic flow, even if the automated vehicle is yielding. The authors conclude that specific and clear eHMI presentations are necessary to explicitly communicate the vehicle’s automated status and its intention to yield, thereby compensating for the lack of traditional human-to-human communication cues. This research highlights the importance of designing eHMI systems that address both the operational and psychological aspects of driver interaction to ensure safety and comfort in automated driving scenarios.

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Topics

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• ehmi external hmi
• automation
• situational awareness
• automation surprise
• acceptance adoption
• driver vru interaction

Information type

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• Empirical Findings: behavioral performance data
• Theoretical Contribution: conceptual framework, theory or model