Investigating HMIs to Foster Communications between Conventional Vehicles and Autonomous Vehicles in Intersections

Avetisyan, Lilit; Deshmukh, Aditya; Yang, X. Jessie; Zhou, Feng · 2023 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2305.17769

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Summary

This study investigates how human-machine interfaces (HMIs) can facilitate communication between autonomous vehicles (AVs) and conventional vehicles (CVs) at intersections, a critical gap in mixed-traffic safety research. While prior work focused on AV interactions with vulnerable road users, this paper addresses the lack of explicit communication strategies between AVs and human-driven CVs, where traditional cues like gestures are ineffective. The research aims to determine how different HMI designs impact CV drivers’ situation awareness (SA), trust, acceptance, and mental workload. The methodology involved a two-phase approach. First, a human-centered design process generated eight HMI concepts, which were evaluated by 32 participants; the top-rated concept was selected for implementation. Second, a within-subjects experiment was conducted with 44 participants using a virtual reality (VR) driving simulator. The experiment featured three conditions: a control condition with no communication, an external HMI (eHMI) displayed on the front of the AV, and an internal HMI (iHMI) projected onto the CV’s windshield. Participants navigated two intersection scenarios involving malfunctioning traffic lights, where the AV either yielded or insisted on the right of way. Data collection included self-reported measures for SA (using the SAGAT technique), trust, and acceptance, alongside eye-tracking data to assess mental workload via pupil diameter and eye openness changes. Results indicated that the iHMI condition produced superior situation awareness compared to both the control and eHMI conditions. Additionally, the iHMI led to higher levels of trust in the AV and a comparatively lower increase in mental workload than the other conditions. The eHMI condition showed intermediate performance, while the control condition resulted in the lowest SA and highest workload. The study found that explicitly sharing traffic situation and right-of-way information through the iHMI was more effective for driver comprehension and decision-making than external displays or no communication. The significance of this work lies in its contribution to the design of effective AV-to-CV communication systems. By demonstrating that internal displays on the CV’s windshield outperform external AV displays in complex intersection scenarios, the findings suggest that future AV systems should prioritize interfaces that directly integrate with the driver’s cockpit to enhance safety and efficiency in mixed-traffic environments. This research provides empirical evidence for prioritizing internal HMIs to mitigate the risks associated with ambiguous traffic situations where traditional communication methods fail.

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Topics

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• ehmi external hmi
• automation
• vru facing ehmi
• situational awareness

Information type

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• Applied Guidance: design guidelines