Neuroergonomic evaluation of risk-warning eHMI penetration rates in vehicle platoons: effects on pedestrians' mental workload, situation awareness, and gap acceptance.

Yang, F; Sun, X; Ma, J; Zhou, S; Liu, B; Li, P; Lyu, W; Wen, S · 2026 · PubMed Central

DOI: 10.1038/s41598-026-42814-3

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Summary

This study investigates the cognitive and behavioral impacts of external human–machine interfaces (eHMIs) on pedestrians interacting with autonomous vehicle (AV) platoons. As Level 4–5 AVs lack human drivers, they cannot provide social cues for crossing negotiations, leading to pedestrian confusion. Risk-warning eHMIs, which display dynamic risk levels based on time-to-arrival, offer a solution but may increase mental workload (MW). The research specifically addresses how varying eHMI penetration rates—zero (no eHMIs), partial (mixed AVs with eHMIs and traditional vehicles), and full (all vehicles with eHMIs)—affect pedestrians’ MW, situation awareness (SA), and gap acceptance decisions. The researchers conducted a video-based experiment with 24 participants who simulated street-crossing decisions in a Unity-generated environment. Participants observed vehicle platoons with randomized speeds (30 or 36 km/h) and temporal gaps (2–6 seconds). To objectively measure MW, the study employed electroencephalography (EEG) to record P300 event-related potentials during a concurrent auditory oddball task, where P300 amplitude served as an indicator of residual attentional capacity. SA was assessed using the Situation Awareness Rating Technique (SART), and behavioral data were collected via gap acceptance choices. The experimental design included three within-subject conditions: zero penetration (all traditional vehicles), full penetration (all AVs with eHMIs), and partial penetration (half AVs with eHMIs, half traditional vehicles). Results indicated that full eHMI penetration significantly improved pedestrians’ situation awareness and reduced mental workload compared to the partial penetration condition. Furthermore, full penetration enhanced pedestrians’ sensitivity to gap sizes, causing crossing probabilities to increase more sharply as gaps widened, without negatively impacting MW or SA. In contrast, the partial penetration condition resulted in significantly higher mental workload and lower situation awareness. Pedestrians in the partial condition also crossed less frequently when encountering vehicles equipped with eHMIs, suggesting that inconsistent signaling creates cognitive interference. The findings demonstrate that while risk-warning eHMIs effectively support pedestrian-AV interactions under full deployment, partial penetration during transitional phases may impair decision-making and cognitive performance. The study highlights the critical importance of strategic planning for eHMI adoption to avoid the cognitive costs associated with mixed-traffic environments. These results inform the design of safer, cognitively efficient AV-pedestrian interaction strategies, emphasizing that uniform eHMI deployment is necessary to maximize safety and minimize mental overload.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

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• vru facing ehmi
• ehmi external hmi
• pedestrian behavior perception
• situational awareness

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• Empirical Findings: self report data
• Theoretical Contribution: theory or model