Using distributed simulations to investigate driver-pedestrian interactions and kinematic cues: Implications for automated vehicle behaviour and communication

Yang, Yue; Lee, Yee Mun; Kalantari, Amir Hossein; de Pedro, Jorge Garcia; Horrobin, Anthony; Daly, Michael; Solernou, Albert; Holmes, Christopher; Markkula, Gustav; Merat, Natasha · 2024 · OpenAlex-citations

DOI: 10.1016/j.trf.2024.08.027

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Summary

This study investigates driver-pedestrian interactions to inform the design of human-like behaviors for Automated Vehicles (AVs). Previous research relied on naturalistic observations or single-actor simulations, which failed to capture causal relationships in real-time, reciprocal interactions. To address this, the authors employed a high-fidelity distributed simulation linking drivers in a motion-based simulator with pedestrians in a CAVE-based environment. The research aimed to determine how infrastructural elements (zebra crossings) and kinematic cues (time gaps) influence driver behavior, and how driver kinematics (deceleration, lateral deviation) subsequently affect pedestrian crossing decisions. The experiment involved 32 pairs of participants (drivers and pedestrians) interacting in real-time across 40 trials per pair. Scenarios varied by the presence of zebra crossings and vehicle approach time gaps (3–7 seconds). Data were analyzed using generalized linear mixed-effects models to assess driver deceleration, braking proximity, and lateral deviation, as well as pedestrian crossing outcomes. Results indicated that driver deceleration exhibited a bimodal distribution: drivers either markedly yielded or continued their path, with few intermediate behaviors. Zebra crossings significantly increased driver deceleration and reduced the distance to pedestrians at peak braking. Crucially, pedestrian crossing decisions were strongly influenced by driver kinematic cues rather than infrastructure alone. Pedestrians were more likely to cross when drivers employed either "soft and early" braking (low deceleration at a greater distance) or "late and hard" braking (high deceleration at close proximity). Conversely, "late and soft" braking often resulted in the vehicle passing first. Additionally, lateral deviation served as an implicit cue; drivers deviated away from pedestrians when not yielding, but deviated toward them when yielding, suggesting a transfer of walking interaction habits to driving. These kinematic cues exerted a stronger influence on pedestrian decisions than the presence of zebra crossings. The findings highlight the critical role of implicit kinematic communication in vehicle-pedestrian interactions. For AV development, these results suggest that algorithms should incorporate human-like braking strategies and lateral movements to facilitate intuitive interactions. Specifically, AVs must avoid ambiguous "late and soft" braking behaviors that confuse pedestrians. Instead, adopting clear yielding or non-yielding kinematic patterns can enhance safety and traffic flow by aligning AV behavior with established human social norms and expectations.

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Topics

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• driver vru interaction
• pedestrian behavior perception
• ehmi external hmi
• braking response
• vru facing ehmi

Information type

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• Empirical Findings: behavioral performance data
• Methodological Resource: tool software
• Theoretical Contribution: computational model