Running into Traffic: Investigating External Human-Machine Interfaces for Automated Vehicle-Runner Interaction

2026-03-13

AI Summary

This study addresses the critical need for autonomous vehicles to effectively communicate yielding intentions to pedestrians, noting that existing external human–machine interfaces (eHMIs) are predominantly designed for walkers and overlook the perceptual and behavioral differences of runners. Through an outdoor augmented reality simulation experiment, this work presents the first systematic comparison of how runners and walkers respond to and rely on three eHMI conditions: colored lights, animated lights, and no eHMI. Results demonstrate that the absence of an eHMI yields the poorest performance; runners, under greater time pressure, exhibit stronger reliance on eHMIs and a significant preference for color-based signals, whereas walkers integrate vehicle dynamics to verify eHMI cues. These findings underscore the pivotal role of user motion state in shaping eHMI effectiveness and interaction strategies, offering empirical foundations for inclusive autonomous vehicle interaction design.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Intelligent Robots: Human-Robot Interaction
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Automated vehicles (AVs) must communicate their yielding intentions to pedestrians at crossings. External Human-Machine Interfaces (eHMIs, on-vehicle displays) are promising solutions, but were primarily tested with walking pedestrians. Runners are a significant pedestrian group who move faster and face distinct bodily and perceptual demands, raising questions about how pedestrian activity influences eHMI use. We conducted an outdoor study using an augmented reality simulator. Participants navigated a virtual crossing while walking and running; an approaching AV displayed one of three eHMIs: red/green colour-changing lights, animated cyan lights, or no-eHMI. No-eHMI consistently underperformed. Walkers mostly stopped and validated eHMI signals with vehicle behaviour; they processed both eHMI animations and colour changes effectively. Runners experienced greater time pressure to cross, increasing reliance on the eHMI over vehicle behaviour. They preferred colour changes over animation for rapid decisions. These findings are crucial for promoting eHMI inclusivity and physical wellbeing as AVs join our roads.

Problem

• automated vehicles
• external human-machine interfaces
• pedestrian interaction
• runners
• crossing behavior

Innovation

• external Human-Machine Interface
• automated vehicles
• pedestrian-runner interaction
• augmented reality simulation
• eHMI design