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

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Authors: Ammar Al-Taie, Thomas Goodge, Shaun Macdonald, Ian Oakley, Stephen Anthony Brewster
Cited by: 3
References: 92

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.

Fields of Study & Subjects

Human-Automation Interaction and Safety Autonomous Vehicle Technology and Safety Gaze Tracking and Assistive Technology

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–20
Publication date
13 April 2026
Language
EN