Running into Traffic: Investigating External Human-Machine Interfaces for Automated Vehicle-Runner Interaction
Ammar Al-Taie, Thomas Goodge, Shaun Alexander Macdonald, Ian Oakley, Stephen Anthony Brewster
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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 5201de35-7ea6-44d3-b530-2da119da2c43Builds on16
- An Aligned Rank Transform Procedure for Multifactor Contrast TestsLisa A. Elkin, Matthew Kay, James J. Higgins, Jacob O. WobbrockUIST 2021 · 671 citations
- Color and Animation Preferences for a Light Band eHMI in Interactions Between Automated Vehicles and PedestriansDebargha Dey, Azra Habibovic, Bastian Pfleging, Marieke H. Martens et al.CHI 2020 · 146 citations
- A Taxonomy of Vulnerable Road Users for HCI Based On A Systematic Literature ReviewKai Holländer, Mark Colley, Enrico Rukzio, Andreas ButzCHI 2021 · 99 citations
- Autonomous Vehicle-Cyclist Interaction: Peril and PromiseMing Hou, Karthik Mahadevan, Sowmya Somanath, Ehud Sharlin et al.CHI 2020 · 71 citations
- BikeAR: Understanding Cyclists' Crossing Decision-Making at Uncontrolled Intersections using Augmented RealityAndrii Matviienko, Florian Müller, Dominik Schön, Paul Seesemann et al.CHI 2022 · 61 citations
Related papers
- The Effects of Explicit Intention Communication, Conspicuous Sensors, and Pedestrian Attitude in Interactions with Automated VehiclesSander Ackermans, Debargha Dey, Peter A. M. Ruijten, Raymond H. Cuijpers et al.CHI 2020 · 81 citations
- Multi-Modal eHMIs: The Relative Impact of Light and Sound in AV-Pedestrian InteractionDebargha Dey, Toros Ufuk Senan, Bart Hengeveld, Mark Colley et al.CHI 2024 · 21 citations
- Light it Up: Evaluating Versatile Autonomous Vehicle-Cyclist External Human-Machine InterfacesAmmar Al-Taie, Graham A. Wilson, Euan Freeman, Frank E. Pollick et al.CHI 2024 · 16 citations
- Evaluating Autonomous Vehicle External Communication Using a Multi-Pedestrian VR SimulatorTram Thi Minh Tran, Callum Parker, Xinyan Yu, Debargha Dey et al.UbiComp 2024 · 22 citations
- "It Must Be Gesturing Towards Me": Gesture-Based Interaction between Autonomous Vehicles and PedestriansXiang Chang, Zihe Chen, Xiaoyan Dong, Yuxin Cai et al.CHI 2024 · 14 citations
