Communicating the intention of an automated vehicle to pedestrians: The contributions of eHMI and vehicle behavior

Debargha Dey · Andrii Matviienko · Melanie Berger · Bastian Pfleging · Marieke Martens · Jacques M. B. Terken

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Human-Automation Interaction and Safety Traffic and Road Safety Social Robot Interaction and HRI

Abstract

Abstract External Human-Machine Interfaces (eHMIs) are expected to bridge the communication gap between an automated vehicle (AV) and pedestrians to replace the missing driver-pedestrian interaction. However, the relative impact of movement-based implicit communication and explicit communication with the aid of eHMIs on pedestrians has not been studied and empirically evaluated. In this study, we pit messages from an eHMI against different driving behaviors of an AV that yields to a pedestrian to understand whether pedestrians tend to pay more attention to the motion dynamics of the car or the eHMI in making road-crossing decisions. Our contributions are twofold: we investigate (1) whether the presence of eHMIs has any objective effect on pedestrians’ understanding of the vehicle’s intent, and (2) how the movement dynamics of the vehicle affect the perception of the vehicle intent and interact with the impact of an eHMI. Results show that (1) eHMIs help in convincing pedestrians of the vehicle’s yielding intention, particularly when the speed of the vehicle is slow enough to not be an obvious threat, but still fast enough to raise a doubt about a vehicle’s stopping intention, and (2) pedestrians do not blindly trust the eHMI: when the eHMI message and the vehicle’s movement pattern contradict, pedestrians fall back to movement-based cues. Our results imply that when explicit communication (eHMI) and implicit communication (motion-dynamics and kinematics) are in alignment and work in tandem, communication of the AV’s yielding intention can be facilitated most effectively. This insight can be useful in designing the optimal interaction between AVs and pedestrians from a user-centered design perspective when driver-centric communication is not available.

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References

2019External Human-Machine Interfaces on Automated Vehicles: Effects on Pedestrian Crossing Decisions 2020Taming the eHMI jungle: A classification taxonomy to guide, compare, and assess the design principles of automated vehicles' external human-machine interfaces 2016Ghost driver: A field study investigating the interaction between pedestrians and driverless vehicles 2018Communicating Intent of Automated Vehicles to Pedestrians 2017Evaluation of Vehicle-to-Pedestrian Communication Displays for Autonomous Vehicles 2019The Case for Implicit External Human-Machine Interfaces for Autonomous Vehicles 2019How Should Automated Vehicles Interact with Pedestrians?

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2021ExplAIn Yourself! Transparency for Positive UX in Autonomous Driving 2022External human–machine interfaces: Gimmick or necessity?2023Deceleration parameters as implicit communication signals for pedestrians’ crossing decisions and estimations of automated vehicle behaviour 2023External Human–Machine Interfaces for Automated Vehicles in Shared Spaces: A Review of the Human–Computer Interaction Literature 2021Towards Scalable eHMIs: Designing for AV-VRU Communication Beyond One Pedestrian

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