Comparing Preferences Between Japan and Germany for External Communication of Automated Vehicles Using Bayesian Optimization

The absence of human users in automated vehicles (AVs) could require external Human-Machine Interfaces (eHMIs) to allow for communication with other vulnerable road users in uncertain scenarios. This could be, for example, regarding the right of way. Given the plethora of adjustable parameters, balancing visual and auditory elements is crucial for effective communication with other road users. With N=40 (n=20 in Germany and n=20 in Japan) participants, this study employed multi-objective Bayesian optimization to evaluate optimized eHMI designs between Japan and Germany. By comparing the Pareto front, we identify optimal design trade-offs and their differences. We also evaluate how the process is perceived between regions.

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Publication Details

Journal
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Published
2026-09-30
DOI
https://doi.org/10.1145/3831988
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Comparing Preferences Between Japan and Germany for External Communication of Automated Vehicles Using Bayesian Optimization

Mark Colley, Xinyue Gui, Pascal Jansen, Enrico Rukzio et al.
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Human-Automation Interaction and Safety
article

Comparing Preferences Between Japan and Germany for External Communication of Automated Vehicles Using Bayesian Optimization

Mark Colley, Xinyue Gui, Pascal Jansen, Enrico Rukzio, Ding Xia, Takeo Igarashi, Yuan Li
article en

Abstract

The absence of human users in automated vehicles (AVs) could require external Human-Machine Interfaces (eHMIs) to allow for communication with other vulnerable road users in uncertain scenarios. This could be, for example, regarding the right of way. Given the plethora of adjustable parameters, balancing visual and auditory elements is crucial for effective communication with other road users. With N=40 (n=20 in Germany and n=20 in Japan) participants, this study employed multi-objective Bayesian optimization to evaluate optimized eHMI designs between Japan and Germany. By comparing the Pareto front, we identify optimal design trade-offs and their differences. We also evaluate how the process is perceived between regions.

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous TechnologiesVol. 10(3)
Universität Ulm (DE), University College London (GB), The University of Tokyo (JP)
Openalex Percentile: Top 7%
Human-Automation Interaction and Safety
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