eHMI for All -- Investigating the Effect of External Communication of Automated Vehicles on Pedestrians, Manual Drivers, and Cyclists in Virtual Reality

2026-01-27

AI Summary

This study addresses the need for effective communication between autonomous vehicles and road users through external human–machine interfaces (eHMIs), noting that prior research has predominantly focused on pedestrians while neglecting cyclists and manually driven vehicle operators, and has lacked cross-role comparisons. Conducting a within-subjects experiment in a virtual reality environment, this work systematically evaluates the subjective and objective impacts of eHMIs on these three user groups under varying levels of distraction, using both self-report measures and behavioral indicators to assess dimensions such as perceived safety, trust, and mental workload. Results demonstrate that eHMIs significantly enhance feelings of safety, trust, and perceived usefulness while reducing mental workload across all groups. Although main effects of user role and distraction level were observed, an interaction effect emerged only for perceived usability, supporting the generalizability and universal effectiveness of a unified eHMI design and providing empirical evidence for its standardization and broader deployment.

Technology Category

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

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

Abstract

With automated vehicles (AVs), the absence of a human operator could necessitate external Human-Machine Interfaces (eHMIs) to communicate with other road users. Existing research primarily focuses on pedestrian-AV interactions, with limited attention given to other road users, such as cyclists and drivers of manually driven vehicles. So far, no studies have compared the effects of eHMIs across these three road user roles. Therefore, we conducted a within-subjects virtual reality experiment (N=40), evaluating the subjective and objective impact of an eHMI communicating the AV's intention to pedestrians, cyclists, and drivers under various levels of distraction (no distraction, visual noise, interference). eHMIs positively influenced safety perceptions, trust, perceived usefulness, and mental demand across all roles. While distraction and road user roles showed significant main effects, interaction effects were only observed in perceived usability. Thus, a unified eHMI design is effective, facilitating the standardization and broader adoption of eHMIs in diverse traffic.

Problem

• eHMI
• automated vehicles
• pedestrians
• cyclists
• manual drivers

Innovation

• eHMI
• automated vehicles
• virtual reality
• road user comparison
• distraction