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

TL;DR

The study investigates whether a single, external HMI (eHMI) can effectively communicate an AV's yielding intent to pedestrians, cyclists, and manual drivers using a VR-based within-subject design (N=$40$, 18 conditions). Results show that eHMIs improve perceived safety, trust, usefulness, and reduce mental demand across all road-user roles, with notable gains in usability and few cross-role interaction effects. The findings support a holistic, standardized eHMI design that can streamline development and adoption in mixed traffic, though challenges remain for multi-user interactions and cross-cultural generalizability. Open data and evaluation scripts enhance transparency and enable broader replication and validation across contexts.

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.

Figures (16)

• Figure 1: The three points of view for the pedestrian, driver, and cyclist scenarios.
• Figure 2: The three simulator setups for the project are a pedestrian, a driver, and a cyclist. All setups are connected to the same computer and done with the same VR headset.
• Figure 3: The white AV with the implemented intention-based SPLB. It blinks when it fully stops. A light band on the AV's side and rear supports omnidirectional communication. The light signal on the windshield around the rearview mirror indicates that it is an AV.
• Figure 4: Noise scenario for the role of pedestrian. The yellow diamond-shaped rectangles indicate pedestrians standing at the street, adding visual noise, although not directly interfering with the participant's trajectory.
• Figure 5: Interference scenario for the role of pedestrian. The yellow diamond-shaped rectangle indicates a cyclist crossing in front of the participant, directly interfering with their intended trajectory.