Effectiveness of eHMI for Conveying Autonomous Vehicle Intentions to Multiple Pedestrians

Abstract

In recent years, the development of automated vehicles has progressed, which is expected to reduce human errors that contribute to traffic accidents. However, in automated vehicles without a human driver, pedestrians may face difficulties in decision-making because the vehicle’s driving intentions are unclear. To address this issue, external Human-Machine Interfaces (eHMIs) have been proposed to present the intentions of automated vehicles to pedestrians. Nevertheless, existing eHMIs mainly assume a one-to-one interaction between a single vehicle and a single pedestrian, and they do not adequately consider complex traffic environments in which multiple vehicles and pedestrians coexist. Therefore, this study proposes two eHMI designs: the Aggregated eHMI, which aggregates information from all vehicles and displays a single eHMI for each pedestrian, and the Distributed eHMI, which aggregates information on a per-lane basis and displays lane-specific eHMIs for each pedestrian. These designs aim to improve pedestrian safety and perceived comfort in complex traffic environments. A pedestrian crossing experiment was conducted in a virtual reality (VR) environment with 15 participants, and crossing willingness was evaluated together with a questionnaire survey using a seven-point Likert scale. The results showed that the Distributed eHMI significantly increased crossing willingness during crossing opportunities compared with existing methods, except for the Aggregated eHMI. Furthermore, in the questionnaire evaluation, the Distributed eHMI achieved the highest mean scores across all items, with statistically significant differences compared with other methods for many items. These results confirm that, in complex traffic environments, clearly conveying each vehicle’s intentions toward each pedestrian is important for improving both safety and perceived comfort.