Where Do Passengers Gaze? Impact of Passengers' Personality Traits on Their Gaze Pattern Toward Pedestrians During APMV-Pedestrian Interactions with Diverse eHMIs

TL;DR

This study investigates how passengers' personality traits influence their gaze behavior toward pedestrians during APMV interactions with various eHMI designs, revealing implications for personalized interface development.

Contribution

It provides new insights into the impact of eHMI modalities and passenger personality traits on gaze patterns during autonomous vehicle-pedestrian interactions.

Findings

Visual eHMI challenges perception for passengers.

High Neuroticism passengers seek pedestrian cues.

Affective voice eHMI influences Openness-related gaze behavior.

Abstract

Autonomous Personal Mobility Vehicles (APMVs) are designed to address the ``last-mile'' transportation challenge for everyone. When an APMV encounters a pedestrian, it uses an external Human-Machine Interface (eHMI) to negotiate road rights. Through this interaction, passengers also engage with the process. This study examines passengers' gaze behavior toward pedestrians during such interactions, focusing on whether different eHMI designs influence gaze patterns based on passengers' personality traits. The results indicated that when using a visual-based eHMI, passengers often struggled to perceive the communication content. Consequently, passengers with higher Neuroticism scores, who were more sensitive to communication details, might seek cues from pedestrians' reactions. In addition, a multimodal eHMI (visual and voice) using neutral voice did not significantly affect the gaze behavior of passengers toward pedestrians, regardless of personality traits. In contrast, a multimodal eHMI using affective voice encouraged passengers with high Openness to Experience scores to focus on pedestrians' heads. In summary, this study revealed how different eHMI designs influence passengers' gaze behavior and highlighted the effects of personality traits on their gaze patterns toward pedestrians, providing new insights for personalized eHMI designs.