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

2025-02-05

AI Summary

This study investigates how passenger personality traits moderate visual attention toward pedestrians during interactions with autonomous passenger mobility vehicles (APMVs), and evaluates the impact of external human–machine interface (eHMI) designs. Using eye-tracking, multimodal eHMIs (visual cues combined with neutral or affective speech), and the Big Five Inventory in a controlled experimental paradigm, we collected behavioral and oculomotor data. Results reveal that neuroticism positively moderates dwell time on pedestrian reaction zones under visual-only eHMIs, whereas openness enhances attentional bias toward pedestrian head regions specifically under affective-speech eHMIs. These findings establish personality as a critical moderator of eHMI-induced cognitive processing, challenging the assumption of uniform user responses. We propose a novel “personality-adaptive eHMI” paradigm, offering empirical grounding and methodological frameworks for designing explainable, personalized in-vehicle interfaces. This work advances human-centered automation by integrating individual differences into eHMI evaluation and design.

Technology Category

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

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments

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.

Problem

• Analyzes APMV passengers' gaze behavior with pedestrians
• Examines eHMI design impact on gaze patterns
• Studies influence of personality traits on gaze behavior

Innovation

• Multimodal eHMI integrates visual and voice
• Affective voice alters gaze behavior
• Personality traits influence gaze patterns