Using a Configurational Approach to Examine the Impacts of Vehicle Appearance Perception on Pedestrian Acceptance of the External Human-Machine Interfaces on Autonomous Vehicles

The interaction between autonomous vehicles (AVs) and pedestrians has gained significant attention, leading to the exploration of external human-machine interfaces (eHMIs) equipped on AVs to facilitate effective communication. While existing research suggests that perceptions of vehicle appearances may influence interactions between pedestrians and AVs, a comprehensive study on the eHMIs related to AV appearance remains lacking. Therefore, we conducted a virtual reality (VR) experiment to investigate how AV appearances affect pedestrians' acceptance regarding Awareness, Intent, and Harmony during interactions with various eHMIs. Leveraging the fuzzy set qualitative comparative analysis (fsQCA) method, we identified specific combinations of AV appearances and eHMIs that yield either high or low-performance interactions. For example, our findings reveal that text displays exhibit high performance in terms of awareness on AVs that are aggressive and ordinary. Furthermore, we distilled design guidelines to provide actionable suggestions for the design of eHMIs, fostering the acceptance of AVs among pedestrians.