The Interaction Effects of Autonomous Vehicle Deceleration Style and eHMI Presence on Pedestrian Crossing Intentions

Communicating through external human-machine interfaces (eHMIs) is considered a potential solution to address the communication gaps and safety issues introduced by automated driving. This study investigates the impact of eHMI on pedestrian willingness to cross during the brief yet crucial 'deceleration-yield' process. Twenty-three participants experienced three different vehicle deceleration styles and two eHMI display conditions, including text-based eHMI and a baseline condition with no eHMI, through simulated videos portraying pedestrian scenarios. Participants continuously reported their real-time willingness to cross using an upward or downward swipe on a tablet and provided subjective assessments of anxiety and perceived risks through a questionnaire after each deceleration experience. The research findings indicate that a more aggressive deceleration approach decreases pedestrian willingness to cross, but the presence of eHMI can mitigate this effect. For pedestrians, the impact of eHMI is more pronounced when the vehicle's behavior exhibits its intent ambiguity. This study provides insights into scenarios where eHMI can be beneficial and offers design recommendations for eHMI implementation in real-world autonomous driving scenarios.