Effect of eHMI-equipped automated vehicles on pedestrian crossing behavior and safety: A focus on blind spot scenarios

Blind spot collisions are a critical and often overlooked threat to pedestrian safety, frequently resulting in severe injuries. This study investigates the impact of automated vehicles equipped with external human–machine interfaces (eHMIs) on pedestrian crossing behavior and safety, focusing on scenarios where AVs create mutual blind spots between pedestrians and adjacent traffic. A virtual reality experiment with 51 participants simulated crossing situations in front of yielding trucks with obstructed pedestrian visibility, featuring three eHMIs: ‘Walk,’ ‘Don’t Walk,’ and ‘Caution! Blind Spots’. Vehicles within the truck’s blind spot exhibited proactive and reactive braking behaviors toward pedestrians. The results indicate that eHMI designs based on color, text, and symbols enhance pedestrian understanding. However, the ‘Walk’ eHMI, which ignores blind spot risks, may lead to dangerous crossing behaviors. In contrast, the ‘Don’t Walk’ eHMI effectively reduced unsafe crossing behaviors, though yielding trucks sometimes caused pedestrian confusion. The ‘Caution! Blind Spots’ eHMI increased alertness but was not significantly more effective than the direct ‘Don’t Walk’ instruction. This study provides empirical evidence for integrating dynamic environmental perception and hazard warnings into eHMI designs to raise road users’ awareness of blind spots. The findings emphasize the importance of comprehensive strategies, including policy-making, education, and VR-based training, to ensure the effective deployment and public understanding of eHMIs in blind spot environments.