Effects of External Environmental Factors on Pedestrian Crossing Behavior in Shared Spaces with Automated Vehicles: A Virtual Reality Study

The integration of automated vehicles (AVs) into urban shared spaces requires an in-depth understanding of pedestrian crossing behavior, especially due to the absence of traditional communication cues from human drivers. This study investigates how multiple external environmental factors—including lane width, surface condition, visual load, time of day, traffic markings, and traffic conditions—influence pedestrians' crossing decisions and perceptions in front of AVs using immersive virtual reality (VR). Sixty participants engaged in controlled VR experiments featuring realistic shared-space scenarios. Pedestrian crossing behaviors were objectively analyzed through crossing initial time, crossing duration, and safety margins, while subjective perceptions of safety, comfort, legibility, and trust were also collected. Linear Mixed Models (LMM) and Generalized Linear Mixed Models (GLMM) were employed to analyze the data. Results indicated significant influences of traffic markings and traffic conditions on both pedestrian behavior and subjective perceptions. Lane width, surface conditions, and visual complexity were also significant in affecting crossing duration and safety margins. This research provides comprehensive insights into pedestrian-AV interactions, informing safer shared-space designs and AV communication strategies.