AI RESEARCH
Eye Gaze-Informed and Context-Aware Pedestrian Trajectory Prediction in Shared Spaces with Automated Shuttles: A Virtual Reality Study
arXiv CS.LG
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ArXi:2603.19812v1 Announce Type: new The integration of Automated Shuttles into shared urban spaces presents unique challenges due to the absence of traffic rules and the complex pedestrian interactions. Accurately anticipating pedestrian behavior in such unstructured environments is therefore critical for ensuring both safety and efficiency. This paper presents a Virtual Reality (VR) study that captures how pedestrians interact with automated shuttles across diverse scenarios, including varying approach angles and navigating in continuous traffic.