arXiv:2603.19812v2 Announce Type: replace Abstract: To address this gap, we conduct a Virtual Reality experiment in which pedestrians interact with automated shuttles under varying approach angles (45{\deg}, 90{\deg}, 135{\deg}) and continuous-traffic conditions (single shuttle, two shuttles with 3 or 5-second gaps), collecting synchronized motion, eye gaze, and head orientation data. To investigate to what extent, under what conditions, and in what form fine-grained eye gaze is informative for pedestrian motion prediction, we develop a multi-modal prediction model that fuses these signals thr
Source: arXiv cs.LG — read the full report at the original publisher.