Hands Up! Investigating Intrinsic Gestures of Persons with Intellectual Disabilities for Inclusive Automated Traffic

As traffic automation grows, research into communication between automated vehicles (AVs) and pedestrians is increasing. Since communication is particularly challenging for persons with intellectual disability (PID), we investigated which gestures are used during street crossings and whether they differ between PID and persons with no diagnosed disability (PnDD). We conducted a virtual reality study with N=70 participants (n=38 PID, n=32 PnDD), observing participants’ movement and gestures in a road-crossing scenario and having them rate their presence, user experience, and the AV’s behavior. PID descriptively gestured less often than PnDD (33.3% vs. 18.8% of trials without a gesture), though this difference was not statistically significant. The increased learning effect of using gestures improves crossing time for PID. We identified three primary gestures (Greet, Barrier, Stop) that both groups equally favored. Our work contributes to making bidirectional communication with AVs more inclusive by providing insights into gestures used by PnDD and PID and identifying indicators of subconscious learning effects when using gestures.