Virtual Reality Study on Pedestrians’ Perceived Trust in Interactions with Automated Vehicles

This paper investigates the impact of different automated vehicle (AV) communication concepts on pedestrians' perceived trust when interacting with the AV in an urban intersection setting. For this, two virtual reality (VR) studies were conducted. The first examined the influence of vehicle automation on how pedestrians interpret driving behavior, while the second analyzed the effects of explicit communication concepts on pedestrians' perceived trust. The results show that AV driving behavior evokes similar associations as manually driven vehicles, with overall perceived trust scores not differing considerably (with driver: 4.7, without driver: 4.6). However, qualitative interviews revealed that pedestrians ultimately interpret AV behavior differently, yielding insights into the applicability of driving behavior of manually driven vehicles as a model for AV driving behavior. The second study showed an increase in pedestrians' perceived trust when vehicle-based explicit communication was present (mean: 4.9). In contrast, infrastructure-based communication showed no difference compared to implicit communication (mean: 4.6). The investigation of the influence of the traffic infrastructure (presence of traffic lights) has shown different results for implicit and explicit communication of AVs. For implicit communication, pedestrians' perceived trust increased with traffic lights (mean: 4.8) compared to scenarios without them (mean: 4.4). However, for explicit communication, the perceived trust decreased with traffic lights (vehicle-based: 4.7, infrastructure-based: 4.6) compared to scenarios without traffic lights (mean: 5.1). One reason for this is possible cognitive overload caused by the perception of multiple visual aids that are not always in the same field of view.