In this work, we investigate the influence that audio and visual feedback have on a manipulation task in virtual reality (VR). Without the tactile feedback of a controller, grasping virtual objects using one’s hands can result in slower interactions because it may be unclear to the user that a grasp has occurred. Providing alternative feedback, such as visual or audio cues, may lead to faster and more precise interactions, but might also affect user preference and perceived ownership of the virtual hands. In this study, we test four feedback conditions for virtual grasping. Three of the conditions provide feedback formore »
Autonomous Vehicle Visual Embodiment for Pedestrian Interactions in Crossing Scenarios: Virtual Drivers in AVs for Pedestrian Crossing
This work presents a novel prototype autonomous vehicle (AV) human-machine interface (HMI) in virtual reality (VR) that utilizes a human-like visual embodiment in the driver’s seat of an AV to communicate AV intent to pedestrians in a crosswalk scenario. There is currently a gap in understanding the use of virtual humans in AV HMIs for pedestrian crossing despite the demonstrated efcacy of human-like interfaces in improving human-machine relationships. We conduct a 3x2 within-subjects experiment in VR using our prototype to assess the efects of a virtual human visual embodiment AV HMI on pedestrian crossing behavior and experience. In the experiment participants walk across a virtual crosswalk in front of an AV. How long they took to decide to cross and how long it took for them to reach the other side were collected, in addition to their subjective preferences and feelings of safety. Of 26 participants, 25 preferred the condition with the most anthropomorphic features. An intermediate condition where a human-like virtual driver was present but did not exhibit any behaviors was least preferred and also had a signifcant efect on time to decide. This work contributes the frst empirical work on using human-like visual embodiments for AV HMIs.
- Award ID(s):
- 1800961
- Publication Date:
- NSF-PAR ID:
- 10275677
- Journal Name:
- Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
- Page Range or eLocation-ID:
- 1 to 7
- Sponsoring Org:
- National Science Foundation
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