Evaluating a VR System for Collecting Safety-Critical Vehicle-Pedestrian Interactions

Erica Weng, Kenta Mukoya, Deva Ramanan, Kris M. Kitani

Keywords: Virtual reality, trajectory forecasting, user study

TL;DR: This paper evaluates the effectiveness of a VR system for collecting realistic pedestrian trajectory and body pose data in safety-critical scenarios, demonstrating its usefulness and validity through professional interviews and empirical studies.

Abstract: Autonomous vehicles (AVs) require comprehensive and reliable pedestrian trajectory data to ensure safe operation. However, obtaining data of safety-critical scenarios such as jaywalking and near-collisions, or uncommon agents such as children, disabled pedestrians, and vulnerable road users poses logistical and ethical challenges. This paper evaluates a Virtual Reality (VR) system designed to collect pedestrian trajectory and body pose data in a controlled, low-risk environment. We substantiate the usefulness of such a system through semi-structured interviews with professionals in the AV field, and validate the effectiveness of the system through two empirical studies: a first-person user evaluation involving 62 participants, and a third-person evaluative survey involving 290 respondents. Our findings demonstrate that the VR-based data collection system elicits realistic responses for capturing pedestrian data in safety-critical or uncommon vehicle-pedestrian interaction scenarios.

Submission Number: 13