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

TL;DR

This paper assesses a VR system for collecting realistic pedestrian data in safety-critical vehicle interactions, addressing data scarcity for autonomous vehicle safety testing through empirical validation and professional feedback.

Contribution

It introduces and validates a VR-based data collection method for safety-critical pedestrian scenarios, filling a gap in autonomous vehicle safety research.

Findings

VR system elicits realistic pedestrian responses

Effective for safety-critical and uncommon scenarios

Validated through user studies and professional feedback

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.