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

arXiv: https://arxiv.org/abs/2310.05882 · HTML: https://mlsanity.com/paper/2310.05882/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Oct 2023.

## Built on by (most cited first, 1 of 1)

- [Trajectory Prediction for Autonomous Driving in Road Construction Zones Using Human-in-the-Loop Driving Data](https://mlsanity.com/paper/2610.12747/) (2026)

## Abstract (arXiv)

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.