A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection

Crosato, L., Wei, C., Ho, E. S. L. , Shum, H. P. H. and Sun, Y. (2024) A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection. In: 19th Annual ACM/IEEE International Conference on Human Robot Interaction (HRI 2024), Boulder, Colorado, USA, 11-15 March 2024, pp. 167-174. ISBN 9798400703225 (doi: 10.1145/3610977.3634923)

Abstract

The advancement of automated driving technology has led to new challenges in the interaction between automated vehicles and human road users. However, there is currently no complete theory that explains how human road users interact with vehicles, and studying them in real-world settings is often unsafe and time-consuming. This study proposes a 3D Virtual Reality (VR) framework for studying how pedestrians interact with human-driven vehicles. The framework uses VR technology to collect data in a safe and cost-effective way, and deep learning methods are used to predict pedestrian trajectories. Specifically, graph neural networks have been used to model pedestrian future trajectories and the probability of crossing the road. The results of this study show that the proposed framework can be for collecting high-quality data on pedestrian-vehicle interactions in a safe and efficient manner. The data can then be used to develop new theories of human-vehicle interaction and aid the Autonomous Vehicles research.

• Item Type: Conference Proceedings
• Additional Information: This project is supported in part by EPSRC (Ref: EP/X031012/1).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ho, Dr Edmond S. L
• Authors: Crosato, L., Wei, C., Ho, E. S. L., Shum, H. P. H., and Sun, Y.
• College/School: College of Science and Engineering > School of Computing Science
• ISBN: 9798400703225
• Published Online: 11 March 2024
• Copyright Holders: © 2024 Copyright held by the owner/author(s)
• First Published: First published in HRI '24: Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction: 167-174
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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