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Simulators are an essential tool for behavioural and interaction research on driving, due to the safety, cost, and experimental control issues of on-road driving experiments. The most advanced simulators use expensive 360 degree projections systems to ensure visual fidelity, full field of view, and immersion. However, similar visual fidelity can be achieved affordably using a virtual reality (VR) based visual interface. We present DReyeVR, an open-source VR based driving simulator platform designed with behavioural and interaction research priorities in mind. DReyeVR (read ''driver'') is based on Unreal Engine and the CARLA autonomous vehicle simulator and has features such as eye tracking, a functional driving heads-up display (HUD) and vehicle audio, custom definable routes and traffic scenarios, experimental logging, replay capabilities, and compatibility with ROS. We describe the hardware required to deploy this simulator for under 5000 USD, much cheaper than commercially available simulators. Finally, we describe how DReyeVR may be leveraged to answer an interaction research question in an example scenario. DReyeVR is open-source at this url: https://github.com/HARPLab/DReyeVR
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GrokWalks: A Portable Virtual Reality Platform to Facilitate Studying Driver-Pedestrian Interactions
Driving simulators are vital for human-centered automotive research, offering safe, replicable environments for studying human interaction with transportation technology interfaces and behaviors. However, traditional driving simulators are not well-suited to studying traffic interactions with various degrees of freedom in a way that allows for the capture of nuances in implicit and explicit interactions, e.g. gestures, body language, and movement. We developed a multi-participant virtual reality (VR) driving simulation platform to study these interactions. This portable system supports cross-cultural experiments by modeling diverse scenarios, generating analyzable data, and capturing human behaviors in traffic. Our interactive demo allows participants to experience roles as drivers or pedestrians in a shared virtual environment, with the goal of providing a hands-on experience with this open-source VR simulator and demonstrating its affordability and scalability for traffic interaction studies to researchers and practitioners.
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- Award ID(s):
- 2212431
- PAR ID:
- 10656928
- Publisher / Repository:
- ACM
- Date Published:
- Page Range / eLocation ID:
- 284 to 288
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3641308.3685013
