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Westdrive X LoopAR: An Open-Access Virtual Reality Project in Unity for Evaluating User Interaction Methods during

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  • 1Institute of Cognitive Science, University of Osnabrück, 49090 Osnabrück, Germany.

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Summary
This summary is machine-generated.

Researchers developed a cost-efficient virtual reality toolkit for studying how distracted drivers safely retake control of automated vehicles. This toolkit enables realistic human-machine interaction experiments without expensive simulators.

Keywords:
VR researchhuman–machine interactionout-of-the-loop unfamiliarity (OOTLU) autonomous drivingtakeover request (ToR)

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Area of Science:

  • Human-Computer Interaction
  • Automotive Engineering
  • Virtual Reality

Background:

  • Highly automated vehicles require drivers to retake control during critical situations.
  • Investigating driver distraction and safe takeover is crucial for autonomous driving safety.
  • Existing research setups are often costly and immobile.

Purpose of the Study:

  • To present a versatile, cost-efficient virtual reality (VR) toolkit for human-machine interaction (HMI) research in automated driving.
  • To enable rapid adaptation for experiments on driver distraction and takeover.
  • To facilitate realistic VR studies without expensive, fixed simulators.

Main Methods:

  • Development of a VR toolkit using the Unity 3D game engine.
  • Integration of realistic traffic simulation (vehicles, pedestrians, environment).
  • Inclusion of eye-tracking and force feedback steering wheel support.

Main Results:

  • A comprehensive, open-source VR toolkit with a large, dynamic, and realistic environment (25 km²).
  • Functionalities for realistic traffic behavior, animated pedestrians, and diverse vehicles.
  • User experience report confirming accessibility and usability.

Conclusions:

  • The VR toolkit provides an accessible and cost-effective solution for researchers studying driver behavior in automated vehicles.
  • It enables realistic simulations for investigating critical takeover scenarios.
  • Facilitates advancements in human-machine interaction for future autonomous driving systems.