Engaging augmented reality on 3D Head-Up Displays to Reduce Risky Driving

The overall aim of this ARC Linkage Project with industry partner Seeing Machines is to reduce risky driving behaviour and driver distraction using innovative 3D Head Up Display (HUD) applications.

More specifically, this research will:

  1. investigate how a new generation of 3D HUDs could be used to maintain a driver’s cognitive engagement on the primary driving task,
  2. design and develop novel 3D HUD applications that improve driver’s behaviour in real-time, and
  3. valuate, in a naturalistic setting, the benefit of the new application, considering their visual implications, human factors and other safety implication side effects.

The investigation takes place in the context of SAE Level 3 & 4 automated driving. We are currently developing HUD applications that aim to engage drivers and optimise their scanning behaviour, situational awareness and hazard perception in SAE Level 3 & 4 automated driving scenarios. We will develop desirable or entertaining content (games, watching videos, etc.) that is:

  1. displayed in such a way that it allows the driver/operator to observe traffic in the peripheral, and
  2. embedding contextual information in the content delivery in such a way that it further contributes to a heightened situation and mode awareness.

Using SeeingMachines’ Driver Monitoring System (DMS), we are particularly interested in how to measure the level of engagement in the primary driving task and cognitive distraction from the driving task, as well as the overall fallback readiness of the driver.

Award

Dr Ronald Schroeter and Michael Gerber won “Best Demonstration Award” at the 2018 Automotive User Interfaces (AutoUI) Conference in Toronto in September 2018.


Funding / Grants

  • ARC Linkage Grant (2015 - 2018)

Team

Other Team Members

This project includes Prof Joanne Wood from the QUT School of Optometry and Vision Science and Prof Daniel Johnson from the QUT School of Computer Science.

Partners

Publications

  • & (2018) A low-cost VR-based automated driving simulator for rapid automotive UI prototyping. In Donmez, B (Ed.) Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. Association for Computing Machinery, United States of America, pp. 248-251.
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  • , , & (2019) A video-based automated driving simulator for automotive UI prototyping, UX and behaviour research. In Volkel, Sarah Theres & Mirnig, Alexander G. (Eds.) Proceedings of the 11th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019. Association for Computing Machinery (ACM), United States of America, pp. 14-23.
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  • , , , & (2020) Self-Interruptions of Non-Driving Related Tasks in Automated Vehicles: Mobile vs Head-Up Display. In CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (ACM), United States of America, pp. 1-9.
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