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      Virtual Reality Simulation and Eye Tracking to Assess Hazard Perception of Car Drivers


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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      Virtual Reality, Eye Tracking, Machine Learning, Simulated Training, Driving, Hazard Perception



            The assessment of a driver’s hazard perception on the road is difficult to measure. Using a Virtual Reality (VR) simulation coupled with eye tracking to objectively detect hazard recognition is a viable technological solution. The objective in this paper is to outline an approach that uses a virtual simulation to assess hazard perception of car drivers. This approach covers the development of a system capable of capturing the data required to interpret a subject’s attention (e.g. head and eye gaze scan path), and a proposed approach to using supervised machine learning algorithms to analyse this dataset and predict driver competency in hazard perception.


            Author and article information

            July 2018
            July 2018
            : 1-4

            4-6 Upper Cres, Belfast BT7 1NT, Northern Ireland, UK
            [0002]Ulster University

            Newtownabbey, County Antrim, BT37 0QB, Northern

            Ireland, UK
            © Ferris et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of the 32nd International BCS Human Computer Interaction Conference
            Belfast, UK
            4 - 6 July 2018
            Electronic Workshops in Computing (eWiC)
            Human Computer Interaction Conference
            Product Information: 1477-9358BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Electronic Workshops in Computing


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