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

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.