Abstract
Autonomous vehicles are increasingly becoming a reality, but for the driving vision information allocation is not clear enough. Driver distraction and inattention are the main causes of accidents. This paper presents experimental results of an eye tracker under real driving conditions, and analyses them from the design point of view. Clustering eye tracking data for each stage resulted in a pattern classification, as well as each type of driver’s visual and psychological characteristics, from which common eye gaze practices could be summed up. The improved concept depends on the drivers’ needs and desires and can serve as a basis for view management concepts of future HUD.
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Wang, X., Wang, Y., Zhang, X., Liu, C. (2018). Research on Driver’s Visual and Psychological Characteristics Under Right-Turning Scenario for Car Head-Up Displays. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2017. Advances in Intelligent Systems and Computing, vol 592. Springer, Cham. https://doi.org/10.1007/978-3-319-60366-7_21
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DOI: https://doi.org/10.1007/978-3-319-60366-7_21
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