Windshield Frame Shape and Awareness of the External World While Driving an Automobile
The vehicle windshield is supported and framed by the hood, roof, and pillars, which occlude the driver’s view of the outside. It has been previously shown that awareness of the external world changes according to differences in windshield shape. This dir
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Takeda (&) K. Iwase T. Hara A. Kishi K. Nishikawa T. Nouzawa Technical Research Center, Mazda Motor Corporation, 3-1, Shinchi, Fuchu-cho, Aki-gun, Hiroshima 730-8670, Japan e-mail: [email protected] K. Iwase e-mail: [email protected] T. Hara e-mail: [email protected] A. Kishi e-mail: [email protected] K. Nishikawa e-mail: [email protected] T. Nouzawa e-mail: [email protected] R. Veale M. Yoshida T. Isa Department of Developmental Physiology, National Institute for Physiological Sciences, Division of Behavioral Development, 38 Nishigonaka Myodaiji, Okazaki, Aichi 444-8585, Japan e-mail: [email protected] M. Yoshida e-mail: [email protected] T. Isa e-mail: [email protected] © Springer International Publishing Switzerland 2017 K.S. Hale and K.M. Stanney (eds.), Advances in Neuroergonomics and Cognitive Engineering, Advances in Intelligent Systems and Computing 488, DOI 10.1007/978-3-319-41691-5_32
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focuses on Itti and Koch’s visual saliency that attracts bottom-up attention as a visual scene changes in shape and color around front windshield frame during driving. This paper aims to quantify the relationships between drivers’ gaze movements and visual saliency.
Keywords External awareness Visual shapes and properties of the windshield frame Visual saliency while driving a vehicle
1 Introduction We look through the windshield when driving a vehicle. The windshield is supported and framed by the hood, roof, and pillars, which occlude the driver’s view of the outside. It has been previously shown that recognition of objects outside the car changes according to differences in windshield shape, and affects drivability. Thus, the relationship between windshield shape and driver visual performance must be quantified so that it can be balanced with other performance measures such as weight and roominess to design the optimal cockpit. Visual performance during driving consists of role-sharing between (1) bottom-up attention and (2) top-down attention, and the processes selecting between them. Many psychological and computational studies on bottom-up attention have been reported. For example, Treisman and Gelade [1] proposed the feature integration theory of visual attention. They explained psychologically that visual stimuli are simultaneously processed in independent feature channels (e.g., intensity, color, orientation and motion) and are finally integrated into a ‘master map’. Furthermore, Koch and Ullman [2] proposed a ‘saliency map’ that expresses how bottom-up attention is calculated computationally. Since then, several researchers have measured gaze movements and quantified the relationship between gaze movements and visual stimulus characteristics quantitatively. Furthermore, Itti and Koch [3] proposed a computational algorithm to compute the saliency map while subjects look at a still image or video. This algorithm estimates the time needed to find a target in a visual search paradigm by assuming that the subject will look at items in order of how sali
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