Abstract
In a crowdsourced experiment, the effects of distance and type of the approaching vehicle, traffic density, and visual clutter on pedestrians’ attention distribution were explored. 966 participants viewed 107 images of diverse traffic scenes for durations between 100 and 4000 ms. Participants’ eye-gaze data were collected using the TurkEyes method. The method involved briefly showing codecharts after each image and asking the participants to type the code they saw last. The results indicate that automated vehicles were more often glanced at than manual vehicles. Measuring eye gaze without an eye tracker is promising.
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Acknowledgement
This research is supported by grant 016.Vidi.178.047 (“How should automated vehicles communicate with other road users?”), which is financed by the Netherlands Organisation for Scientific Research (NWO).
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Bazilinskyy, P., Dodou, D., De Winter, J.C.F. (2021). Visual Attention of Pedestrians in Traffic Scenes: A Crowdsourcing Experiment. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2021. Lecture Notes in Networks and Systems, vol 270. Springer, Cham. https://doi.org/10.1007/978-3-030-80012-3_18
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