@inproceedings{45e6571552014916996c587e474f2ef6,
title = "Visual Attention of Pedestrians in Traffic Scenes: A Crowdsourcing Experiment.",
abstract = "In a crowdsourced experiment, the effects of distance and type of the approaching vehicle, traffic density, and visual clutter on pedestrians{\textquoteright} attention distribution were explored. 966 participants viewed 107 images of diverse traffic scenes for durations between 100 and 4000 ms. Participants{\textquoteright} 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.",
keywords = "Automated driving, Crowdsourcing, Eye gazes, Pedestrians",
author = "Pavlo Bazilinskyy and Dimitra Dodou and Winter, {Joost C. F. de}",
note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",
year = "2021",
doi = "10.1007/978-3-030-80012-3_18",
language = "English",
isbn = "9783030800116",
series = "Lecture Notes in Networks and Systems",
pages = "147--154",
editor = "Neville Stanton",
booktitle = "Advances in Human Aspects of Transportation - Proceedings of the AHFE 2021",
}