@inproceedings{8575881fc12a4916a4f9f0880e02bfce,
title = "Watch Out! Modelling Pedestrians with Egocentric Distractions",
abstract = "The use of mobile devices is one of the most commonly observed family of distracted behaviours exhibited by pedestrians in urban environments. We develop an event-driven behaviour tree model for distracted pedestrians that includes initiating mobile device use as well as terminating or pausing mobile device use based on internal or external cues to refocus attention. We present a simple, probabilistic attention model for such pedestrians. The proposed model is not meant to be complete. It primarily focuses on computing the probability that a distracted agent looks up, based on the agent's individual characteristics and the elements in their environment. We condition the potentially attention grabbing elements in the environment on distraction-specific egocentric fields for visual attention. We also propose an oriented ellipse model for capturing the affects of cognitively fuzzy goals during distracted navigation. Our model is simple and intuitively parameterized, and thus can be easily edited and extended.",
keywords = "crowd simuation, distracted pedestrians, visual attention",
author = "Melissa Kremer and Brandon Haworth and Mubbasir Kapadia and Petros Faloutsos",
note = "Funding Information: Funding was provided by Ontario Research Foundation (Grant No. RE08-054) and National Science Foundation (Grant Nos. IIS1703883, S&AS-1723869). Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 13th ACM SIGGRAPH Conference on Motion, Interaction, and Games, MIG 2020 ; Conference date: 16-10-2020 Through 18-10-2020",
year = "2020",
month = oct,
day = "16",
doi = "10.1145/3424636.3426910",
language = "English (US)",
series = "Proceedings - MIG 2020: 13th ACM SIGGRAPH Conference on Motion, Interaction, and Games",
publisher = "Association for Computing Machinery, Inc",
editor = "Spencer, {Stephen N.}",
booktitle = "Proceedings - MIG 2020",
}