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Optimizing Movement of Cooperating Pedestrians by Exploiting Floor-Field Model and Markov Decision Process
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SYSNO ASEP 0474861 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Optimizing Movement of Cooperating Pedestrians by Exploiting Floor-Field Model and Markov Decision Process Author(s) Sečkárová, Vladimíra (UTIA-B) RID
Hrabák, Pavel (UTIA-B)Number of authors 2 Source Title Bayesian Statistics in Action. - Cham : Springer International Publishing, 2017 / Argiento R. ; Lanzarone E. ; Villalobos I. A. ; Mattei A. - ISSN 2194-1009 - ISBN 978-3-319-54083-2 Pages s. 241-251 Number of pages 11 s. Publication form Print - P Action Bayesian Young Statisticians Meeting, BAYSM 2016 Event date 19.06.2016 - 21.06.2016 VEvent location Florence Country IT - Italy Event type WRD Language eng - English Country CH - Switzerland Keywords optimization of cooperating pedestrians ; floor-field model ; Markov decision process ; combination of transition probabilities Subject RIV BC - Control Systems Theory OECD category Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) R&D Projects GA13-13502S GA ČR - Czech Science Foundation (CSF) GA16-09848S GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 UT WOS 000418403500023 EID SCOPUS 85020024751 DOI 10.1007/978-3-319-54084-9 Annotation Optimizing movement of pedestrians is a topic of great importance, calling for modeling crowds. In this contribution we address the problem of evacuation, where pedestrians choose their actions in order to leave the endangered area. To address such decision making process we exploit the well-known floor-field model with modeling based on Markov decision processes (MDP). In addition, we also allow the pedestrians to cooperate and exchange their information (probability distribution) about the state of the surrounding environment. This information in form of probability distributions is then combined in the Kullback–Leibler sense. We show in the simulation study how the use of MDP and information sharing positively influences the amount of inhaled CO and the evacuation time. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2018
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