Optimizing Movement of Cooperating Pedestrians by Exploiting Floor-Field Model and Markov Decision Process

0474861 - ÚTIA 2018 RIV CH eng C - Conference Paper (international conference)
Sečkárová, Vladimíra - Hrabák, Pavel
Optimizing Movement of Cooperating Pedestrians by Exploiting Floor-Field Model and Markov Decision Process.
Bayesian Statistics in Action. Cham: Springer International Publishing, 2017 - (Argiento, R.; Lanzarone, E.; Villalobos, I.; Mattei, A.), s. 241-251. ISBN 978-3-319-54083-2. ISSN 2194-1009.
[Bayesian Young Statisticians Meeting, BAYSM 2016. Florence (IT), 19.06.2016-21.06.2016]
R&D Projects: GA ČR GA13-13502S; GA ČR(CZ) GA16-09848S
Institutional support: RVO:67985556
Keywords : optimization of cooperating pedestrians * floor-field model * Markov decision process * combination of transition probabilities
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://library.utia.cas.cz/separaty/2017/AS/seckarova-0474861.pdf

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.
Permanent Link: http://hdl.handle.net/11104/0272094