Estimation of Discretised Motion of Pedestrians by the Decision-Making Model

Pavel Hrabák (), Ondřej Ticháček () and Vladimíra Sečkárová ()
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Pavel Hrabák: The Institute of Information Theory and Automation of the Czech Academy of Sciences
Ondřej Ticháček: The Institute of Information Theory and Automation of the Czech Academy of Sciences
Vladimíra Sečkárová: The Institute of Information Theory and Automation of the Czech Academy of Sciences

A chapter in Traffic and Granular Flow '15, 2016, pp 313-320 from Springer

Abstract: Abstract The contributionHrabák, Pavel gives a micro-structural insight intoTicháček, Ondřej the pedestrian decisionSečkárová, Vladimíra process during an egress situation. A method how to extract the decisions of pedestrians from the trajectories recorded during the experiments is introduced. The underlying Markov decision process is estimated using the finite mixture approximation. Furthermore, the results of this estimation can be used as an input to the optimisation of a Markov decision process for one ‘clever’ agent. This agent optimises his strategy of motion with respect to different reward functions, minimising the time spent in the room or minimising the amount of inhaled CO.

Keywords: Markov Decision Process; Reward Function; Discretised Motion; Pedestrian Flow; Neighbouring Sector (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-33482-0_40

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DOI: 10.1007/978-3-319-33482-0_40

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