This article presents a new simulation approach for multidestination pedestrian crowds in complex environments. The work covers two major topics. In the first part, a novel cellular automaton (CA) model is proposed. The model describes the pedestrian movement by a set of simple rules and produces fundamental diagrams similar to those derived from laboratory experiments. The second topic of this work describes how the CA can be integrated into an iterative learning cycle where the individual pedestrian can adapt travel plans based on experiences from previous iterations. Depending on the setup, the overall travel behavior moves either toward a Nash equilibrium or the system optimum. The functional interaction of the CA with the iterative learning approach is demonstrated on a set of transport paradoxes. Furthermore, time series of speed and density observed in a small-scale experiment show a general agreement between the CA simulation and laboratory experiments. The scalability of the proposed approach is demonstrated on a large-scale scenario.

Crociani, L., Lämmel, G. (2016). Multidestination Pedestrian Flows in Equilibrium: A Cellular Automaton-Based Approach. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 31(6), 432-448 [10.1111/mice.12209].

Multidestination Pedestrian Flows in Equilibrium: A Cellular Automaton-Based Approach

Crociani, L;
2016

Abstract

This article presents a new simulation approach for multidestination pedestrian crowds in complex environments. The work covers two major topics. In the first part, a novel cellular automaton (CA) model is proposed. The model describes the pedestrian movement by a set of simple rules and produces fundamental diagrams similar to those derived from laboratory experiments. The second topic of this work describes how the CA can be integrated into an iterative learning cycle where the individual pedestrian can adapt travel plans based on experiences from previous iterations. Depending on the setup, the overall travel behavior moves either toward a Nash equilibrium or the system optimum. The functional interaction of the CA with the iterative learning approach is demonstrated on a set of transport paradoxes. Furthermore, time series of speed and density observed in a small-scale experiment show a general agreement between the CA simulation and laboratory experiments. The scalability of the proposed approach is demonstrated on a large-scale scenario.
Articolo in rivista - Articolo scientifico
Civil and Structural Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Computer Graphics and Computer-Aided Design; Computational Theory and Mathematics
English
2016
31
6
432
448
none
Crociani, L., Lämmel, G. (2016). Multidestination Pedestrian Flows in Equilibrium: A Cellular Automaton-Based Approach. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 31(6), 432-448 [10.1111/mice.12209].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/199728
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