Title: Entropy generation: a path for understanding human gait patterns and crowd dynamics
Author: Antonio F. Miguel
Address: Department of Physics, School of Science and Technology, University of Evora, Rua Romao Ramalho 59, 7000-671 Evora, Portugal
Abstract: Pedestrian dynamics can be interpreted as a self-organisation phenomenon, and can be exploited based on the measurement of the irreversibility of processes. Here, we focus on the measure of irreversibility on the collective human motion but also on individual's gait motion. In this context, entropy generation provides a measure of the extent of irreversibility. Analytical models are proposed for the generation of entropy in pedestrian motion. Our results underline that some fundamental features of pedestrian dynamics can be understood based on entropy generation. In particular, self-selected gait speed, and gait transitions from walking to running, can be linked to, and understood based on the quantification of entropy generation. In addition, we examine the extent of irreversibility in collective patterns of motion formed by pedestrian crowds. Our results underline that the existence of repulsive forces between pedestrians, when interpersonal distances are very small, leads to a particular trend of dissipation.
Keywords: entropy generation; self-selected gait speed; comfortable walking speed; walk-run transition; from walking to running; self-organisation; crowd dynamics; repulsive forces.
Int. J. of Exergy, 2017 Vol.23, No.1, pp.18 - 30
Submission date: 23 Nov 2016
Date of acceptance: 21 Jan 2017
Available online: 01 Jun 2017