Elsevier

Safety Science

Volume 139, July 2021, 105215
Safety Science

CellEVAC: An adaptive guidance system for crowd evacuation through behavioral optimization

https://doi.org/10.1016/j.ssci.2021.105215Get rights and content
Under a Creative Commons license
open access

Highlights

  • CellEVAC: adaptive cell-based colored indications to guide evacuees.

  • Behavioral model optimization to implement evacuation systems.

  • AnyLogic and Matlab simulation–optimization framework, a cutting-edge solution.

  • Pedestrian Fundamental diagrams to the rescue of safe evacuations.

  • Imitation behavior, a trustworthy ally of CellEVAC.

Abstract

A critical aspect of crowds’ evacuation processes is the dynamism of individual decision making. Identifying optimal strategies at an individual level may improve both evacuation time and safety, which is essential for developing efficient evacuation systems. Here, we investigate how to favor a coordinated group dynamic through optimal exit-choice instructions using behavioral strategy optimization. We propose and evaluate an adaptive guidance system (Cell-based Crowd Evacuation, CellEVAC) that dynamically allocates colors to cells in a cell-based pedestrian positioning infrastructure, to provide efficient exit-choice indications. The operational module of CellEVAC implements an optimized discrete-choice model that integrates the influential factors that would make evacuees adapt their exit choice. To optimize the model, we used a simulation–optimization modeling framework that integrates microscopic pedestrian simulation based on the classical Social Force Model. In the majority of studies, the objective has been to optimize evacuation time. In contrast, we paid particular attention to safety by using Pedestrian Fundamental Diagrams that model the dynamics of the exit gates. CellEVAC has been tested in a simulated real scenario (Madrid Arena) under different external pedestrian flow patterns that simulate complex pedestrian interactions. Results showed that CellEVAC outperforms evacuation processes in which the system is not used, with an exponential improvement as interactions become complex. We compared our system with an existing approach based on Cartesian Genetic Programming. Our system exhibited a better overall performance in terms of safety, evacuation time, and the number of revisions of exit-choice decisions. Further analyses also revealed that Cartesian Genetic Programming generates less natural pedestrian reactions and movements than CellEVAC. The fact that the decision logic module is built upon a behavioral model seems to favor a more natural and effective response. We also found that our proposal has a positive influence on evacuations even for a low compliance rate (40%).

Keywords

Crowd evacuation
Behavioral optimization
Exit-choice decisions
Simulation–optimization modeling
Cell-based evacuation
Evacuation safety

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