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      LED wristbands for Cell-based Crowd Evacuation: an Adaptive Exit-choice Guidance System Architecture

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          Abstract

          Cell-based crowd evacuation systems provide adaptive or static exit-choice indications that favor a coordinated group dynamic, improving evacuation time and safety. While a great effort has been made to modeling its control logic by assuming an ideal communication and positioning infrastructure, the architectural dimension and the influence of pedestrian positioning uncertainty have been largely overlooked. In our previous research, a Cell-based crowd evacuation system (CellEVAC) was proposed that dynamically allocates exit gates to pedestrians in a cell-based pedestrian positioning infrastructure. This system provides optimal exit-choice indications through color-based indications and a control logic module built upon an optimized discrete-choice model. Here, we investigate how location-aware technologies and wearable devices can be used for a realistic deployment of CellEVAC. We consider a simulated real evacuation scenario (Madrid Arena) and propose a system architecture for CellEVAC that includes: a controller node, a radio-controlled LED wristband subsystem, and a cell-node network equipped with active Radio Frequency Identification (RFID) devices. These subsystems coordinate to provide control, display and positioning capabilities. We quantitatively study the sensitivity of evacuation time and safety to uncertainty in the positioning system. Results showed that CellEVAC was operational within a limited range of positioning uncertainty. Further analyses revealed that reprogramming the control logic module through a simulation-optimization process, simulating the positioning system's expected uncertainty level, improved the CellEVAC performance in scenarios with poor positioning systems.

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          Author and article information

          Journal
          19 August 2020
          Article
          2008.11128
          f30fb76d-d671-41bc-b869-62f491a58ab1

          http://creativecommons.org/licenses/by-nc-sa/4.0/

          Custom metadata
          19 pages,11 figures
          cs.OH

          General computer science

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