Miguel Angel Lopez-Carmona
Profesor Titular de Universidad. Associate Professor.
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Articles (13)
Exit‐choice behavior significantly influences the performance of egress operations in crowded spaces. Thus, strategically issuing active exit‐choice recommendations that provide clear and concise guidance to pedestrians can help improve evacuation safety and efficiency. This study investigates how to optimally regulate pedestrian density at the exits by generating time‐multiplexed exit‐choice recommendations. The study develops a simulated crowd evacuation scenario with multiple exits, where pedestrians receive periodic sequences of exit‐choice instructions. The optimal period for each instruction is obtained through simulation‐optimization processes with three minimization objectives: evacuation time, cumulative density, and cumulative density variance. First, the effect of collective behaviors on evacuation performance is studied, which justifies the need for active mechanisms to improve exit‐choice decision‐making coordination. Then, several optimal plans for the different objectives are obtained and evaluated regarding evacuation time and cumulative density performance. Finally, the influence of adoption rate and collective commitment to instructions are evaluated. This study suggests that static plans, defined as time‐multiplexed exit‐choice instructions obtained through simulation‐optimization, reasonably represent a first step in the real deployment of intelligent crowd management systems.
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2024
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2024
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2024
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2023
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2023
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2023
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2022
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2022
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2021
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2021
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2021
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2020
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2020
Collaborators (7)
Alvaro Paricio‐Garcia
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Robert Alms
Deutsches Zentrum für Luft- und Raumfahrt
Andreas Freymann
Fraunhofer-Institut für Arbeitswirtschaft und Organisation
Diego Lopez-Pajares
Universidad de Alcalá
Joshua Bittle
Associate Professor
The University of Alabama
Joerg Schweizer
University of Bologna
Tobias Meuser
Technische Universität Darmstadt
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