Minimizing the evacuation time of a crowd from a complex building using rescue guides

Schantz, Anton von; Ehtamo, Harri

doi:10.1016/j.physa.2022.127011

Cited by 14 publications

(8 citation statements)

References 34 publications

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“…Next, we will present the crowd movement model used for evacuation of a passenger terminal. It is the deterministic version of the social force model presented in von Schantz & Ehtamo (2020). It is essentially Helbing's original social force model, with a velocity-dependent social repulsion force.…”

Section: Evacuation Model With Guidesmentioning

confidence: 99%

“…A working evacuation plan should be robust against them. Related to this, we recently raised the question in von Schantz & Ehtamo (2020): how should a crowd be evacuated when there is the possibility that a large part of it deviates from its usual rules of motion? Here, our objective is to study how the guides should be coordinated so that the crowd is evacuated in minimum time considering different crowd flow traffic scenarios.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the research on using guides are comparative studies, where different configurations are numerically simulated and compared. There are only few studies where mathematical optimization has been used Albi et al (2016); Zhou et al (2019); von Schantz & Ehtamo (2020). On the other hand, the need for rigorous mathematical approaches have been recognized Haghani (2020).…”

Section: Introductionmentioning

confidence: 99%

“…In our recent study von Schantz & Ehtamo (2020), the number of guides, their initial positions and exit assignments needed to minimize the crowd evacuation time is solved in a single optimization problem. In it, the crowd is modeled with the stochastic social force model to which interaction rules between regular agents and guides are added.…”

Section: Introductionmentioning

confidence: 99%

“…The minimum time crowd evacuation problem is first formulated as a stochastic control problem. Then it is reformulated as a scenario optimization problem and solved with a combined numerical simulation and genetic algorithm (GA) von Schantz & Ehtamo (2020).…”

Section: Introductionmentioning

confidence: 99%

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Minimization of mean-CVaR evacuation time of a crowd using rescue guides: a scenario-based approach

Schantz¹,

Ehtamo²,

Hostikka³

2020

Preprint

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In case of a threat in a public space, the crowd in it should be moved to a shelter or evacuated without delays. Risk management and evacuation planning in public spaces should also take into account uncertainties in the traffic patterns of crowd flow. One way to account for the uncertainties is to make use of safety staff, or guides, that lead the crowd out of the building according to an evacuation plan. Nevertheless, solving the minimum time evacuation plan is a computationally demanding problem. In this paper, we model the evacuating crowd and guides as a multi-agent system with the social force model. To represent uncertainty, we construct probabilistic scenarios. The evacuation plan should work well both on average and also for the worst-performing scenarios. Thus, we formulate the problem as a bi-objective scenario optimization problem, where the mean and conditional value-at-risk (CVaR) of the evacuation time are objectives. A solution procedure combining numerical simulation and genetic algorithm is presented. We apply it to the evacuation of a fictional passenger terminal. In the mean-optimal solution, guides are assigned to lead the crowd to the nearest exits, whereas in the CVaR-optimal solution the focus is on solving the physical congestion occurring in the worst-case scenario.With one guide positioned behind each agent group near each exit, a plan that minimizes both objectives is obtained.

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Section: Evacuation Model With Guidesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%