### Browsing by Author "von Schantz, Anton"

Now showing 1 - 7 of 7

###### Results Per Page

###### Sort Options

Item Cellular Automaton Evacuation Model Coupled with a Spatial Game(2014) von Schantz, Anton; Ehtamo, Harri; Department of Mathematics and Systems Analysis; Slezak, Dominik; Schaefer, Gerald; Vuong, Son T.; Kim, Yoo-SungItem Minimization of mean-CVaR evacuation time of a crowd using rescue guides: a scenario-based approach(2021-07-07) von Schantz, Anton; Ehtamo, Harri; Hostikka, Simo; Department of Mathematics and Systems Analysis; Department of Civil EngineeringIn 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.Item Minimizing the evacuation time of a crowd from a complex building using rescue guides(Elsevier Science B.V., 2022-05-15) von Schantz, Anton; Ehtamo, Harri; Department of Mathematics and Systems AnalysisIn an emergency situation, the evacuation of a large crowd from a complex building can become slow or even dangerous without a working evacuation plan. The use of rescue guides that lead the crowd out of the building can improve the evacuation efficiency. An important issue is how to choose the number, positions, and exit assignments of these guides to minimize the evacuation time of the crowd. Here, we model the evacuating crowd as a multi-agent system with the social force model and simple interaction rules for guides and their followers. We formulate the problem of minimizing the evacuation time using rescue guides as a stochastic optimization problem. Then, we solve it with a procedure combining numerical simulation and a genetic algorithm (GA). The GA iteratively searches for the optimal evacuation plan, while numerical simulations evaluate the evacuation time of the plans. We apply the procedure on a test case and on an evacuation of a fictional conference building. The procedure is able to solve the number of guides, their initial positions and exit assignments in a single although complicated optimization. The attained results show that the procedure converges to an optimal evacuation plan, which minimizes the evacuation time and mitigates congestion and the effect of random deviations in agents’ motion.Item Numerical simulation and optimization models for socio-dynamical features of crowd evacuation(Aalto University, 2021) von Schantz, Anton; Ehtamo, Harri, Prof., Aalto University, Department of Mathematics and Systems Analysis, Finland; Matematiikan ja systeemianalyysin laitos; Department of Mathematics and Systems Analysis; Systems Analysis Laboratory; Perustieteiden korkeakoulu; School of Science; Ehtamo, Harri, Prof., Aalto University, Department of Mathematics and Systems Analysis, FinlandThe rapid increase of various mass gatherings and overcrowded festivals pose serious challenges, for example in case of emergency. Computational models may help to address issues related to these socio-physical systems, and in particular evacuating crowds. Physics-inspired self-driven particle models can describe most of the physics of moving crowds. However, there is still a need for comprehensive crowd models that can describe collective crowd effects, starting from individual crowd members' decision-making. In addition to models being able to describe harmful crowd phenomena, they should also prescribe solutions to prevent them. This dissertation concerns the mathematical and computational modeling of an evacuating crowd. The main focus is on studying how individual decision-making causes the harmful physical effects in a bottleneck evacuation. How should rescue guides be used to minimize the evacuation time of a crowd? What is the effect of uncertain crowd movement patterns on the minimum time evacuation plan? A multiagent framework is used to model the crowd. Its members are modeled as agents that interact with each other. The crowd dynamics are described using social force model based on Newtonian dynamics, and the agents' decision-making is described using evolutionary game theory. The model is studied by developing a simulation environment, which is implemented in a high-performance computing cluster. Numerical simulations show that due to the locally-played game, non-monotonous dynamical effects emerge. In a bottleneck congestion, the back of the crowd behaves impatiently. It pushes the agents in front of it, and pressure increases. As a result, arch-like structures form, capable of interrupting the flow and slowing down the evacuation. The arches break down due to fluctuating loads. The results coincide with findings from behavioral and physical evacuation experiments. New mathematical models and algorithms are developed to solve the minimum time crowd evacuation problem with rescue guides. The new methods are based on mathematical optimization, namely, on scenario optimization, genetic algorithms, numerical simulation-based optimization, and bi-objective optimization. Also, worst-case scenarios are accounted for with a risk measure. The solution to the minimum time evacuation problem gives the number of guides, their initial positions, and exit assignments. It is shown that there is a tradeoff between the evacuation plan that performs well across scenarios, and the one that performs well on the worst-case scenario. With enough guides, the uncertainty in the individual and crowd movement patterns is mitigated. This dissertation provides new practical tools for numerical simulation and optimization of dynamical features of crowd evacuation, and hopefully gives ways to prevent fatal accidents in emergencies.Item Pushing and overtaking others in a spatial game of exit congestion(Elsevier Science B.V., 2019-08-01) von Schantz, Anton; Ehtamo, Harri; Department of Mathematics and Systems AnalysisWith self-driven particle models, like the social force model, most of the physics of moving crowds can be modeled. However, it has not been fully unraveled why large crowds evacuating through narrow bottlenecks often act against their self-interest. They form jams in front of the bottleneck, that slow down the evacuation, and fatal pressures build up in the crowd. Here, we take a novel approach, and model the local decision-making in an evacuating crowd as a spatial game. The game is coupled to the social force model, so that different strategies alter the physical parameters. With our integrated treatment of behavioral and physical aspects, we are able to simulate when, why and how typical phenomena of an evacuation through a bottleneck occur. Most importantly, we attain non-monotonous speed and kinetic pressure patterns, in contrast to the monotonous patterns predicted by the pure social force model. This is a result of impatient agents in the back of the simulated crowd pushing and overtaking their way forward. Our findings give insight into the origin of crowd disasters, since the build-up of kinetic pressure has been related to the risk of falling and crowd turbulence.Item Spatial game in cellular automaton evacuation model(2015) von Schantz, Anton; Ehtamo, Harri; Department of Mathematics and Systems AnalysisFor numerical simulations of crowd dynamics in an evacuation we need a computationally light environment, such as the cellular automaton model (CA). By choosing the right model parameters, different types of crowd behavior and collective effects can be produced. But the CA does not answer why, when, and how these different behaviors and collective effects occur. In this article, we present a model, where we couple a spatial evacuation game to the CA. In the game, an agent chooses its strategy by observing its neighbors' strategies. The game matrix changes with the distance to the exit as the evacuation conditions develop. In the resulting model, an agent's strategy choice alters the parameters that govern its behavior in the CA. Thus, with our model, we are able to simulate how evacuation conditions affect the behavior of the crowd. Also, we show that some of the collective effects observed in evacuations are a result of the simple game the agents play.Item Two-type multi-agent game for egress congestion(2017) von Schantz, Anton; Ehtamo, Harri; Pärnänen, Ilmari; Department of Mathematics and Systems Analysis; Capgemini Finland OyOur starting point is a recently introduced spatial multiagent game for egress congestion. We present a twotype extension of the game. In the game, the agent chooses its strategy by observing its neighbors’ strategies. The agent’s reward structure depends on its distance to the exit and available safe egress time (TASET ). Although TASET is a well-defined physical quantity, it is assumed that the agents interpret it subjectively: it is assumed that there are high TASET and low TASET agent types. Also, we apply the game to a cellular automaton (CA) evacuation model. We show that high TASET agents are on average able to overtake low TASET agents. However, the more there are high TASET agents in the crowd, the more the evacuation becomes inefficient for the whole crowd.