Numerical simulation and optimization models for socio-dynamical features of crowd evacuation

Anton von Schantz

Research output: ThesisDoctoral ThesisCollection of Articles


The 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.
Translated title of the contributionVäkijoukon evakuoinnin sosiodynaamisten ilmiöiden numeeriset simulointi- ja optimointimallit
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
  • Ehtamo, Harri, Supervising Professor
  • Ehtamo, Harri, Thesis Advisor
Print ISBNs978-952-64-0368-7
Electronic ISBNs978-952-64-0369-4
Publication statusPublished - 2021
MoE publication typeG5 Doctoral dissertation (article)


  • crowd evacuation
  • multiagent system
  • evolutionary game theory
  • numerical simulation
  • mathematical optimization
  • non-monotonous dynamics


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