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Modeling of Behavioral Changes in Agent-Based Simulations

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Modeling of Behavioral Changes in Agent-Based Simulations Fakultät für Informatik / Lehrstuhl für wissenschaftliches Rechnen Technische Universität München Modeling of Behavioral Changes in Agent-Based Simulations Bridging the gap between social and computer science by operationalizing psychological processes Benedikt Kleinmeier Vollständiger Abdruck der von der Fakultät für Informatik der Technischen Universität München zur Erlangung des akademischen Grades eines Doktor der Naturwissenschaften (Dr. rer. nat.) genehmigten Dissertation. Vorsitzender: Prof. Dr.-Ing. Georg Carle Prüfende der Dissertation: 1. Prof. Dr. Hans-Joachim Bungartz 2. Prof. Dr. Gerta Köster (Hochschule München) Die Dissertation wurde am 17.02.2021 bei der Technischen Universität München eingereicht und durch die Fakultät für Informatik am 13.04.2021 angenommen. Abstract This dissertation contributes to the field of pedestrian dynamics. Pedestrian dynam- ics tries to better understand crowd behavior to make gatherings safer. In particular, one wants to avoid crowd disasters like the one at the Love Parade festival in Germany, 2010, with 21 dead or at the Hajj with hundreds of casualties in several years. Pedestrian dynamics researchers carry out experiments and simulate large crowds and pedestrian streams. Current crowd simulation models mostly focus on physically correct simula- tions but neglect psychological aspects which affect crowd behavior. This dissertation describes my efforts to model behavioral changes in agent-based simulations and how I try to bridge the gap between computer science and social sciences to get accurate crowd simulation results. In Part I of this work, I conduct an exhaustive literature research on current modeling approaches and psychological aspects. I distill three important concepts from the broad research field of psychology that must be integrated into state-of-the-art simulations: perception, cognition and behavior. In Part II of this dissertation, I implement these aspects in an established open-source simulation tool. I base my modeling efforts on latest psychological findings. I implement the findings as reusable psychology layer which can easily be integrated into other crowd simulation tools to be beneficial for the whole research community. My modeling effort is supported by an own experiment with 58 participants in which I document human behavior in a specific safety-relevant scenario. In the experiment, I extract quantitative and qualitative data for the model refinement and validation. I use three real-world scenarios to show that my approach is able to reenact a wide range of human behavior which can be observed in reality. My modeling approach is easy to understand and reusable. It aims to better con- nect natural and life sciences because knowledge from both disciplines is necessary to simulate and understand crowd behavior. My approach also provides clear guidelines to operationalize observed human behavior for future simulations with the three sequential phases perception, cognition and a selection of suitable behaviors. Keywords: computer science, psychology, pedestrian dynamics, modeling, experiment, humans, behavioral changes With: 97 figures, 18 tables, 14 listings, 221 references iii Zusammenfassung Diese Arbeit trägt zum Forschungsgebiet der Fußgängerdynamik (engl. Pedestrian Dy- namics) bei. Pedestrian Dynamics versucht das Verhalten von Menschenmengen besser zu verstehen und so Veranstaltungen sicherer zu machen. Im Besonderen gilt es, Kata- strophen zu verhindern wie bei der Loveparade 2010 in Deutschland mit 21 Toten oder wiederholt bei der jährlichen Haddsch. Forscher auf dem Gebiet der Fußgängerdyna- mik versuchen das Verständnis durch zwei Teilbereiche zu vertiefen: Experimente mit Menschen und der Simulation von Menschenmengen. Dabei fokussieren sich die gegen- wärtigen Simulationsmodelle überwiegend auf eine physikalisch korrekte Simulation. Jedoch werden bei der Simulation psychologische Aspekte vernachlässigt, welche sich auf das Verhalten von Menschenmengen auswirken können. Aus diesem Grund widmet sich diese Arbeit diesem Missstand. Die Dissertation beschreibt die Modellierung von menschlichen Verhaltensänderungen für agentenbasierte Fußgängersimulationen. Der erste Teil dieser Arbeit widmet sich einer umfassenden Literaturübersicht zu ak- tuellen Modellierungsansätzen und psychologischen Aspekten, welche menschliche Ver- haltensänderungen beeinflussen können. Aus dem breiten Forschungsgebiet der Psycho- logie arbeite ich drei essentielle Konzepte heraus, welche in State-of-the-Art-Simulati- onen integriert werden müssen: Perzeption, Kognition und Verhalten. Im zweiten Teil dieser Arbeit implementiere ich diese drei wesentlichen Konzepte in einem etablier- ten Open-Source-Fußgängersimulator. Dabei fußt meine Implementierung auf neuestem psychologischen Wissen. Der Fokus meiner Arbeit liegt in der Schaffung einer wieder- verwendbaren Architektur, welche sich auch einfach in eine Vielzahl weiterer Fußgän- gersimulatoren integrieren lässt. Aus diesem Grund kapsle ich meine Implementierung als wiederverwendbare Psychologieschicht. Dadurch ist meine Modellierung und Imple- mentierung für die gesamte Forschungsgemeinschaft nützlich. Meine Modellierung wird unterstützt durch ein eigenes Fußgängerexperiment mit 58 Teilnehmern. Ich nutze die neu geschaffene Psychologieschicht, um drei reale Situationen als Simulationen nachzu- stellen. Die erfolgreiche Anwendung zeigt, dass mein Ansatz in der Lage ist, ein breites Spektrum von menschlichen Verhaltensänderungen korrekt und realitätsnah abzubilden. Mein Modellierungsansatz ist einfach zu verstehen und vor allem wiederverwendbar. Mein Ziel ist es Natur- und Sozialwissenschaften besser zu verbinden, da Wissen aus bei- den Bereichen notwendig ist, um das Verhalten von Menschenmengen zu verstehen und korrekt zu simulieren. Mein Ansatz liefert klare Leitlinien für Modellierer, um menschli- ches Verhalten systematisch für Simulationen zu operationalisieren. Diese Leitlinien sind durch Perzeption, Kognition und einem Verhaltensrepertoire gegeben. Themenbereiche: Informatik, Psychologie, Fußgängerdynamik, Modellierung, Experi- ment, Menschen, Verhaltensänderungen Mit: 97 Abbildungen, 18 Tabellen, 14 Listings, 221 Quellen iv Acknowledgment My role as writer and principal researcher of this dissertation is only one part of the game. There are many other people in the background which influenced my thoughts and supported this work. I would like to thank Hans-Joachim Bungartz for supervising this dissertation from the university side. This should be not taken for granted because my research group is hosted at the Munich University of Applied Sciences. But, it is Hans’ diverse interest in many topics which makes this collaboration possible and it is a great platform to exchange ideas and to share knowledge. Hans, you are available at any time of the day — and also all night long — willing to give feedback. Therefore, thank you very much! I would like to thank Gerta Köster for building up the pedestrian dynamics research group at the Munich University of Applied Sciences and proofreading this work. You write time-consuming research proposals, ask for funding and provide valuable feed- back in discussions. This ensures that researchers with different backgrounds (computer science, mathematics, mechanical engineering and also psychology) can work on in- teresting research questions across disciplines. This interdisciplinarity promotes under- standing. Former members of the research group (Michael Seitz, Isabella von Sivers and Felix Dietrich) helped to build up the research group from which the current generation of researchers benefits. I would like to thank the current members of the research group: Benedikt Zönnchen, Daniel Lehmberg, Marion Gödel, Stefan Schuhbäck, Christina Mayr and Simon Rahn. We had a lot of fun in our daily work, when visiting conferences or also in our leisure time. Keep up the good work. A special thanks to John Drury for inviting and hosting me at the School of Psychol- ogy (University of Sussex) in 2019. The collaboration and discussion with John and members of his research group “Crowds & Identities” helped enormously to operational- ize observed behavior and mold it into a reusable computer model. The research stay helped to bridge computer science and psychology and is a starting point to get more reliable pedestrian and crowd simulations. A special thanks to two brave proofreaders: Benedikt Zönnchen and Simone “Zitrone” Jehl. And of course, thank you to my family. It is good to have you! v “Everything should be made as simple as possible, but not simpler.” Attributed to Albert Einstein (O’Toole 2011) vi Table of contents Abstract iii Acknowledgmentv Table of contents vii Figures, tables and listingsx List of figures.....................................x List of tables..................................... xiii List of listings..................................... xiii 1 Introduction1 1.1 Motivation: Why we need pedestrian dynamics models...........1 1.2 Challenges in simulating pedestrian dynamics................2 1.3 Goals and research question..........................5 1.4 Structure of this work.............................6 1.5 Infrastructure and tools............................7 I State of the Art9 2 Simulations of pedestrian dynamics 11 2.1 Different perspectives on pedestrian streams................. 11 2.2 Pedestrian stream models for locomotion................... 12 2.2.1 Macroscopic locomotion models.................... 15 2.2.2 Mesoscopic/Multi-scale locomotion models............. 21
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