Commit ae8d5bcc authored by Arne Graf's avatar Arne Graf

before tikz

parent f5709404
\@writefile{toc}{\contentsline {section}{\numberline {1}Pedestrian Dynamics: Introduction}{5}}
\@writefile{toc}{\contentsline {section}{\numberline {2}ODE based Model}{5}}
\@writefile{toc}{\contentsline {section}{\numberline {3}Modelling}{5}}
\@writefile{toc}{\contentsline {subsection}{\numberline {3.1}Variant Model}{7}}
\@writefile{toc}{\contentsline {subsection}{\numberline {3.2}Eikonal Equation}{7}}
\@writefile{lof}{\contentsline {figure}{\numberline {3.1}{\ignorespaces Isolines of a floor-field.}}{7}}
\newlabel{replace with bibtex:}{{3.2}{8}}
\@writefile{toc}{\contentsline {subsection}{\numberline {3.3}Safe Navigation using the Floorfield}{8}}
\@writefile{toc}{\contentsline {subsection}{\numberline {3.4}Distances-Field}{9}}
\@writefile{toc}{\contentsline {subsubsection}{\numberline {3.4.1}Cost of a ``full'' preprocessing step }{10}}
\@writefile{toc}{\contentsline {subsubsection}{\numberline {3.4.2}Distances-Field and repulsive Wall-Forces}{10}}
\@writefile{toc}{\contentsline {subsection}{\numberline {3.5}Idea of Separation of a Moving-Vector into Direction and Magnitute}{11}}
\@writefile{toc}{\contentsline {subsubsection}{\numberline {3.5.1}no clipping}{11}}
\@writefile{toc}{\contentsline {subsubsection}{\numberline {3.5.2}Recycling the Distances Field (neg. Gradient must be saved)}{11}}
\@writefile{toc}{\contentsline {section}{\numberline {4}Testing}{11}}
\@writefile{toc}{\contentsline {section}{\numberline {5}Outlook}{11}}
\@writefile{toc}{\contentsline {subsection}{\numberline {5.1}Floor-field}{11}}
\@writefile{toc}{\contentsline {subsubsection}{\numberline {5.1.1}Multiple Goals }{11}}
\@writefile{toc}{\contentsline {subsubsection}{\numberline {5.1.2}Multiple Floors}{11}}
\@writefile{toc}{\contentsline {paragraph}{Neighboring Relations}{11}}
\@writefile{toc}{\contentsline {subsection}{\numberline {5.2}Usage in JuPedSim}{12}}
\@writefile{toc}{\contentsline {subsection}{\numberline {5.3}Floor-fields in Triangulated Domains}{12}}
\@writefile{toc}{\contentsline {subsection}{\numberline {5.4}Parallelization}{12}}
\@writefile{toc}{\contentsline {section}{\numberline {6}Appendices}{12}}
\@writefile{toc}{\contentsline {subsection}{\numberline {6.1}Fast-Marching Algorithm}{12}}
\@writefile{toc}{\contentsline {subsection}{\numberline {6.2}Classes and their Relations}{12}}
\@writefile{toc}{\contentsline {subsection}{\numberline {6.3}Code Snippets}{12}}
\@writefile{toc}{\contentsline {section}{\numberline {7}Bibliography}{12}}
@online{Universidad Carlos III de Madrid, RoboticsLab, @online{Madrid,
author = {L.Moreno et al.}, AUTHOR = {Moreno},
title = {Fast Marching}, TITLE = {Fast Marching,},
date = {2014-12-19}, DATE = {2014-12-19},
url = {}, YEAR = {2014},
} URL = {},
\ No newline at end of file }
Title = {Gradient navigation model for pedestrian dynamics},
Author = {Dietrich, Felix and K{\"o}ster, Gerta},
Journal = {Arxiv e-prints},
Year = {2014},
File = {:pdf\\Dietrich2014.pdf:PDF},
Keywords = {Agent, Pedestrians, Modelling, Microscopic, Ordinary differential equations (ODE), Flow},
Owner = {WeichenLiao},
Timestamp = {2014.01.09}
Title = {Validated force-based modeling of pedestrian dynamics},
Author = {Chraibi, Mohcine},
School = {Universit{\"a}t zu K{\"o}ln},
Year = {2012},
Month = {March, 15},
File = {:pdf\\Chraibi2012.pdf:PDF},
Owner = {Fred},
Timestamp = {2012.07.18}
Title = {Route choice modelling and runtime optimisation for simulation of building evacuation},
Author = {Kemloh Wagoum, Armel Ulrich},
Journal = {Schriften des Forschungszentrums J{\"u}lich},
Year = {2013},
Note = {pedestrian dynamics, route choice, evacuation, high performance computing},
Volume = {17},
Abstract = {Increasing number of visitors at large-scale events combined with the increasing complexity of modern buildings set a major challenge for planners, operators and emergency services. Examples include multi-purpose arenas, large railway stations and airports. In this dissertation the use of modern parallel hardware in combination with optimised algorithms are for the first time used on site to speed up the simulation of large crowds. The aim is to perform real-time forecasts of pedestrian traffic. For this purpose, specialneighbourhood lists and a two-stage hybrid parallelisation are used. Thesecond part of this dissertation deals with route choice in complex structures, which plays an important role in achieving realistic computer simulations of pedestrian flows. The developed route choice process is based on visibility and perception of the local environment by the simulated agents. It has as basis a navigation graph. The generation of the graph, espe- cially in complex structures, has also been performed within the framework of this thesis. The work is closed with an empirical study in which the route choice profiles of spectators during various football games and concert performances are analysed and compared with the proposed model. The runtime optimisation strategies and route choice algorithms have been successfully tested in the ESPRIT arena in Düsseldorf (Germany), where they have been integrated in an evacuation assistant.},
File = {:pdf/KemlohWagoum2013.pdf:PDF},
ISBN = {978-3-89336-865-5},
ISSN = {1868-8489},
Keywords = {pedestrian dynamics, route choice, evacuation, high performance computing},
Owner = {f},
Timestamp = {2013.04.30}
Title = {Parallel Implementation of Fast Marching Method, 18.337 final report},
Author = {Leonardo Andrés Zepeda Núñez},
Journal = {},
Year = {2011},
TITLE = {},
DATE = {},
YEAR = {2015},
URL = {},
Title = {How simple rules determine pedestrian behavior and crowd disasters},
Author = {Moussa\"id, Mehdi and Helbing, Dirk and Theraulaz, Guy},
Journal = {PNAS},
Year = {2011},
Abstract = {With the increasing size and frequency of mass events, the study of crowd disasters and the simulation of pedestrian flows have become important research areas. However, even successful modeling approaches such as those inspired by Newtonian force models are still not fully consistent with empirical observations and are sometimes hard to calibrate. Here, a cognitive science approach is proposed, which is based on behavioral heuristics. We suggest that, guided by visual information, namely the distance of obstructions in candidate lines of sight, pedestrians apply two simple cognitive procedures to adapt their walking speeds and directions. Although simpler than previous approaches, this model predicts individual trajectories and collective patterns of motion in good quantitative agreement with a large variety of empirical and experimental data. This model predicts the emergence of self-organization phenomena, such as the spontaneous formation of unidirectional lanes or stop-and-go waves. Moreover, the combination of pedestrian heuristics with body collisions generates crowd turbulence at extreme densities-a phenomenon that has been observed during recent crowd disasters. By proposing an integrated treatment of simultaneous interactions between multiple individuals, our approach overcomes limitations of current physics-inspired pair interaction models. Understanding crowd dynamics through cognitive heuristics is therefore not only crucial for a better preparation of safe mass events. It also clears the way for a more realistic modeling of collective social behaviors, in particular of human crowds and biological swarms. Furthermore, our behavioral heuristics may serve to improve the navigation of autonomous robots.},
Comment = {Social Force Modell, microscopic, modelling, stop-and-go waves},
File = {Moussaid2011.pdf:pdf/Moussaid2011.pdf:PDF},
Owner = {portz},
Timestamp = {2011.05.06}
Title = {Force-based models of pedestrian dynamics},
Author = {Chraibi, M. and Kemloh, U., Seyfried, A. and Schadschneider, A.},
Journal = {Networks and Heterogeneous Media},
Year = {2011},
Number = {3},
Pages = {425--442},
Volume = {6},
Abstract = {Force-based models describe the interactions of pedestrians in terms of physical and social forces. We discuss some intrinsic problems of this ap- proach, like penetration of particles, unrealistic oscillations and velocities as well as conceptual problems related to violations of Newton’s laws. We then present the generalized centrifugal force model which solves some of these prob- lems. Furthermore we discuss the problem of choosing a realistic driving force to an exit. We illustrate this problem by investigating the behaviour of pedes- trians at bottlenecks.},
Doi = {10.3934/nhm.2011.6.425},
File = {:pdf\\Chraibi2011.pdf:PDF},
Keywords = {Pedestrian dynamics, flow, bottleneck, force-based models.},
Owner = {mmueller},
Timestamp = {2011.10.26},
Url = {}
Title = {Adaptive pedestrian dynamics based on geodesics},
Author = {Hartmann, Dirk},
Journal = {New Journal of Physics},
Year = {2010},
Pages = {043032},
Volume = {12},
Abstract = {Here, we report on a new approach for adaptive path finding in microscopic simulations of pedestrian dynamics. The approach extends a widely used concept based on scalar navigation field -- the so-called floor field method. Adopting a continuum perspective, navigation fields used in our approach correspond to the shortest distances to the pedestrian's targets with respect to arbitrary metrics, e.g. metrics depending on the local terrain. If the metric correlates inversely with the expected speed, these distances could be interpreted as expected travel times. Following this approach, it is guaranteed that virtual pedestrians navigate along the steepest descent of the navigation field and thus follow geodesics. Using the Eikonal equation, i.e. a continuum model, navigation fields can be determined with respect to arbitrary metrics in an efficient manner. The fast marching method used in this work offers a fast method to solve the Eikonal equation (complexity N log N, where N is degree of freedom). Increasing computational efforts with respect to classical approaches only mildly, the consideration of locally varying metrics allows a realistic adaptive movement behavior like the avoidance of certain terrains. The method is outlined using a simple cellular automaton approach. Extensions to other microscopic models, e.g. cellular automata approaches or social force models, are possible.},
Comment = {shortest path, quickest path, routing, re-routing, travel time},
File = {Hartmann2010.pdf:pdf/Hartmann2010.pdf:PDF},
Owner = {portz},
Timestamp = {2010.10.22}
Title = {JuPedSim.}
Author = {Forschungszentrum J{\"u}lich GmbH, JSC, CST}
Year = {2015}
URL = {}
Title = {Personenstr\"ome in Geb\"auden - Berechnungsmethoden f\"ur die Projektierung},
Author = {Predtechenskii, W. M. and Milinskii, A. I.},
Publisher = {Verlagsgesellschaft Rudolf M{\"u}ller, K{\"o}ln-Braunsfeld},
Year = {1971},
Note = {Original in Russian, Stroiizdat Publishers, Moscow, 1969},
File = {Predtechenskii1971.pdf:pdf/Predtechenskii1971.pdf:PDF},
Owner = {portz},
Timestamp = {2008.01.09}
Title = {A simulation of the behavior of a crowd in panic},
Author = {Hirai, K. and Tarui, K.},
Booktitle = {Proc. of the 1975 International Conference on Cybernetics and Society},
Year = {1975},
Address = {San Francisco},
Pages = {409-411},
Abstract = {The purpose of this paper is to study the behavior of a crowd in panic by digital simulation. Psychologienl factors and effects of the environment such as the presence of sign or symbol to guide the crowd to exits in emergency, wall eonfigurations, and the location of emergency exits, were taken into consideration in constructing a mathematical model of a crowd. These simulation results ean be applied to the control of crowds in panic.},
File = {Hirai1975.pdf:pdf/Hirai1975.pdf:PDF},
Owner = {seyfried},
Timestamp = {2012.10.26}
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