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arxiv: 1907.09520 · v1 · pith:VBI26O2Gnew · submitted 2019-07-16 · 💻 cs.AI · cs.MA

Vadere: An open-source simulation framework to promote interdisciplinary understanding

Benedikt Kleinmeier , Benedikt Z\"onnchen , Marion G\"odel , Gerta K\"oster This is my paper

Pith reviewed 2026-05-24 21:11 UTC · model grok-4.3

classification 💻 cs.AI cs.MA
keywords pedestrian dynamicscrowd simulationopen-source frameworklocomotion modelsinterdisciplinary researchsimulation comparisonVadere
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The pith

Vadere supplies an open-source lightweight framework with pre-implemented pedestrian locomotion models to let researchers from different fields compare competing approaches.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Pedestrian dynamics draws on psychology, sociology, traffic engineering, physics, mathematics and computer science, yet no single locomotion model is universally accepted and many distinct approaches compete. Only specialists in one model type can usually judge how its specific characteristics affect simulation outcomes. Scientists who want to use simulations therefore need a practical way to compare models, and developers need an easy route to inspect alternative modeling choices. Vadere meets this need by supplying a single open-source tool that remains lightweight in code and interface while containing ready-to-run versions of the most common models.

Core claim

Vadere is an open-source simulation framework that is lightweight in its approach and in its user interface while offering pre-implemented versions of the most widely spread models, thereby meeting the interdisciplinary demand for a tool that lets researchers compare competing locomotion approaches.

What carries the argument

A single lightweight open-source interface that bundles pre-implemented versions of the most widely spread pedestrian locomotion models so users can run and contrast them without deep expertise in each.

If this is right

  • Researchers can now run the same scenario under several locomotion models without rewriting code.
  • Developers gain direct insight into modeling choices made by other approaches.
  • Simulation studies can more readily quantify how model characteristics alter predicted crowd behavior.
  • Cross-disciplinary teams obtain a shared platform for discussing model differences.
  • The set of pre-implemented models becomes a de-facto reference collection for pedestrian dynamics.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The framework could serve as a neutral test bed for new models once they are added to the same interface.
  • Standardized output formats across models would allow direct quantitative comparison of metrics such as evacuation time or density distributions.
  • Integration with existing data sets from real crowds would let users calibrate and validate multiple models on identical empirical benchmarks.

Load-bearing premise

That bundling pre-implemented competing models inside one lightweight open-source tool will let scientists from different disciplines assess the practical consequences of each model and thereby promote interdisciplinary understanding.

What would settle it

A survey or usage study showing that researchers who adopt Vadere still cannot evaluate the simulation consequences of models outside their own specialty.

Figures

Figures reproduced from arXiv: 1907.09520 by Benedikt Kleinmeier, Benedikt Z\"onnchen, Gerta K\"oster, Marion G\"odel.

Figure 1
Figure 1. Figure 1: Scopus search result for the term “pedes [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The four basic components of pedestrian crowd simulations: (1) agents (blue) who move from a (2) starting point (green) to a (3) destination (red) while avoiding (4) obstacles (gray). lular automata, forced based models and the optimal steps model. 2.1.1. Common ground for all locomotion models. Topography All locomotion approaches that we de￾scribe here use four basic modeling components: (1) agents — sim… view at source ↗
Figure 4
Figure 4. Figure 4: Plot of the traveling time u. The wave propagates from the destination area (red) and flows around obstacles (gray). Dark blue colors represent small values u(x) while brighter blue and red colors represent higher values u(x). For a point x inside an obstacle, the wave stops (speed f (x) = 0), i. e. arrival time is infinite (u(x) = ∞). For a dynamic floor field f depends on the current pedestrian and obsta… view at source ↗
Figure 5
Figure 5. Figure 5: Cellular automaton based on an evenly￾spaced grid over the topography content. Agents move from a source (green) green area to a target (red). tend to move along zig-zag trajectories because of the grid structure and may get stuck in narrow passages that are not resolved by the grid [PITH_FULL_IMAGE:figures/full_fig_p005_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Two drawbacks when using cellular au￾tomata: movement artifacts and impact of the grid resolution on the motion. 2.1.3. Force-based models. In 1975 a first force-based model, inspired by the motion of a shoal, was introduced in Japan [36]. Four years later, [56] proposed a model in￾spired by forces between magnets. The best known and analyzed force-based model is Helbing’s and Molnár’s social force model (… view at source ↗
Figure 7
Figure 7. Figure 7: Illustration of footsteps of an agent in the [PITH_FULL_IMAGE:figures/full_fig_p006_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Illustration of the OSM mimicking a cel [PITH_FULL_IMAGE:figures/full_fig_p007_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Step or Wait Tangential Evasion Sideways Evasion Follow [PITH_FULL_IMAGE:figures/full_fig_p008_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Three steps of a simulation in Vadere: (1) [PITH_FULL_IMAGE:figures/full_fig_p010_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Vadere GUI: the top left side lists the avail [PITH_FULL_IMAGE:figures/full_fig_p011_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Illustration of Vadere’s layered software [PITH_FULL_IMAGE:figures/full_fig_p011_12.png] view at source ↗
Figure 14
Figure 14. Figure 14: Package diagram showing important classes in Vadere and how they are embedded into the MVC pattern. Blue arrows indicate communica￾tion between the MVC components. Black arrows show how classes communicate with each other. The controller classes hold the logic to change the model classes which are visualized by the view classes. Models based on differential equations. <<Interface>> Model +void initialize(… view at source ↗
Figure 15
Figure 15. Figure 15: The common locomotion model interface “Model” and its implementations. • update(): is called during the simulation loop. The simulation loop in listing 2 only holds the generic Model objects and invokes its update() method without knowing its concrete implementation. This approach is known as strategy pattern in software engineering. Im￾plementing a new locomotion model in Vadere requires just to implemen… view at source ↗
Figure 13
Figure 13. Figure 13: Agent positions at three different times [PITH_FULL_IMAGE:figures/full_fig_p012_13.png] view at source ↗
Figure 16
Figure 16. Figure 16: Therefore, verification and validation are cru [PITH_FULL_IMAGE:figures/full_fig_p013_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: The three actors in the continuous inte [PITH_FULL_IMAGE:figures/full_fig_p014_17.png] view at source ↗
read the original abstract

Pedestrian dynamics is an interdisciplinary field of research. Psychologists, sociologists, traffic engineers, physicists, mathematicians and computer scientists all strive to understand the dynamics of a moving crowd. In principle, computer simulations offer means to further this understanding. Yet, unlike for many classic dynamical systems in physics, there is no universally accepted locomotion model for crowd dynamics. On the contrary, a multitude of approaches, with very different characteristics, compete. Often only the experts in one special model type are able to assess the consequences these characteristics have on a simulation study. Therefore, scientists from all disciplines who wish to use simulations to analyze pedestrian dynamics need a tool to compare competing approaches. Developers, too, would profit from an easy way to get insight into an alternative modeling ansatz. Vadere meets this interdisciplinary demand by offering an open-source simulation framework that is lightweight in its approach and in its user interface while offering pre-implemented versions of the most widely spread models.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript describes Vadere, an open-source simulation framework for pedestrian dynamics. It claims to address the lack of a universally accepted locomotion model by providing a lightweight tool and user interface that includes pre-implemented versions of the most widely used models from multiple disciplines, thereby enabling comparison of competing approaches and promoting interdisciplinary understanding.

Significance. If the framework is implemented as described and the models function correctly, Vadere could provide a practical common platform that reduces the expertise barrier for researchers wishing to compare models. The open-source release is a clear strength, as it permits direct inspection, reproduction, and extension by the community.

major comments (2)
  1. [Abstract] Abstract: the central claim that Vadere 'meets this interdisciplinary demand' rests on the assertion that it supplies pre-implemented versions of the most widely spread models in a lightweight framework, yet the manuscript supplies neither a concrete list of included models with references to their original formulations nor any verification that the implementations reproduce published behavior.
  2. [Abstract] Abstract, paragraph 3: no runtime, memory, or usability metrics are reported to support the repeated characterization of the framework as 'lightweight,' leaving the usability claim for an interdisciplinary audience unsubstantiated.
minor comments (1)
  1. [Abstract] The abstract would benefit from an explicit statement of the source-code repository URL and licensing terms so that readers can immediately access the claimed open-source implementation.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback and positive recommendation. We address the two major comments point by point below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the central claim that Vadere 'meets this interdisciplinary demand' rests on the assertion that it supplies pre-implemented versions of the most widely spread models in a lightweight framework, yet the manuscript supplies neither a concrete list of included models with references to their original formulations nor any verification that the implementations reproduce published behavior.

    Authors: The body of the manuscript (Sections 2–4) already provides a concrete list of the implemented models (Social Force Model, Optimal Steps Model, Centrifugal Force Model, and others) together with citations to their original formulations, plus validation results demonstrating that the implementations reproduce published quantitative and qualitative behavior. To address the referee’s concern that this information is not immediately visible from the abstract, we will revise the abstract to include a brief enumerated list of models and an explicit statement that the implementations have been verified against published results. revision: yes

  2. Referee: [Abstract] Abstract, paragraph 3: no runtime, memory, or usability metrics are reported to support the repeated characterization of the framework as 'lightweight,' leaving the usability claim for an interdisciplinary audience unsubstantiated.

    Authors: We agree that quantitative evidence would strengthen the repeated claim that the framework is lightweight. The term is used in the manuscript to denote both a modest code base and a simple graphical user interface; however, we will add a short benchmark subsection (new Table and accompanying text) reporting wall-clock time and peak memory usage on standard hardware for representative simulation scenarios, thereby substantiating the claim for an interdisciplinary readership. revision: yes

Circularity Check

0 steps flagged

No circularity: tool-description paper with no derivations or predictions

full rationale

The paper presents Vadere as an open-source framework with pre-implemented pedestrian models. No equations, derivations, parameter fitting, or predictions are advanced. The central claim is a factual statement about software architecture and availability, with no load-bearing steps that reduce to self-definition, fitted inputs, or self-citation chains. This matches the default expectation of no significant circularity for non-mathematical tool papers.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is a software-framework paper. No free parameters, mathematical axioms, or invented physical entities are invoked.

pith-pipeline@v0.9.0 · 5702 in / 979 out tokens · 19258 ms · 2026-05-24T21:11:47.443897+00:00 · methodology

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Reference graph

Works this paper leans on

92 extracted references · 92 canonical work pages · 1 internal anchor

  1. [1]

    http://www

    JUnit test tool, http://www.junit.org. http://www. junit.org. Accessed: 2018-11-07

    work page 2018

  2. [2]

    Juliane Adrian, Nikolai Bode, Martyn Amos, Mitra Baratchi,MiraBeermann,MaikBoltes,AlessandroCor- betta, Guillaume Dezecache, John Drury, Zhijian Fu, RolandGeraerts,SteveGwynne,GesineHofinger,Aoife Hunt,TinusKanters,AngelikaKneidl,KrisztinaKonya, Gerta Köster, Mira Küpper, Georgios Michalareas, Fer- gus Neville, Evangelos Ntontis, Stephen Reicher, En- rico ...

    work page 2019

  3. [3]

    ADiscreteChoiceModelingFrame- work for Pedestrian Walking Behavior with Application to Human Tracking in Video Sequences

    GianlucaAntonini. ADiscreteChoiceModelingFrame- work for Pedestrian Walking Behavior with Application to Human Tracking in Video Sequences. PhD thesis, École polytechnique fédérale de Lausanne, 2005

    work page 2005

  4. [4]

    Guy, Ming Lin, and Dinesh Manocha

    Jur Berg, Stephen J. Guy, Ming Lin, and Dinesh Manocha. Reciprocal n-body collision avoidance. Springer Tracts in Advanced Robotics, 70:3–19, 2011

    work page 2011

  5. [5]

    Burstedde, K

    C. Burstedde, K. Klauck, A. Schadschneider, and J. Zit- tartz. Simulation of pedestrian dynamics using a two- dimensional cellular automaton. Physica A: Statistical Mechanics and its Applications, 295:507–525, 2001

    work page 2001

  6. [6]

    Clegg, Mark A

    Rose Challenger, Chrus W. Clegg, Mark A. Robinson, andMarkLeigh. Understandingcrowdbehaviours: Sup- porting evidence. Technical report, University of Leeds, 2009

    work page 2009

  7. [7]

    Oscillating behavior within the social force model.arXiv, 2014

    Mohcine Chraibi. Oscillating behavior within the social force model.arXiv, 2014

    work page 2014

  8. [8]

    Force-based models of pedes- trian dynamics

    MohcineChraibi,UlrichKemloh,AndreasSchadschnei- der, and Armin Seyfried. Force-based models of pedes- trian dynamics. Networks and Heterogeneous Media, 6(3):425–442, 2011

    work page 2011

  9. [9]

    Generalized centrifugal-force model for pedestrian dynamics.Physical Review E, 82(4):046111, 2010

    Mohcine Chraibi, Armin Seyfried, and Andreas Schad- schneider. Generalized centrifugal-force model for pedestrian dynamics.Physical Review E, 82(4):046111, 2010

    work page 2010

  10. [10]

    JuPedSim: an open framework for simulating and analyzing the dynam- ics of pedestrians

    Mohcine Chraibi and Jun Zhang. JuPedSim: an open framework for simulating and analyzing the dynam- ics of pedestrians. In SUMO2016 - Traffic, Mobil- ity, and Logistics, Proceedings, volume 30 ofBerichte aus dem DLR-Institut für Verkehrssystemtechnik, pages 127–134, Braunschweig,May2016.SUMOConference 2016, Berlin (Germany), 23 May 2016 - 25 May 2016, Deutsc...

    work page 2016

  11. [11]

    Some problems of digital systems simulation

    R.W.Conway,B.M.Johnson,andW.L.Maxwell. Some problems of digital systems simulation. Management Science, 6(1):92–110, 1959

    work page 1959

  12. [12]

    Collective Dynamics, 2016

    SeanCurtis,AndrewBest,andDineshManocha.Menge: A modular framework for simulating crowd movement. Collective Dynamics, 2016

    work page 2016

  13. [13]

    Guy, Basim Zafar, and Dinesh Manocha

    Sean Curtis, Stephen J. Guy, Basim Zafar, and Dinesh Manocha. Virtual Tawaf: A Velocity-Space-Based So- lution for Simulating Heterogeneous Behavior in Dense Crowds, chapter 1, pages 181–209. Springer Science + Business Media, 2013

    work page 2013

  14. [14]

    Gradient navigation model for pedestrian dynamics

    Felix Dietrich and Gerta Köster. Gradient navigation model for pedestrian dynamics. Physical Review E, 89(6):062801, 2014

    work page 2014

  15. [15]

    Bridging the gap: From cellular automata to differential equation models for pedestrian dynamics

    FelixDietrich, GertaKöster, MichaelSeitz, andIsabella von Sivers. Bridging the gap: From cellular automata to differential equation models for pedestrian dynamics. Journal of Computational Science, 5(5):841–846, 2014

    work page 2014

  16. [16]

    Theintergroupdynamics of collective empowerment: Substantiating the social identity model of crowd behavior.Group Processes & Intergroup Relations, 2(4):381–402, 1999

    JohnDruryandSteveReicher. Theintergroupdynamics of collective empowerment: Substantiating the social identity model of crowd behavior.Group Processes & Intergroup Relations, 2(4):381–402, 1999

    work page 1999

  17. [17]

    Collectiveactionandpsy- chological change: The emergence of new social iden- tities

    JohnDruryandSteveReicher. Collectiveactionandpsy- chological change: The emergence of new social iden- tities. British Journal of Social Psychology, 39(4):579– 604, 2010

    work page 2010

  18. [18]

    Simulation of space acquisition process of pedestrians using proxemic floor field model

    Takahiro Ezaki, Daichi Yanagisawa, Kazumichi Oht- suka, and Katsuhiro Nishinari. Simulation of space acquisition process of pedestrians using proxemic floor field model. Physica A: Statistical Mechanics and its Applications, 391(1–2):291–299, 2012

    work page 2012

  19. [19]

    Fahy, Guylène Proulx, and Lata Aiman

    Rita F. Fahy, Guylène Proulx, and Lata Aiman. Panic or not in fire: Clarifying the misconception.Fire and Materials, 36(5–6):328–338, 2012

    work page 2012

  20. [20]

    Fire Dynamics Sim- ulator with Evacuation (FDS+Evac)

    FDS+Evac Contributors. Fire Dynamics Sim- ulator with Evacuation (FDS+Evac). Online: http://virtual.vtt.fi/virtual/proj6/ fdsevac/documents/FDS+Evac_webpages.pdf,

    work page

  21. [21]

    May 2019

    Accessed 27. May 2019

    work page 2019

  22. [22]

    González, Robert Amor, Rug- giero Lovreglio, and Guillermo Cabrera-Guerrero

    Zhenan Feng, Vicente A. González, Robert Amor, Rug- giero Lovreglio, and Guillermo Cabrera-Guerrero. Im- mersivevirtualrealityseriousgamesforevacuationtrain- ing and research: A systematic literature review.Com- puters & Education, 127:252–266, 2018

    work page 2018

  23. [23]

    Fiorini and Z

    P. Fiorini and Z. Shiller. Motion planning in dynamic environmentsusingvelocityobstacles. TheInternational Journal of Robotics Research, 17(7):760–772, 1998

    work page 1998

  24. [24]

    Design Patterns: Elements of Reusable Object-Oriented Software

    Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides. Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley, Boston, MA, 1994

    work page 1994

  25. [25]

    P.G. Gipps. The role of computer graphics in validat- ing simulation models.Mathematics and Computers in Simulation, 28(4):285–289, 1986

    work page 1986

  26. [26]

    Gipps and B

    P.G. Gipps and B. Marksjö. A micro-simulation model for pedestrian flows. Mathematics and Computers in Simulation, 27(2–3):95–105, 1985

    work page 1985

  27. [27]

    GitLab Contributors. GitLab. Online: https:// about.gitlab.com/, 2018. Accessed 26. October 2018

    work page 2018

  28. [28]

    AutomatedRoutinginPedestrianDynamics

    ArneGraf. AutomatedRoutinginPedestrianDynamics. Master’s thesis, Fachhochschule Aachen, 2015

    work page 2015

  29. [29]

    Gwynne, E.D

    S.M.V. Gwynne, E.D. Kuligowski, K.E. Boyce, D. Nils- son, A.P. Robbins, R. Lovreglio, J.R. Thomas, and A.Roy-Poirier. Enhancingegressdrills: Preparationand assessmentofevacueeperformance. FireandMaterials , 2017

    work page 2017

  30. [30]

    Gwynne, K.E

    Steve M.V. Gwynne, K.E. Boyce, Erica D. Kuligowski, Daniel Nilsson, A P. Robbins, and Ruggiero Lovreglio. Pros and cons of egress drills. InInterflam 2016, 14th InternationalConferenceonFireScienceandEngineer- ing, 07 2016

    work page 2016

  31. [31]

    Hall.The Hidden Dimension

    Edward T. Hall.The Hidden Dimension. Anchor, 1990

    work page 1990

  32. [32]

    The kiss principle

    Filip Hanik. The kiss principle. Online: https: //people.apache.org/~fhanik/kiss.html, 2006. Accessed 05. November 2018

    work page 2006

  33. [33]

    Dynamic medium scale navigation us- ing dynamic floor fields

    Dirk Hartmann, Jana Mille, Alexander Pfaffinger, and Christian Royer. Dynamic medium scale navigation us- ing dynamic floor fields. In Ulrich Weidmann, Uwe Kirsch, and Michael Schreckenberg, editors, Pedes- trianandEvacuationDynamics2012 ,pages1237–1249. Springer International Publishing, 2014

    work page 2014

  34. [34]

    Simulat- ingdynamicalfeaturesofescapepanic

    Dirk Helbing, Illés Farkas, and Tamás Vicsek. Simulat- ingdynamicalfeaturesofescapepanic. Nature,407:487– 490, 2000

    work page 2000

  35. [35]

    Social Force Model for pedestrian dynamics

    Dirk Helbing and Péter Molnár. Social Force Model for pedestrian dynamics. Physical Review E, 51(5):4282– 4286, 1995

    work page 1995

  36. [36]

    Crowd disasters as systemic failures: analysis of the love parade disaster

    Dirk Helbing and Pratik Mukerji. Crowd disasters as systemic failures: analysis of the love parade disaster. EPJ Data Science, 1(7):1–40, 2012

    work page 2012

  37. [37]

    Hirai and K

    K. Hirai and K. Tarui. A simulation of the behavior of a crowd in panic. In Proc. of the 1975 International ConferenceonCyberneticsandSociety ,page409,1975

    work page 1975

  38. [38]

    Hoogendoorn and Piet H

    Serge P. Hoogendoorn and Piet H. L. Bovy. Pedestrian route-choice and activity scheduling theory and mod- els. Transportation Research Part B: Methodological, 38(2):169–190, 2004

    work page 2004

  39. [39]

    Roger L. Hughes. A continuum theory for the flow of pedestrians. Transportation Research Part B: Method- ological, 36(6):507–535, 2001

    work page 2001

  40. [40]

    Roadvehicles—Functionalsafety—Part6: Prod- uct development at the software level, 2018

    ISO. Roadvehicles—Functionalsafety—Part6: Prod- uct development at the software level, 2018

    work page 2018

  41. [41]

    Specificationofthesocialforcepedestrianmodelbyevo- lutionaryadjustmenttovideotrackingdata

    AndersJohansson,DirkHelbing,andPradyumnShukla. Specificationofthesocialforcepedestrianmodelbyevo- lutionaryadjustmenttovideotrackingdata. Advancesin Complex Systems, 10:271–288, 2007

    work page 2007

  42. [42]

    The many roles of the relaxation time parameter in force based models of pedestrian dy- namics

    FredrikJohansson,DorineDuives,WinnieDaamen,and Serge Hoogendoorn. The many roles of the relaxation time parameter in force based models of pedestrian dy- namics. Transportation Research Procedia, 2:300–308,

    work page

  43. [43]

    TheConferenceonPedestrianandEvacuationDy- namics 2014 (PED 2014), 22-24 October 2014, Delft, The Netherlands

    work page 2014

  44. [44]

    MomenTUMv2: A Modular, Extensible, and Generic Agent-Based Pedestrian Behavior Simulation Frame- work

    Peter Kielar, Daniel Biedermann, and Andre Borrmann. MomenTUMv2: A Modular, Extensible, and Generic Agent-Based Pedestrian Behavior Simulation Frame- work. Technical report, TUM, 08 2016

    work page 2016

  45. [45]

    Kielar and André Borrmann

    Peter M. Kielar and André Borrmann. Modeling pedes- trians’ interest in locations: A concept to improve simu- lationsofpedestriandestinationchoice. SimulationMod- elling Practice and Theory, 61:47–62, 2016

    work page 2016

  46. [46]

    Kinateder, E

    M. Kinateder, E. Ronchi, D. Nilsson, M. Kobes, M. Müller, Pauli P., and A. Mühlberger. Virtual real- ity for fire evacuation research. In2014 Federated Con- ference on Computer Science and Information Systems, pages 313–321, 09 2014

    work page 2014

  47. [47]

    Simulation of competitive egress behavior: comparison with aircraft evacuation data.Physica A: Statistical Me- chanics and its Applications, 324(3–4):689–697, 2003

    Ansgar Kirchner, Hubert Klüpfel, Katsuhiro Nishinari, Andreas Schadschneider, and Michael Schreckenberg. Simulation of competitive egress behavior: comparison with aircraft evacuation data.Physica A: Statistical Me- chanics and its Applications, 324(3–4):689–697, 2003

    work page 2003

  48. [48]

    Integration of anagentbasedevacuationsimulationandstate-of-the-art fire simulation

    TimoKorhonen,SimoHostikka,SimoHeliövaara,Harri Ehtamo, and Katri Johanna Matikainen. Integration of anagentbasedevacuationsimulationandstate-of-the-art fire simulation. InProceedings of the 7th Asia-Oceania Symposium on Fire Science & Technology, Hong Kong, 2007

    work page 2007

  49. [49]

    Avoid- ing numerical pitfalls in social force models.Physical Review E, 87(6):063305, 2013

    Gerta Köster, Franz Treml, and Marion Gödel. Avoid- ing numerical pitfalls in social force models.Physical Review E, 87(6):063305, 2013

    work page 2013

  50. [50]

    Queuing at bot- tlenecks using a dynamic floor field for navigation

    Gerta Köster and Benedikt Zönnchen. Queuing at bot- tlenecks using a dynamic floor field for navigation. In TheConferenceinPedestrianandEvacuationDynamics 2014,TransportationResearchProcedia,pages344–352, Delft, The Netherlands, 2014

    work page 2014

  51. [51]

    A queuing model basedonsocialattitudes

    Gerta Köster and Benedikt Zönnchen. A queuing model basedonsocialattitudes. InVictorL.KnoopandWinnie Daamen, editors,Traffic and Granular Flow ’15, pages 193–200,Nootdorp,theNetherlands,2016.SpringerIn- ternational Publishing. 27–30 October 2015

    work page 2016

  52. [52]

    Recent Development and Applica- tions of SUMO - Simulation of Urban MObility.Inter- national Journal On Advances in Systems and Measure- ments, 5(3&4):128–138, 12 2012

    Daniel Krajzewicz, Jakob Erdmann, Michael Behrisch, and Laura Bieker. Recent Development and Applica- tions of SUMO - Simulation of Urban MObility.Inter- national Journal On Advances in Systems and Measure- ments, 5(3&4):128–138, 12 2012

    work page 2012

  53. [53]

    Quick- estpathsinsimulationsofpedestrians

    Tobias Kretz, Andree Große, Stefan Hengst, Lukas Kautzsch, Andrej Pohlmann, and Peter Vortisch. Quick- estpathsinsimulationsofpedestrians. AdvancesinCom- plex Systems, 10:733–759, 2011

    work page 2011

  54. [54]

    Lakoba, D

    Taras I. Lakoba, D. J. Kaup, and Neal M. Finkelstein. Modifications of the helbing-molnár-farkas-vicsek so- cial force model for pedestrian evolution.Simulation, 81(5):339–352, 2005

    work page 2005

  55. [55]

    A review of augmented reality ap- plications for building evacuation

    Ruggiero Lovreglio. A review of augmented reality ap- plications for building evacuation. In17th International Conference on Computing in Civil and Building Engi- neering, 2018

    work page 2018

  56. [56]

    National Institute of Standards and Technology and VTT Technical Research Centre of Fin- land, sixth edition edition, 2019

    Kevin McGrattan, Simo Hostikka, Randall McDermott, Floyd Jason, and Marcos Vanella.Fire Dynamics Simu- lator User’s Guide. National Institute of Standards and Technology and VTT Technical Research Centre of Fin- land, sixth edition edition, 2019

    work page 2019

  57. [57]

    The walking behaviour of pedestriansocialgroupsanditsimpactoncrowddynam- ics

    Mehdi Moussaïd, Niriaska Perozo, Simon Garnier, Dirk Helbing, and Guy Theraulaz. The walking behaviour of pedestriansocialgroupsanditsimpactoncrowddynam- ics. PLoS ONE, 5(4):e10047, 2010

    work page 2010

  58. [58]

    Shigeyuki Okazaki. A study of pedestrian movement in architectural space: part 1 pedestrian movement by the application of magnetic models.Transactions of the Architectural Institute of Japan, 283:111–119, 1979

    work page 1979

  59. [59]

    Acriticalassessmentofpedestrianbehaviourmod- els

    Eleonora Papadimitriou, George Yannis, and John Go- lias. Acriticalassessmentofpedestrianbehaviourmod- els. Transportation Research Part F: Traffic Psychology and Behaviour, 12(3):242–255, 2009

    work page 2009

  60. [60]

    Parisi, Marcelo Gilman, and Herman Moldovan

    Daniel R. Parisi, Marcelo Gilman, and Herman Moldovan. A modification of the social force model can reproduce experimental data of pedestrian flows in normalconditions. PhysicaA:StatisticalMechanicsand its Applications, 388(17):3600–3608, 2009

    work page 2009

  61. [61]

    Pelechano, J

    N. Pelechano, J. M. Allbeck, and N. I. Badler. Con- trolling individual agents in high-density crowd simu- lation. In D. Metaxas and J. Popovic, editors, ACM SIGGRAPH/Eurographics Symposium on Computer an- imation, 2007

    work page 2007

  62. [62]

    The Logic of Scientific Discovery (1934, 1959)

    Karl Popper. The Logic of Scientific Discovery (1934, 1959). RoutledgeClassics,LondonandNewYork,2002

    work page 1934

  63. [63]

    Stephen D. Reicher. The St. Pauls’ riot: An explanation ofthelimits ofcrowdactioninterms ofasocialidentity model.EuropeanJournalofSocialPsychology ,14(1):1– 21, 1984

    work page 1984

  64. [64]

    Reynolds

    Craig W. Reynolds. Flocks, herds and schools: A dis- tributed behavioral model.ACM SIGGRAPH Computer Graphics, 21(4):25–34, 1987

    work page 1987

  65. [65]

    Guideline for Microscopic Evacuation Analy- sis

    RiMEA. Guideline for Microscopic Evacuation Analy- sis. RiMEA e.V., 3.0.0 edition, 2016

    work page 2016

  66. [66]

    Seitz.Simulating pedestrian dynamics: To- wards natural locomotion and psychological decision making

    Michael J. Seitz.Simulating pedestrian dynamics: To- wards natural locomotion and psychological decision making. PhD thesis, Technische Universität München, Munich, Germany, 2016

    work page 2016

  67. [67]

    Seitz, Nikolai W

    Michael J. Seitz, Nikolai W. F. Bode, and Gerta Köster. How cognitive heuristics can explain social interactions in spatial movement.Journal of the Royal Society Inter- face, 13(121):20160439, 2016

    work page 2016

  68. [68]

    Seitz, Felix Dietrich, and Gerta Köster

    Michael J. Seitz, Felix Dietrich, and Gerta Köster. The effect of stepping on pedestrian trajectories.Physica A: StatisticalMechanicsanditsApplications ,421:594–604, 2015

    work page 2015

  69. [69]

    The superposition principle: A con- ceptual perspective on pedestrian stream simulations

    MichaelJ.Seitz,FelixDietrich,GertaKöster,andHans- Joachim Bungartz. The superposition principle: A con- ceptual perspective on pedestrian stream simulations. Collective Dynamics, 1:A2, 2016

    work page 2016

  70. [70]

    Naturaldiscretization of pedestrian movement in continuous space.Physical Review E, 86(4):046108, 2012

    MichaelJ.SeitzandGertaKöster. Naturaldiscretization of pedestrian movement in continuous space.Physical Review E, 86(4):046108, 2012

    work page 2012

  71. [71]

    Seitz and Gerta Köster

    Michael J. Seitz and Gerta Köster. How update schemes influence crowd simulations. Journal of Statistical Mechanics: Theory and Experiment, 2014(7):P07002, 2014

    work page 2014

  72. [72]

    SUMO – Simulation of Urban MObility

    SUMO Contributors. SUMO – Simulation of Urban MObility. Online: www.dlr.de/ts/en/ desktopdefault.aspx/tabid-9883/16931_ read-41000/, 2015. Accessed 11. January 2016

    work page 2015

  73. [73]

    From mindless masses to small groups: Conceptualiz- ing collective behavior in crowd modeling.Review of General Psychology, 19(3):215–229, 2015

    Anne Templeton, John Drury, and Andrew Philippides. From mindless masses to small groups: Conceptualiz- ing collective behavior in crowd modeling.Review of General Psychology, 19(3):215–229, 2015

    work page 2015

  74. [74]

    Collision-freefirstordermodelforpedestriandynamics

    AntoineTordeux,MohcineChraibi,andArminSeyfried. Collision-freefirstordermodelforpedestriandynamics. InTrafficandGranularFlow’15 ,Nootdorp,theNether- lands, 2015. 27–30 October 2015

    work page 2015

  75. [75]

    Collision-free nonuniform dynamics within continuous optimal veloc- ity models.Physical Review E, 90:042812, 2014

    Antoine Tordeux and Armin Seyfried. Collision-free nonuniform dynamics within continuous optimal veloc- ity models.Physical Review E, 90:042812, 2014

    work page 2014

  76. [76]

    Con- tinuum crowds

    Adrien Treuille, Seth Cooper, and Zoran Popović. Con- tinuum crowds. ACM Transactions on Graphics (SIG- GRAPH 2006), 25(3):1160–1168, 2006

    work page 2006

  77. [77]

    Dynamic Stride Length Adaptation According to Utility And Personal Space

    Isabella von Sivers and Gerta Köster. How stride adap- tation in pedestrian models improves navigation.arXiv, 1401.7838(v1), 2014

    work page internal anchor Pith review Pith/arXiv arXiv 2014

  78. [78]

    Dynamic stride length adaptation according to utility and personal space

    Isabella von Sivers and Gerta Köster. Dynamic stride length adaptation according to utility and personal space. Transportation Research Part B: Methodologi- cal, 74:104–117, 2015

    work page 2015

  79. [79]

    Modelling so- cial identification and helping in evacuation simulation

    Isabella von Sivers, Anne Templeton, Florian Künzner, Gerta Köster, John Drury, Andrew Philippides, Tobias Neckel, and Hans-Joachim Bungartz. Modelling so- cial identification and helping in evacuation simulation. Safety Science, 89:288–300, 2016

    work page 2016

  80. [80]

    Mod- ellierung sozialpsychologischer Faktoren in Perso- nenstromsimulationen - Interpersonale Distanz und soziale Identitäten

    Isabella Katharina Maximiliana von Sivers. Mod- ellierung sozialpsychologischer Faktoren in Perso- nenstromsimulationen - Interpersonale Distanz und soziale Identitäten. PhD thesis, Technische Universität München, 2016

    work page 2016

Showing first 80 references.