2016
von Sivers, Isabella Katharina Maximiliana; Templeton, Anne; Künzner, Florian; Köster, Gerta; Drury, John; andNeckel, Tobias Philippides Andrew; Bungartz, Hans-Joachim
Modelling social identification and helping in evacuation simulation Journal Article
In: Safety Science, vol. 89, pp. 288–300, 2016, ISSN: 0925-7535.
@article{sivers-2016d-cdyn,
title = {Modelling social identification and helping in evacuation simulation},
author = {Isabella Katharina Maximiliana von Sivers and Anne Templeton and Florian Künzner and Gerta Köster and John Drury and Tobias Philippides Andrew andNeckel and Hans-Joachim Bungartz},
doi = {10.1016/j.ssci.2016.07.001},
issn = {0925-7535},
year = {2016},
date = {2016-01-01},
journal = {Safety Science},
volume = {89},
pages = {288--300},
abstract = {Social scientists have criticised computer models of pedestrian streams for their treatment of psychological
crowds as mere aggregations of individuals. Indeed most models for evacuation dynamics use analogies
from physics where pedestrians are considered as particles. Although this ensures that the results of
the simulation match important physical phenomena, such as the deceleration of the crowd with
increasing density, social phenomena such as group processes are ignored. In particular, people in a
crowd have social identities and share those social identities with the others in the crowd. The process
of self categorisation determines norms within the crowd and influences how people will behave in
evacuation situations. We formulate the application of social identity in pedestrian simulation
algorithmically. The goal is to examine whether it is possible to carry over the psychological model to
computer models of pedestrian motion so that simulation results correspond to observations from crowd
psychology. That is, we quantify and formalise empirical research on and verbal descriptions of the effect
of group identity on behaviour. We use uncertainty quantification to analyse the model's behaviour when
we vary crucial model parameters. In this first approach we restrict ourselves to a specific scenario that
was thoroughly investigated by crowd psychologists and where some quantitative data is available: the
bombing and subsequent evacuation of a London underground tube carriage on July 7th 2005.},
keywords = {},
pubstate = {published},
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}
Social scientists have criticised computer models of pedestrian streams for their treatment of psychological
crowds as mere aggregations of individuals. Indeed most models for evacuation dynamics use analogies
from physics where pedestrians are considered as particles. Although this ensures that the results of
the simulation match important physical phenomena, such as the deceleration of the crowd with
increasing density, social phenomena such as group processes are ignored. In particular, people in a
crowd have social identities and share those social identities with the others in the crowd. The process
of self categorisation determines norms within the crowd and influences how people will behave in
evacuation situations. We formulate the application of social identity in pedestrian simulation
algorithmically. The goal is to examine whether it is possible to carry over the psychological model to
computer models of pedestrian motion so that simulation results correspond to observations from crowd
psychology. That is, we quantify and formalise empirical research on and verbal descriptions of the effect
of group identity on behaviour. We use uncertainty quantification to analyse the model's behaviour when
we vary crucial model parameters. In this first approach we restrict ourselves to a specific scenario that
was thoroughly investigated by crowd psychologists and where some quantitative data is available: the
bombing and subsequent evacuation of a London underground tube carriage on July 7th 2005.
crowds as mere aggregations of individuals. Indeed most models for evacuation dynamics use analogies
from physics where pedestrians are considered as particles. Although this ensures that the results of
the simulation match important physical phenomena, such as the deceleration of the crowd with
increasing density, social phenomena such as group processes are ignored. In particular, people in a
crowd have social identities and share those social identities with the others in the crowd. The process
of self categorisation determines norms within the crowd and influences how people will behave in
evacuation situations. We formulate the application of social identity in pedestrian simulation
algorithmically. The goal is to examine whether it is possible to carry over the psychological model to
computer models of pedestrian motion so that simulation results correspond to observations from crowd
psychology. That is, we quantify and formalise empirical research on and verbal descriptions of the effect
of group identity on behaviour. We use uncertainty quantification to analyse the model's behaviour when
we vary crucial model parameters. In this first approach we restrict ourselves to a specific scenario that
was thoroughly investigated by crowd psychologists and where some quantitative data is available: the
bombing and subsequent evacuation of a London underground tube carriage on July 7th 2005.
Seitz, Michael J; Bode, Nikolai W F; Köster, Gerta
How cognitive heuristics can explain social interactions in spatial movement Journal Article
In: Journal of the Royal Society Interface, vol. 13, no. 121, pp. 20160439, 2016.
@article{seitz-2016c-cdyn,
title = {How cognitive heuristics can explain social interactions in spatial movement},
author = {Michael J Seitz and Nikolai W F Bode and Gerta Köster},
doi = {10.1098/rsif.2016.0439},
year = {2016},
date = {2016-01-01},
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Seitz, Michael J; Seer, Stefan; Klettner, Silvia; Köster, Gerta; Handel, Oliver
How do we wait? Fundamentals, characteristics, and modeling implications Proceedings Article
In: Knoop, Victor L; Daamen, Winnie (Ed.): Traffic and Granular Flow '15, pp. 217-224, Springer International Publishing, Nootdorp, the Netherlands, 2016, (27--30 October 2015).
@inproceedings{seitz-2015b-cdyn,
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von Sivers, Isabella; Templeton, Anne; Künzner, Florian; Köster, Gerta; Drury, John; Philippides, Andrew; Neckel, Tobias; Bungartz, Hans-Joachim
Modelling social identification and helping in evacuation simulation Journal Article
In: arXiv, vol. 1602.00805, no. v1, 2016, (submitted to Safety Science).
@article{sivers-2016-cdyn,
title = {Modelling social identification and helping in evacuation simulation},
author = {Isabella von Sivers and Anne Templeton and Florian Künzner and Gerta Köster and John Drury and Andrew Philippides and Tobias Neckel and Hans-Joachim Bungartz},
url = {http://arxiv.org/abs/1602.00805},
year = {2016},
date = {2016-01-01},
journal = {arXiv},
volume = {1602.00805},
number = {v1},
abstract = {Social scientists have criticised computer models of pedestrian streams for
their treatment of psychological crowds as mere aggregations of individuals.
Indeed most models for evacuation dynamics use analogies from physics where
pedestrians are considered as particles. Although this ensures that the results
of the simulation match important physical phenomena, such as the deceleration
of the crowd with increasing density, social phenomena such as group processes
are ignored. In particular, people in a crowd have social identities and share
those social identities with the others in the crowd. The process of self
categorisation determines norms within the crowd and influences how people will
behave in evacuation situations. We formulate the application of social
identity in pedestrian simulation algorithmically. The goal is to examine
whether it is possible to carry over the psychological model to computer models
of pedestrian motion so that simulation results correspond to observations from
crowd psychology. That is, we quantify and formalise empirical research on and
verbal descriptions of the effect of group identity on behaviour. We use
uncertainty quantification to analyse the model's behaviour when we vary
crucial model parameters. In this first approach we restrict ourselves to a
specific scenario that was thoroughly investigated by crowd psychologists and
where some quantitative data is available: the bombing and subsequent
evacuation of a London underground tube carriage on July 7th 2005.},
note = {submitted to Safety Science},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Social scientists have criticised computer models of pedestrian streams for
their treatment of psychological crowds as mere aggregations of individuals.
Indeed most models for evacuation dynamics use analogies from physics where
pedestrians are considered as particles. Although this ensures that the results
of the simulation match important physical phenomena, such as the deceleration
of the crowd with increasing density, social phenomena such as group processes
are ignored. In particular, people in a crowd have social identities and share
those social identities with the others in the crowd. The process of self
categorisation determines norms within the crowd and influences how people will
behave in evacuation situations. We formulate the application of social
identity in pedestrian simulation algorithmically. The goal is to examine
whether it is possible to carry over the psychological model to computer models
of pedestrian motion so that simulation results correspond to observations from
crowd psychology. That is, we quantify and formalise empirical research on and
verbal descriptions of the effect of group identity on behaviour. We use
uncertainty quantification to analyse the model's behaviour when we vary
crucial model parameters. In this first approach we restrict ourselves to a
specific scenario that was thoroughly investigated by crowd psychologists and
where some quantitative data is available: the bombing and subsequent
evacuation of a London underground tube carriage on July 7th 2005.
their treatment of psychological crowds as mere aggregations of individuals.
Indeed most models for evacuation dynamics use analogies from physics where
pedestrians are considered as particles. Although this ensures that the results
of the simulation match important physical phenomena, such as the deceleration
of the crowd with increasing density, social phenomena such as group processes
are ignored. In particular, people in a crowd have social identities and share
those social identities with the others in the crowd. The process of self
categorisation determines norms within the crowd and influences how people will
behave in evacuation situations. We formulate the application of social
identity in pedestrian simulation algorithmically. The goal is to examine
whether it is possible to carry over the psychological model to computer models
of pedestrian motion so that simulation results correspond to observations from
crowd psychology. That is, we quantify and formalise empirical research on and
verbal descriptions of the effect of group identity on behaviour. We use
uncertainty quantification to analyse the model's behaviour when we vary
crucial model parameters. In this first approach we restrict ourselves to a
specific scenario that was thoroughly investigated by crowd psychologists and
where some quantitative data is available: the bombing and subsequent
evacuation of a London underground tube carriage on July 7th 2005.
von Sivers, Isabella; Seitz, Michael Jakob; Köster, Gerta
How do people search: a modelling perspective Proceedings Article
In: Parallel Processing and Applied Mathematics, 11th International Conference, PPAM 2015, Krakow, Poland, September 6-9, 2015. Revised Selected Papers, Part II, pp. 487–496, Springer, 2016.
@inproceedings{sivers-2015b-cdyn,
title = {How do people search: a modelling perspective},
author = {Isabella von Sivers and Michael Jakob Seitz and Gerta Köster},
doi = {10.1007/978-3-319-32152-3_45},
year = {2016},
date = {2016-01-01},
booktitle = {Parallel Processing and Applied Mathematics, 11th International Conference, PPAM 2015, Krakow, Poland, September 6-9, 2015. Revised Selected Papers, Part II},
volume = {9574},
pages = {487--496},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
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pubstate = {published},
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von Sivers, Isabella; Köster, Gerta; Kleinmeier, Benedikt
Modelling stride length and stepping frequency Proceedings Article
In: Knoop, Victor L; Daamen, Winnie (Ed.): Traffic and Granular Flow '15, pp. 113–120, Springer International Publishing, 2016, (27--30 October 2015).
@inproceedings{sivers-2015c-cdyn,
title = {Modelling stride length and stepping frequency},
author = {Isabella von Sivers and Gerta Köster and Benedikt Kleinmeier},
editor = {Victor L Knoop and Winnie Daamen},
doi = {10.1007/978-3-319-33482-0},
year = {2016},
date = {2016-01-01},
booktitle = {Traffic and Granular Flow '15},
pages = {113--120},
publisher = {Springer International Publishing},
note = {27--30 October 2015},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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Dietrich, Felix; Albrecht, Florian; Köster, Gerta
Surrogate Models for Bottleneck Scenarios Conference
Proceedings of the 8th International Conference on Pedestrian and Evacuation Dynamics (PED2016), Hefei, China, 2016.
@conference{dietrich-2016-cdyn,
title = {Surrogate Models for Bottleneck Scenarios},
author = {Felix Dietrich and Florian Albrecht and Gerta Köster},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 8th International Conference on Pedestrian and Evacuation Dynamics (PED2016)},
address = {Hefei, China},
keywords = {},
pubstate = {published},
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Dietrich, Felix; Köster, Gerta; Bungartz, Hans-Joachim
Numerical Model Construction with Closed Observables Journal Article
In: SIAM Journal on Applied Dynamical Systems, vol. 15, no. 4, pp. 2078–2108, 2016.
@article{dietrich-2016b-cdyn,
title = {Numerical Model Construction with Closed Observables},
author = {Felix Dietrich and Gerta Köster and Hans-Joachim Bungartz},
doi = {10.1137/15M1043613},
year = {2016},
date = {2016-01-01},
journal = {SIAM Journal on Applied Dynamical Systems},
volume = {15},
number = {4},
pages = {2078--2108},
keywords = {},
pubstate = {published},
tppubtype = {article}
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Köster, Gerta; Sesser, Florian; Kneidl, Angelika
Reducing Cognitive Overhead: Evacuation of a Beer Tent in Virtual Reality Conference
Proceedings of the 8th International Conference on Pedestrian and Evacuation Dynamics (PED2016), Hefei, China, 2016.
@conference{koster-2016-cdyn,
title = {Reducing Cognitive Overhead: Evacuation of a Beer Tent in Virtual Reality},
author = {Gerta Köster and Florian Sesser and Angelika Kneidl},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 8th International Conference on Pedestrian and Evacuation Dynamics (PED2016)},
address = {Hefei, China},
keywords = {},
pubstate = {published},
tppubtype = {conference}
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von Sivers, Isabella; Künzner, Florian; Köster, Gerta
Pedestrian Evacuation Simulation with Separated Families Conference
Proceedings of the 8th International Conference on Pedestrian and Evacuation Dynamics (PED2016), Hefei, China, 2016.
@conference{sivers-2016c-cdyn,
title = {Pedestrian Evacuation Simulation with Separated Families},
author = {Isabella von Sivers and Florian Künzner and Gerta Köster},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 8th International Conference on Pedestrian and Evacuation Dynamics (PED2016)},
address = {Hefei, China},
abstract = {Crowds are composed of both single persons and small to large groups of people. A family can
be considered a special group within a crowd because of its unique behaviour. While families may become
separated at the beginning of an emergency situation, they tend to evacuate the situation together. That is,
according to ndings in psychology, family members search for each other and evacuate once they are reunited.
However, it is not exceptional that families are separated at the beginning of an emergency. According to
psychological ndings, family members search for each other and evacuate after they are reunited. The model
presented in this paper transfers these ndings into pedestrian evacuation simulation. We describe how we
model the behaviour of separated families and qualitatively validate the model. With the help of uncertainty
quantication and Sobol indices, we analyse the impact of three uncertain parameters of the model on the
evacuation times: the percentage of family members in the crowd, the speed at which parents search for their
children, and the speed of the children evacuating with their parents. As a result, we can show that it is vital
to consider families in evacuation simulation to better estimate of the evacuation times.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Crowds are composed of both single persons and small to large groups of people. A family can
be considered a special group within a crowd because of its unique behaviour. While families may become
separated at the beginning of an emergency situation, they tend to evacuate the situation together. That is,
according to ndings in psychology, family members search for each other and evacuate once they are reunited.
However, it is not exceptional that families are separated at the beginning of an emergency. According to
psychological ndings, family members search for each other and evacuate after they are reunited. The model
presented in this paper transfers these ndings into pedestrian evacuation simulation. We describe how we
model the behaviour of separated families and qualitatively validate the model. With the help of uncertainty
quantication and Sobol indices, we analyse the impact of three uncertain parameters of the model on the
evacuation times: the percentage of family members in the crowd, the speed at which parents search for their
children, and the speed of the children evacuating with their parents. As a result, we can show that it is vital
to consider families in evacuation simulation to better estimate of the evacuation times.
be considered a special group within a crowd because of its unique behaviour. While families may become
separated at the beginning of an emergency situation, they tend to evacuate the situation together. That is,
according to ndings in psychology, family members search for each other and evacuate once they are reunited.
However, it is not exceptional that families are separated at the beginning of an emergency. According to
psychological ndings, family members search for each other and evacuate after they are reunited. The model
presented in this paper transfers these ndings into pedestrian evacuation simulation. We describe how we
model the behaviour of separated families and qualitatively validate the model. With the help of uncertainty
quantication and Sobol indices, we analyse the impact of three uncertain parameters of the model on the
evacuation times: the percentage of family members in the crowd, the speed at which parents search for their
children, and the speed of the children evacuating with their parents. As a result, we can show that it is vital
to consider families in evacuation simulation to better estimate of the evacuation times.
2015
Torchiani, Carolin; Seitz, Michael J; Willems, David; Ruzika, Stefan; Köster, Gerta
no. TUM-I1517, 2015.
@techreport{torchiani-2015-cdyn,
title = {Fahrgastwechselzeiten von Shuttlebussen: Feldbeobachtung, statistische Auswertung und weitere Verwendung der Daten (Beobachtung vom 06.12.2014 in Kaiserslautern)},
author = {Carolin Torchiani and Michael J Seitz and David Willems and Stefan Ruzika and Gerta Köster},
url = {http://mediatum.ub.tum.de/?id=1249728},
year = {2015},
date = {2015-01-01},
number = {TUM-I1517},
school = {Technische Universität München},
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von Sivers, Isabella; Köster, Gerta
Dynamic Stride Length Adaptation According to Utility And Personal Space Journal Article
In: Transportation Research Part B: Methodological, vol. 74, pp. 104–117, 2015.
@article{sivers-2015-cdyn,
title = {Dynamic Stride Length Adaptation According to Utility And Personal Space},
author = {Isabella von Sivers and Gerta Köster},
doi = {10.1016/j.trb.2015.01.009},
year = {2015},
date = {2015-01-01},
journal = {Transportation Research Part B: Methodological},
volume = {74},
pages = {104--117},
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von Sivers, Isabella; Köster, Gerta
Dynamic Stride Length Adaptation According to Utility And Personal Space Journal Article
In: Transportation Research Part B: Methodological, vol. 74, pp. 104–117, 2015.
@article{sivers-2015,
title = {Dynamic Stride Length Adaptation According to Utility And Personal Space},
author = {Isabella von Sivers and Gerta Köster},
doi = {10.1016/j.trb.2015.01.009},
year = {2015},
date = {2015-01-01},
journal = {Transportation Research Part B: Methodological},
volume = {74},
pages = {104--117},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2012
Davidich, Maria; Köster, Gerta
Towards automatic and robust adjustment of human behavioral parameters in a pedestrian stream model to measured data Journal Article
In: Safety Science, vol. 50, no. 5, pp. 1253–1260, 2012, ISSN: 0925-7535.
@article{davidich-2012-cdyn,
title = {Towards automatic and robust adjustment of human behavioral parameters in a pedestrian stream model to measured data},
author = {Maria Davidich and Gerta Köster},
doi = {10.1016/j.ssci.2011.12.024},
issn = {0925-7535},
year = {2012},
date = {2012-01-01},
journal = {Safety Science},
volume = {50},
number = {5},
pages = {1253--1260},
abstract = {People die or get injured at mass events when the crowd gets out of control. Urbanization and the increasing popularity of mass events, from soccer games to religious celebrations, enforce this trend. Thus, there is a strong need to better control crowd behavior. Here, simulation of pedestrian streams can be very helpful: Simulations allow a user to run through a number of scenarios in a critical situation and thereby to investigate adequate measures to improve security. In order to make realistic, reliable predictions, a model must be able to reproduce the data known from experiments quantitatively. Therefore, automatic and fast calibration methods are needed that can easily adapt model parameters to different scenarios. Also, the model must be robust. Small changes or measurement errors in the crucial input parameters must not lead to disproportionally large changes in the simulation outcome and thus potentially useless results. In this paper we present two methods to automatically calibrate pedestrian simulations to the socio-cultural parameters captured through measured fundamental diagrams. We then introduce a concept of robustness to compare the two methods. In particular, we propose a quantitative estimation of parameter quality and a method of parameter selection based on a criterion for robustness. We discuss the results of our test scenarios and, based on our experience, propose further steps.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
People die or get injured at mass events when the crowd gets out of control. Urbanization and the increasing popularity of mass events, from soccer games to religious celebrations, enforce this trend. Thus, there is a strong need to better control crowd behavior. Here, simulation of pedestrian streams can be very helpful: Simulations allow a user to run through a number of scenarios in a critical situation and thereby to investigate adequate measures to improve security. In order to make realistic, reliable predictions, a model must be able to reproduce the data known from experiments quantitatively. Therefore, automatic and fast calibration methods are needed that can easily adapt model parameters to different scenarios. Also, the model must be robust. Small changes or measurement errors in the crucial input parameters must not lead to disproportionally large changes in the simulation outcome and thus potentially useless results. In this paper we present two methods to automatically calibrate pedestrian simulations to the socio-cultural parameters captured through measured fundamental diagrams. We then introduce a concept of robustness to compare the two methods. In particular, we propose a quantitative estimation of parameter quality and a method of parameter selection based on a criterion for robustness. We discuss the results of our test scenarios and, based on our experience, propose further steps.