2016
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},
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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.
Seitz, Michael J; Dietrich, Felix; Köster, Gerta; Bungartz, Hans-Joachim
The superposition principle: A conceptual perspective on pedestrian stream simulations Journal Article
In: Collective Dynamics, vol. 1, pp. A2, 2016.
@article{seitz-2016b-cdyn,
title = {The superposition principle: A conceptual perspective on pedestrian stream simulations},
author = {Michael J Seitz and Felix Dietrich and Gerta Köster and Hans-Joachim Bungartz},
doi = {10.17815/CD.2016.2},
year = {2016},
date = {2016-01-01},
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Seitz, Michael J; Dietrich, Felix; Köster, Gerta; Bungartz, Hans-Joachim
The superposition principle: A conceptual perspective on pedestrian stream simulations Journal Article
In: Collective Dynamics, vol. 1, pp. A2, 2016.
@article{seitz-2016b,
title = {The superposition principle: A conceptual perspective on pedestrian stream simulations},
author = {Michael J Seitz and Felix Dietrich and Gerta Köster and Hans-Joachim Bungartz},
doi = {10.17815/CD.2016.2},
year = {2016},
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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: Safety Science, vol. 89, pp. 288–300, 2016, ISSN: 0925-7535.
@article{sivers-2016d,
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},
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},
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.
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,
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},
journal = {Journal of the Royal Society Interface},
volume = {13},
number = {121},
pages = {20160439},
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pubstate = {published},
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Köster, Gerta; Zönnchen, Benedikt
A Queuing Model Based On Social Attitudes Proceedings Article
In: Knoop, Victor L; Daamen, Winnie (Ed.): Traffic and Granular Flow '15, pp. 193–200, Springer International Publishing, Nootdorp, the Netherlands, 2016, (27--30 October 2015).
@inproceedings{koster-2015b-cdyn,
title = {A Queuing Model Based On Social Attitudes},
author = {Gerta Köster and Benedikt Zönnchen},
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 = {193--200},
publisher = {Springer International Publishing},
address = {Nootdorp, the Netherlands},
abstract = {Modern pedestrian simulation models have to deal with queuing to obtain
realistic results. Queues control the number of pedestrians entering or leaving an
area and, through this, the number of pedestrians inside that area. Furthermore they
impede passing pedestrians. But how do humans decide on a queuing strategy? And
how does this effect the form of the emerging queue? Based on dynamic floor fields
for navigation and a simple heuristic decision mechanism we present a computer
model that is able to capture different queuing patterns that we observe in every day
life. For this we assume that there are two basic attitudes, aggressive competition
and cooperative getting in line. Pedestrians can switch between these strategies.},
note = {27--30 October 2015},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Modern pedestrian simulation models have to deal with queuing to obtain
realistic results. Queues control the number of pedestrians entering or leaving an
area and, through this, the number of pedestrians inside that area. Furthermore they
impede passing pedestrians. But how do humans decide on a queuing strategy? And
how does this effect the form of the emerging queue? Based on dynamic floor fields
for navigation and a simple heuristic decision mechanism we present a computer
model that is able to capture different queuing patterns that we observe in every day
life. For this we assume that there are two basic attitudes, aggressive competition
and cooperative getting in line. Pedestrians can switch between these strategies.
realistic results. Queues control the number of pedestrians entering or leaving an
area and, through this, the number of pedestrians inside that area. Furthermore they
impede passing pedestrians. But how do humans decide on a queuing strategy? And
how does this effect the form of the emerging queue? Based on dynamic floor fields
for navigation and a simple heuristic decision mechanism we present a computer
model that is able to capture different queuing patterns that we observe in every day
life. For this we assume that there are two basic attitudes, aggressive competition
and cooperative getting in line. Pedestrians can switch between these strategies.
Seitz, Michael J
Simulating pedestrian dynamics PhD Thesis
Technische Universität München, 2016.
@phdthesis{seitz-2016b,
title = {Simulating pedestrian dynamics},
author = {Michael J Seitz},
year = {2016},
date = {2016-01-01},
address = {München},
school = {Technische Universität München},
keywords = {},
pubstate = {published},
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Modellierung sozialpsychologischer Faktoren in Personenstromsimulationen PhD Thesis
Technische Universität München, 2016.
@phdthesis{,
title = {Modellierung sozialpsychologischer Faktoren in Personenstromsimulationen},
year = {2016},
date = {2016-01-01},
address = {München},
school = {Technische Universität München},
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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 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},
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.
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},
journal = {Journal of the Royal Society Interface},
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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,
title = {How do we wait? Fundamentals, characteristics, and modeling implications},
author = {Michael J Seitz and Stefan Seer and Silvia Klettner and Gerta Köster and Oliver Handel},
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},
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publisher = {Springer International Publishing},
address = {Nootdorp, the Netherlands},
note = {27--30 October 2015},
keywords = {},
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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},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
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 = {},
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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},
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.