Comparing pedestrian movement simulation models for a crossing area based on real world data

Dietmar Bauer

doi:10.1007/978-1-4419-9725-8

Comparing pedestrian movement simulation models for a crossing area based on real world data

Dietmar Bauer (Speaker)

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation

Abstract

In this paper two different pedestrian movement simulation models (a model of the social force type and a queuing network model) are compared with respect to their capability to predict individual walking times in a crossing area. Both models are calibrated using a trajectory data set and their relative performance on the estimation data set as well as on a separate validation data set is discussed. The social force type model is found to better predict the walking times as well as space usage in both in- and out-of sample comparison.

Original language	English
Title of host publication	Pedestrian and Evacuation Dynamics
Editors	Richard Peacock, Erica Kuligowski, Jason Averill
Publisher	Springer New York
Pages	547-556
Number of pages	10
ISBN (Print)	978-1-4419-9724-1
DOIs	https://doi.org/10.1007/978-1-4419-9725-8
Publication status	Published - 2011
Event	Pedestrian and Evacuation Dynamics 2010 - Duration: 8 Mar 2010 → 10 Mar 2010

Conference

Conference	Pedestrian and Evacuation Dynamics 2010
Period	8/03/10 → 10/03/10

Research Field

Former Research Field - Mobility Systems

Access to Document

10.1007/978-1-4419-9725-8Licence: Unspecified

Cite this

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title = "Comparing pedestrian movement simulation models for a crossing area based on real world data",

abstract = "In this paper two different pedestrian movement simulation models (a model of the social force type and a queuing network model) are compared with respect to their capability to predict individual walking times in a crossing area. Both models are calibrated using a trajectory data set and their relative performance on the estimation data set as well as on a separate validation data set is discussed. The social force type model is found to better predict the walking times as well as space usage in both in- and out-of sample comparison.",

author = "Dietmar Bauer",

year = "2011",

doi = "10.1007/978-1-4419-9725-8",

language = "English",

isbn = "978-1-4419-9724-1",

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editor = "Richard Peacock and Erica Kuligowski and Jason Averill",

booktitle = "Pedestrian and Evacuation Dynamics",

publisher = "Springer New York",

address = "United States",

note = "Pedestrian and Evacuation Dynamics 2010 ; Conference date: 08-03-2010 Through 10-03-2010",

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PY - 2011

Y1 - 2011

N2 - In this paper two different pedestrian movement simulation models (a model of the social force type and a queuing network model) are compared with respect to their capability to predict individual walking times in a crossing area. Both models are calibrated using a trajectory data set and their relative performance on the estimation data set as well as on a separate validation data set is discussed. The social force type model is found to better predict the walking times as well as space usage in both in- and out-of sample comparison.

AB - In this paper two different pedestrian movement simulation models (a model of the social force type and a queuing network model) are compared with respect to their capability to predict individual walking times in a crossing area. Both models are calibrated using a trajectory data set and their relative performance on the estimation data set as well as on a separate validation data set is discussed. The social force type model is found to better predict the walking times as well as space usage in both in- and out-of sample comparison.

U2 - 10.1007/978-1-4419-9725-8

DO - 10.1007/978-1-4419-9725-8

M3 - Conference Proceedings with Oral Presentation

SN - 978-1-4419-9724-1

SP - 547

EP - 556

BT - Pedestrian and Evacuation Dynamics

PB - Springer New York

T2 - Pedestrian and Evacuation Dynamics 2010

Y2 - 8 March 2010 through 10 March 2010

ER -

Comparing pedestrian movement simulation models for a crossing area based on real world data

Abstract

Conference

Research Field

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