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A genetic fuzzy system to model pedestrian walking path in a built environment

Nasir,M, Lim,CP, Nahavandi,S and Creighton,D 2014, A genetic fuzzy system to model pedestrian walking path in a built environment, Simulation Modelling Practice and Theory, vol. 45, pp. 18-34, doi: 10.1016/j.simpat.2014.03.002.

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Title A genetic fuzzy system to model pedestrian walking path in a built environment
Author(s) Nasir,M
Lim,CPORCID iD for Lim,CP orcid.org/0000-0003-4191-9083
Nahavandi,S
Creighton,DORCID iD for Creighton,D orcid.org/0000-0002-9217-1231
Journal name Simulation Modelling Practice and Theory
Volume number 45
Start page 18
End page 34
Total pages 17
Publisher Elsevier
Place of publication Amsterdam , Netherlands
Publication date 2014-06
ISSN 1569-190X
Keyword(s) Genetic fuzzy system
Pedestrian behaviour modelling
Pedestrian environmental perception
Walking trajectory prediction
Science & Technology
Technology
Computer Science, Interdisciplinary Applications
Computer Science, Software Engineering
Computer Science
ALGORITHMS
CONTROLLERS
FRAMEWORK
SELECTION
DYNAMICS
BEHAVIOR
DESIGN
Summary A study on the pedestrian's steering behaviour through a built environment in normal circumstances is presented in this paper. The study focuses on the relationship between the environment and the pedestrian's walking trajectory. Owing to the ambiguity and vagueness of the relationship between the pedestrians and the surrounding environment, a genetic fuzzy system is proposed for modelling and simulation of the pedestrian's walking trajectory confronting the environmental stimuli. We apply the genetic algorithm to search for the optimum membership function parameters of the fuzzy model. The proposed system receives the pedestrian's perceived stimuli from the environment as the inputs, and provides the angular change of direction in each step as the output. The environmental stimuli are quantified using the Helbing social force model. Attractive and repulsive forces within the environment represent various environmental stimuli that influence the pedestrian's walking trajectory at each point of the space. To evaluate the effectiveness of the proposed model, three experiments are conducted. The first experimental results are validated against real walking trajectories of participants within a corridor. The second and third experimental results are validated against simulated walking trajectories collected from the AnyLogic® software. Analysis and statistical measurement of the results indicate that the genetic fuzzy system with optimised membership functions produces more accurate and stable prediction of heterogeneous pedestrians' walking trajectories than those from the original fuzzy model. © 2014 Elsevier B.V. All rights reserved.
Language eng
DOI 10.1016/j.simpat.2014.03.002
Field of Research 091302 Automation and Control Engineering
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30069995

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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