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. Attached Files Name Description MIMEType Size Downloads Title A genetic fuzzy system to model pedestrian walking path in a built environment Author(s) Nasir,M Lim,CP orcid.org/0000-0003-4191-9083 Nahavandi,S Creighton,D 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 Related Links Link Description Connect to Elements publication management system Go to link with your DU access privileges   Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 24 Feb 2015, 16:07:48 EST Tue, 24 Feb 2015, 16:08:32 EST Wed, 25 Feb 2015, 04:01:57 EST Wed, 25 Feb 2015, 05:07:28 EST Wed, 25 Feb 2015, 09:00:09 EST Wed, 25 Feb 2015, 09:04:35 EST Wed, 25 Feb 2015, 09:09:34 EST Wed, 20 May 2015, 16:14:21 EST Thu, 21 May 2015, 08:09:33 EST Filtered Full Citation counts:   Cited 9 times in TR Web of Science Cited 11 times in Scopus Search Google Scholar Access Statistics: 243 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Tue, 24 Feb 2015, 16:08:32 EST

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