Prediction of pedestrians routes within a built environment in normal conditions

Nasir,M, Lim,CP, Nahavandi,S and Creighton,D 2014, Prediction of pedestrians routes within a built environment in normal conditions, Expert systems with applications, vol. 41, no. 10, pp. 4975-4988, doi: 10.1016/j.eswa.2014.02.034.

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Title Prediction of pedestrians routes within a built environment in normal conditions
Author(s) Nasir,M
Lim,CPORCID iD for Lim,CP
Nahavandi,SORCID iD for Nahavandi,S
Creighton,DORCID iD for Creighton,D
Journal name Expert systems with applications
Volume number 41
Issue number 10
Start page 4975
End page 4988
Total pages 14
Publisher Elsevier
Place of publication Oxford, United Kingdom
Publication date 2014-08
ISSN 0957-4174
Keyword(s) Dynamic programming
Network-based routing
Path prediction
Pedestrian optimum route
Utility optimization
Science & Technology
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Operations Research & Management Science
Computer Science
Summary Modelling and prediction of pedestrian routing behaviours within known built environments has recently attracted the attention of researchers across multiple disciplines, owing to the growing demand on urban resources and requirements for efficient use of public facilities. This study presents an investigation into pedestrians' routing behaviours within an indoor environment under normal, non-panic situations. A network-based method using constrained Delaunay triangulation is adopted, and a utility-based model employing dynamic programming is developed. The main contribution of this study is the formulation of an appropriate utility function that allows an effective application of dynamic programming to predict a series of consecutive waypoints within a built environment. The aim is to generate accurate sequence waypoints for the pedestrian walking path using only structural definitions of the environment as defined in a standard CAD format. The simulation results are benchmarked against those from the A* algorithm, and the outcome positively indicates the usefulness of the proposed method in predicting pedestrians' route selection activities. © 2014 Elsevier Ltd. All rights reserved.
Language eng
DOI 10.1016/j.eswa.2014.02.034
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
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
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