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Incorporating Cellular Automaton based Microscopic Pedestrian Simulation and Genetic Algorithm for Spatial Layout Design Optimization

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 481))

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Abstract

Autonomous spatial layout design had become the prominent applications for early planning process for a space arrangement. The available spatial layout design applications had focused on the structural and functional demands for a trendy, cultural influences and scalable spatial design. The previous research on the autonomous spatial layout design had proved that the Genetic Algorithm (GA) with full-fledged of operators are able to design an optimal spatial layout that is scalable for the space utilization. However, in these recent years, due to many occurrences of emergency incidents, the security assurance of the pedestrian to evacuate from the spatial layout during panic situation had become the main focus in designing a spatial layout. Hence, this research had proposed the pedestrian movement simulation using Cellular Automata (CA) with the Moore Neighborhood transition movement direction as the objective function for optimizing the GA operators based spatial layout design. The results have shown that the CA based pedestrian movement simulation was able to optimize the GA operators based spatial layout design in designing a feasible and scalable space arrangement with low-risk of pedestrian casualties.

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Acknowledgement

Research experiment reported here is pursued under the Fundamental Research Grant Scheme (FRGS) by Ministry of Education Malaysia for “Enhancing Genetic Algorithm for Spatial Layout Design Optimization with Pedestrian Simulation in a Panic Situation” [203.PKOMP.6711534], Research University Grant (RUI) by Universiti Sains Malaysia for “Bio-Inspired Optimization Algorithm for Spatial Layout Design of Cul-de-sac Area using Microscopic Pedestrian Movement in a Panic Situation” [1001.PKOMP.8014073] and Bridging Grant by Universiti Sains Malaysia for “Pedestrian Simulation Model for Clogging Detection and Survival Prediction in a Fire Spreading Situation” [304.PKOMP.6316019]. The preliminary study of this research is supported under the Short Term Grant Scheme by Universiti Sains Malaysia for “Pedestrian Simulator and Heuristic Search Methods for Spatial Layout Design” [304.PKOMP.6313169].

Author information

Authors and Affiliations

  1. School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia

    Najihah Ibrahim & Fadratul Hafinaz Hassan

  2. School of Housing, Building and Planning, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia

    Safial Aqbar Zakaria

Authors
  1. Najihah Ibrahim
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  2. Fadratul Hafinaz Hassan
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  3. Safial Aqbar Zakaria
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Corresponding author

Correspondence to Najihah Ibrahim .

Editor information

Editors and Affiliations

  1. Knowledge Technology Research Unit, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

    Rayner Alfred

  2. School of Information Science, Security and Networks Area, Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Yuto Lim

  3. Faculty of Computing and Informatics, Universiti Malaysia Sabah Faculty of Computing and Informatics, Kota Kinabalu, Sabah, Malaysia

    Ag Asri Ag Ibrahim

  4. Lincoln University , Christchurch, New Zealand

    Patricia Anthony

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Ibrahim, N., Hassan, F.H., Zakaria, S.A. (2019). Incorporating Cellular Automaton based Microscopic Pedestrian Simulation and Genetic Algorithm for Spatial Layout Design Optimization. In: Alfred, R., Lim, Y., Ibrahim, A., Anthony, P. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 481. Springer, Singapore. https://doi.org/10.1007/978-981-13-2622-6_28

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  • DOI: https://doi.org/10.1007/978-981-13-2622-6_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2621-9

  • Online ISBN: 978-981-13-2622-6

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