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Pythagorean Theorem for Shortest Distance in CA Based Pedestrian Simulation: A Case Study on the Closed Area

  • Najihah IbrahimEmail author
  • Fadratul Hafinaz Hassan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 547)

Abstract

Cellular Automata (CA) model approach has become a well-known approach in demonstrating the microscopic movement of pedestrian for path finding and navigation to reach point of interest. One of the features in the CA movement model is to find the shortest path distance that will navigate the pedestrian movement towards point of interest in the fastest of time. Nowadays, there are many path navigation systems that were constructed by using the pre-defined movement simulation based on the static obstacles’ layout. However, the pre-defined movement simulation is not able to highlight the near-realistic movement of the pedestrian due to the dynamic obstacle’s avoidance and physical collision that will affect the pedestrian movement direction’s selection and safety. Hence, this research has simulated the enhanced transition direction of the CA based pedestrian movement using the optimal Moore Neighborhood transition method and has proposed the Pythagorean Theorem for the shortest distance path finding for assisting the pedestrian direction selection. This research has proven that the enhanced movement transition direction and the implementation of Pythagorean Theorem able to construct an intelligent and near-realistic pedestrian simulation that able to evacuate in fastest time (<25 s) from the selected spatial layout design compared to the transition method based pedestrian movement simulation.

Keywords

Pythagorean theorem Shortest distance Cellular automata Moore neighborhood transition Pedestrian movement 

Notes

Acknowledgements

Research experiment is pursued under the FRGS grant by Ministry of Education Malaysia [203.PKOMP.6711534], Bridging Grant by Universiti Sains Malaysia [304.PKOMP.6316019] and Research University Grant by Universiti Sains Malaysia [1001.PKOMP.8014073].

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Computer SciencesUniversiti Sains MalaysiaPulau PinangMalaysia

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