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

Ibrahim, Najihah; Hassan, Fadratul Hafinaz

doi:10.1007/978-981-13-6447-1_9

Cited by 1 publication

(1 citation statement)

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“…Therefore, the shortest path approach can be exploited in CAbased movement simulation to mimic pedestrian decision-making during an evacuation by selecting the nearest exit. There are many shortest path approaches, such as Dijkstra's Algorithm (DA), Floyd-Warshall algorithm, and A* search algorithm for graph theory solutions involving intersection and Euclidean geometry solutions using Pythagorean Theorem (PT) for high dimensional space that consists of vector for magnitude and direction [16,18,[24][25][26][27]. In this research, the Pythagorean Theorem (PT) and Dijkstra's Algorithm (DA) were chosen and analysed to determine a viable approach for designing an emergency route plan with obstacles.…”

Section: Shortest Path Approachmentioning

confidence: 99%

Emergency Route Planning with the Shortest Path Methods: Static and Dynamic Obstacles

Ibrahim¹,

Hassan²,

Wahab³

et al. 2022

Int. j. simul. model.

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In extreme cases, evacuation difficulties could cause casualties in a closed layout during an emergency. The existing emergency routes are designed based on the shortest path to the nearest egress in a vacant layout. This research aims to design an emergency route plan in a realistic closed layout with interior arrangements and crowds as static and dynamic impediments that cause movement divergence and misdirection that affect evacuation time. This research proposes an automated emergency route design using Cellular Automata (CA) based pedestrian simulation in a realistic layout. The simulation was integrated with the Pythagorean Theorem (PT) and Dijkstra's Algorithm (DA) to imitate human exitfinding behaviour during evacuation. The results showed that PT is viable in layouts with static obstacles, requiring 20 % less travel distances and evacuation time than DA with similar experiment sets. However, the DA approach results have become on par with the PT in a layout with dynamic and static obstacles. DA outperforms PT in densely populated regions, while PT outperforms DA in less populated regions.

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