Using microscopic pedestrian simulation statistics to find clogging regions

Hassan, Fadratul Hafinaz

doi:10.1109/sai.2016.7555976

Cited by 6 publications

(6 citation statements)

References 3 publications

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“…Pedestrian simulation is an artificial intelligence approach that mimics human behaviour and reaction that involves position transitioning, navigation, and collision avoidance. Many methods have been proposed for motion modelling, including Cellular Automata (CA), lattice gas model, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) [14,15,[19][20][21][22]. Mainly, crowd movement is always represented as the macroscopic movement phenomenon.…”

Section: Microscopic Approach: Cellular Automata Modelmentioning

confidence: 99%

“…However, research shows that pedestrian motion and decision-making vary depending on the surrounding situation and neighbouring interaction [9,15]. During the panic, the pedestrian will self-organize due to safety, fear, and desire for movement direction [7,8,14,19]. Hence, the microscopic approach is a suitable model to mimic pedestrian interaction with surroundings while self-organizing [14,15,19,20].…”

Section: Microscopic Approach: Cellular Automata Modelmentioning

confidence: 99%

“…During the panic, the pedestrian will self-organize due to safety, fear, and desire for movement direction [7,8,14,19]. Hence, the microscopic approach is a suitable model to mimic pedestrian interaction with surroundings while self-organizing [14,15,19,20].…”

Section: Microscopic Approach: Cellular Automata Modelmentioning

confidence: 99%

“…However, in general, the route will be designed based on a vacant layout, making it difficult to assist the pedestrians in evacuating during an actual panic situation because, realistically, the occupied layouts are often filled with furniture and people. Studies have shown that incorporating pedestrian behaviour and movement into layout design can validate and ensure pedestrian safety in a layout [13][14][15]. Previous research proposed designing an emergency route plan for chemical accident mitigation by combining chemical leakage parameters, meteorological conditions, and ammonia concentration with pedestrian behaviour [16].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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Section: Microscopic Approach: Cellular Automata Modelmentioning

confidence: 99%

Section: Microscopic Approach: Cellular Automata Modelmentioning

confidence: 99%

Section: Microscopic Approach: Cellular Automata Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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“…The incidents that had happened in the past such as; 1) The fire spreading at The Station nightclub in Rhode Island in 2003 that had killed 100 people and injured 230 people in total due to the rapid growth of fire that has blocked the egress and entrapped the pedestrians inside the building, 2) The fire incidents at the Valley Parade stadium at the city of Bradford in UK in 1985 that had killed 56 people and injured 300 people, and 3) The tear gas explosion during riot control such as at the overcrowded Ellis Park stadium at Johannesburg, South Africa in 2001 that at least killed 43 people and injured 155 people when the crowd trying to get out from the stadium forcefully due to the tear gas and had caused a huge stampede near to the egress points [9][10][11][12]. Hence, the researchers are searching and reviewing the suitable methods to detect, predict and overcome this crowd management issue as the implication for the future incidents or for the controlling actions to reduce the casualties or as the principle guidance for the structural design, arrangement and crowd movement supervision [2,[13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Cellular Automaton based Fire Spreading Simulation in Closed Area: Clogging Region Detection

Ibrahim¹,

Hassan²,

Mahyuddin³

et al. 2018

IJET

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Fire spreading is one of the visualization techniques used for re-enacting or envisions the fire incidents for conducting the post-incidents’ responses and analysing the incidents for post-mortem purposes. There are several current researches on the fire spreading incidents that involve the construction of fire spreading simulation which has focusing on the fire development, smoke control, the prediction of temperature distribution during the fire spreading, emergency response’s plans and post-fire damage assessment. However, there are more features need to be explored in the fire spreading simulation and also the pedestrians movement of the affected incident’s area for the future space design development, arrangement and structural improvement that are impactful towards human safety and also useful for the justification and prediction on the pedestrian survival rate during any panic situations. Hence, this research has focusing on the features of realistic scaling of the spatial layout and implementing the Cellular Automata (CA) approach for imitating the near-realistic pedestrian self-organizing movement and fire spreading characteristics at the microstructure level for designing the heat map of the affected area to show the clogging region in the spatial layout while constructing a reliable prediction on the pedestrian survival rate. This clogging region mapping will be useful for finding the existing issues that lead towards high casualties. Based on the experiments and observations, the heat map of the affected area showed the heavy congestions happened specifically near to the ingress/ egress points and narrow pathways that had affected the pedestrian flow rate and caused the 75% of the 352 pedestrians in the spatial layout to burn and die during the fire simulation by unintentionally taking an extra of 43.85 seconds more than the total fire spreading time (13.42 seconds) to evacuate from the closed area building.

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Optimal Moore Neighborhood Approach of Cellular Automaton Based Pedestrian Movement: A Case Study on the Closed Area

Ibrahim

Hassan

2018

Advances in Intelligent Systems and Computing

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Using microscopic pedestrian simulation statistics to find clogging regions

Cited by 6 publications

References 3 publications

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

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

Cellular Automaton based Fire Spreading Simulation in Closed Area: Clogging Region Detection

Optimal Moore Neighborhood Approach of Cellular Automaton Based Pedestrian Movement: A Case Study on the Closed Area

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