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A Social Force Evacuation Model with Guides Based on Fuzzy Clustering and a Two-Layer Fuzzy Inference.

Qian Xiao1, Jiayang Li1,2

  • 1School of Intelligent Science and Engineering Shenyang University, Shenyang, Liaoning 110044, China.

Computational Intelligence and Neuroscience
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Summary
This summary is machine-generated.

This study introduces a novel fuzzy inference system to optimize emergency evacuation guide placement, considering pedestrian decision-making. The improved model significantly reduces evacuation times and balances exit usage for better crowd management.

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Area of Science:

  • Emergency Management
  • Crowd Dynamics
  • Fuzzy Systems

Background:

  • Current emergency management often overlooks pedestrian decision-making in guide placement.
  • Existing models lack consideration for subjective pedestrian perceptions during evacuations.
  • Limited vision scenarios present unique challenges for effective crowd guidance.

Purpose of the Study:

  • To design a fuzzy inference system for pedestrian-guided evacuation selection.
  • To construct an improved crowd evacuation model incorporating guide placement strategies.
  • To enhance emergency management decision-making with flexible guidance strategies.

Main Methods:

  • Gaussian fuzzy clustering to determine optimal guide numbers and positions.
  • A two-layer fuzzy inference system for multifactor pedestrian guide selection.
  • An improved social force model integrating manager and pedestrian perspectives.

Main Results:

  • Simulations demonstrate reduced evacuation times compared to existing methods.
  • The proposed guide setting scheme effectively balances exit utilization.
  • The model proves beneficial for diverse population distributions in simulated scenarios.

Conclusions:

  • The developed fuzzy inference system and evacuation model improve emergency response.
  • Considering pedestrian perspectives leads to more efficient and equitable evacuations.
  • The model offers a valuable tool for emergency management decision-making departments.