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The study on mechanical model considering optimal self-adaption in the bottleneck area.

Longcheng Yang1,2, Huajun Wang1, Jun Hu2

  • 1Key Laboratory of Earth Exploration and Information Technology of Ministry of Education, Chengdu University of Technology, Chengdu, 610059, China.

Heliyon
|April 4, 2024
PubMed
Summary

This study introduces a new crowd evacuation model to improve simulation accuracy in multi-exit scenarios. The enhanced model optimizes pedestrian path choices and distribution, leading to more realistic and efficient evacuations, especially in crowded conditions.

Keywords:
Bottleneck areaCentralized and distributed network modelCrowd evacuationElephant herding algorithmMulti-exit

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Area of Science:

  • Computational Social Science
  • Traffic and Transportation Engineering
  • Agent-Based Modeling

Background:

  • Traditional social force models inaccurately simulate pedestrian evacuation in multi-exit scenarios, particularly regarding optimal path selection and herd behavior.
  • Existing models struggle with the complexities of real-world crowd dynamics, leading to discrepancies between simulated and actual evacuation states.

Purpose of the Study:

  • To develop a novel crowd evacuation optimization model that enhances simulation accuracy in multi-exit environments.
  • To address limitations in traditional models concerning shortest path assumptions and local optima in evacuation behavior.

Main Methods:

  • Developed a new model integrating a field model for motion direction, considering exit distance, pedestrian distribution, and crowding.
  • Employed a centralized and distributed network model for global optimization and an elephant herding algorithm for local optimization of the social force model.
  • Validated the model through experimental comparisons with an improved social force model and analyzed key influencing factors.

Main Results:

  • The new model optimizes path selection early in evacuation and improves efficiency later, ensuring even pedestrian distribution across exits.
  • Simulations demonstrate a more realistic evacuation process, with significant efficiency gains for larger pedestrian populations.
  • The model effectively mitigates disorder caused by high crowd density during multi-exit evacuations.

Conclusions:

  • The proposed model offers a significant improvement over traditional methods for simulating multi-exit pedestrian evacuations.
  • It provides a robust framework for optimizing crowd flow and enhancing safety in complex, high-density scenarios.
  • The findings highlight the importance of considering global and local optimization strategies for realistic crowd behavior modeling.