KDEM: A Knowledge-Driven Exploration Model for Indoor Crowd Evacuation Simulation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Knowledge plays an important role in the indoor crowd evacuation. However, most evacuation simulation models assume that the agent is familiar with the simulation scene and does not apply the posterior knowledge to the simulation. This also makes it difficult for these models to judge the real situation of unfamiliar and complex scenes effectively. This study proposes a Knowledge-Driven Evacuation Model (KDEM), focusing on indoor crowd evacuation. In order to adapt the model to more complex scenarios, we refine the building structure knowledge and add bridge knowledge, and clarify the role of building object knowledge of safety signs and dangerous sources. The SEIR model is used to construct the function of knowledge dissemination and decay, and knowledge discovery is proposed as another way of knowledge acquisition. An exploration module is proposed, using Dijkstra and ORCA models, to help agents plan goals and paths and avoid obstacles in action. The experimental results show that the KDEM model conforms to the real situation and can provide practical guidance for public safety.

Original languageEnglish
Title of host publicationAdvances in Computer Graphics - 40th Computer Graphics International Conference, CGI 2023, Proceedings
EditorsBin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann
PublisherSpringer Science and Business Media Deutschland GmbH
Pages262-274
Number of pages13
ISBN (Print)9783031500749
DOIs
StatePublished - 2024
Event40th Computer Graphics International Conference, CGI 2023 - Shanghai, China
Duration: 28 Aug 20231 Sep 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14497
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference40th Computer Graphics International Conference, CGI 2023
Country/TerritoryChina
CityShanghai
Period28/08/231/09/23

Keywords

  • Crowd Evacuation
  • Crowd Simulation
  • Exploration Planning
  • Knowledge Dissemination
  • Knowledge-Driven

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