A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire Information

Background: Escape routes are important measures for firefighters to ensure their own safety, providing predetermined paths to safe areas. Their establishment needs to consider numerous factors, such as the timeliness and safety of the routes. Aims: Optimize the path planning method previously studi...

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Main Authors: Hesun Wang, Junhao Sheng, Xindong Li, Hongyang Zhao, Dandan Li
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Fire
Subjects:
Online Access:https://www.mdpi.com/2571-6255/7/12/459
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author Hesun Wang
Junhao Sheng
Xindong Li
Hongyang Zhao
Dandan Li
author_facet Hesun Wang
Junhao Sheng
Xindong Li
Hongyang Zhao
Dandan Li
author_sort Hesun Wang
collection DOAJ
description Background: Escape routes are important measures for firefighters to ensure their own safety, providing predetermined paths to safe areas. Their establishment needs to consider numerous factors, such as the timeliness and safety of the routes. Aims: Optimize the path planning method previously studied by our team to ensure the dynamic nature, timeliness, and safety of the routes. Methods: (1) Propose a comprehensive safety index that encompasses both spatial and temporal safety indices, providing a more holistic approach to route safety. (2) Introduce spatial adaptive factors and spatial safety windows corresponding to the spatial safety index within the comprehensive safety index. (3) Present a new concept, the “observation cycle”, as a standard for the frequency of updating wildfire spread information, thereby addressing the issue of a lack of real-time input information. Based on this, we propose a reliable dynamic update rule for its updating. Results: Compared to the unoptimized model, the final optimized model’s planned escape routes offer impressive dynamic performance, effectively guarding against sudden changes in wildfire conditions, enhancing route safety, and ensuring timeliness. Conclusions: This research ensures that firefighters can effectively guard against the threats posed by sudden changes in wildfire conditions when escaping in wildfire environments, while also guaranteeing timeliness and safety.
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series Fire
spelling doaj-art-856faee1c3ea44a298b9ebaac3f3a2052024-12-27T14:25:46ZengMDPI AGFire2571-62552024-12-0171245910.3390/fire7120459A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire InformationHesun Wang0Junhao Sheng1Xindong Li2Hongyang Zhao3Dandan Li4College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaCollege of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaCollege of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaCollege of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaCollege of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaBackground: Escape routes are important measures for firefighters to ensure their own safety, providing predetermined paths to safe areas. Their establishment needs to consider numerous factors, such as the timeliness and safety of the routes. Aims: Optimize the path planning method previously studied by our team to ensure the dynamic nature, timeliness, and safety of the routes. Methods: (1) Propose a comprehensive safety index that encompasses both spatial and temporal safety indices, providing a more holistic approach to route safety. (2) Introduce spatial adaptive factors and spatial safety windows corresponding to the spatial safety index within the comprehensive safety index. (3) Present a new concept, the “observation cycle”, as a standard for the frequency of updating wildfire spread information, thereby addressing the issue of a lack of real-time input information. Based on this, we propose a reliable dynamic update rule for its updating. Results: Compared to the unoptimized model, the final optimized model’s planned escape routes offer impressive dynamic performance, effectively guarding against sudden changes in wildfire conditions, enhancing route safety, and ensuring timeliness. Conclusions: This research ensures that firefighters can effectively guard against the threats posed by sudden changes in wildfire conditions when escaping in wildfire environments, while also guaranteeing timeliness and safety.https://www.mdpi.com/2571-6255/7/12/459escape routedynamismfirefighter safetytravel ratesleast-cost path modellingabrupt shifts in wildfire behavior
spellingShingle Hesun Wang
Junhao Sheng
Xindong Li
Hongyang Zhao
Dandan Li
A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire Information
Fire
escape route
dynamism
firefighter safety
travel rates
least-cost path modelling
abrupt shifts in wildfire behavior
title A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire Information
title_full A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire Information
title_fullStr A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire Information
title_full_unstemmed A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire Information
title_short A Self-Adaptive Escape Route Planning Model Based on Dynamic Wildfire Information
title_sort self adaptive escape route planning model based on dynamic wildfire information
topic escape route
dynamism
firefighter safety
travel rates
least-cost path modelling
abrupt shifts in wildfire behavior
url https://www.mdpi.com/2571-6255/7/12/459
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