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End-to-end emergency response protocol for tunnel accidents augmentation with reinforcement learning.

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第一作者： Hafiz Muhammad Raza,Ur Rehman

第一单位： Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea.

作者： Hafiz Muhammad Raza,Ur Rehman ^[1] ; M Junaid,Gul ^[1] ; Rabbiya,Younas ^[1] ; Muhammad Zeeshan,Jhandir ^[2] ; Roberto Marcelo,Alvarez ^[3] ; Yini,Miro ^[4] ; Imran,Ashraf ^[5]

作者单位： Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea. ^[1] Department of Data Science, The Islamia University of Bahawalpur, Bahawalpur, Pakistan. ^[2] Universidad Europea del Atlantico, Isabel Torres 21, 39011, Santander, Spain.;Universidad Internacional Iberoamericana, Arecibo, PR, 00613, USA.;Universidade Internacional do Cuanza, Cuito, Angola. ^[3] Universidad Europea del Atlantico, Isabel Torres 21, 39011, Santander, Spain.;Universidad Internacional Iberoamericana, 24560, Campeche, Mexico.;Universidad de La Romana, La Romana, Dominican Republic. ^[4] Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Republic of Korea. imranashraf@ynu.ac.kr. ^[5]

关键词 Drones Multi-agents system Path finding Reinforcement learning Robotic systems Tunnel hazards Unmanned aerial vehicles

DOI 10.1038/s41598-026-37191-w

PMID 41588147

发布时间 2026-02-16

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