公路2024,Vol.69Issue(12) :271-277.

数据驱动下高速公路应急无人机基站选址研究

Research on Highway Emergency Unmanned Aerial Vehicle(UAV)Base Station Siting Driven by Data

谢庆 袁辉 计明军 曾斌 吴炜昌 匡政霖
公路2024,Vol.69Issue(12) :271-277.

数据驱动下高速公路应急无人机基站选址研究

Research on Highway Emergency Unmanned Aerial Vehicle(UAV)Base Station Siting Driven by Data

谢庆 1袁辉 1计明军 2曾斌 1吴炜昌 1匡政霖2
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作者信息

  • 1. 中铁南方投资集团有限公司 阳江市 529500
  • 2. 大连海事大学 大连市 116000
  • 折叠

摘要

无人机技术的应用极大促进了我国智慧高速公路网络的发展,无人机基站作为系统核心组成部分其位置选择对于系统功能发挥具有至关重要的作用,同时对整个高速公路网络的运行效率和应急处理能力也有着不可或缺的影响.创新性地针对无人机在续航能力和实时通信距离上的局限性,构建了应对高速公路不同路段事故风险的无人机基站选址模型,并运用贪婪随机自适应搜索算法进行了优化求解.通过算例分析和对建站数量的敏感性分析,提出的选址方案在确保了满足操作约束的同时,显著提高了应急响应的速度,为智慧高速公路的应急管理系统提供了有效的策略支持,标志着在智慧高速公路建设中向前迈进了重要一步.

Abstract

The application of Unmanned Aerial Vehicle(UAV)technology has significantly advanced the development of China's intelligent highway network.The base stations of UAV,critical to the system,play a pivotal role in its functionality,affecting the efficiency and emergency handling capabilities of the entire network.This study innovatively addresses the limitations of drones'endurance and real-time communication range by developing a siting model for drone bases across various highway sections.The model,optimized with a Greedy Randomized Adaptive Search algorithm,enhances emergency response speed and provides strategic support for intelligent highway emergency management systems,marking a significant step forward in the development of intelligent expressways.

关键词

智慧交通/无人机基站/高速公路应急/深度学习/最大覆盖模型/贪婪随机自适应

Key words

intelligent transportation/UAV base stations/expressway emergency response/deep learning/maximum coverage model/greedy randomized adaptive search

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出版年

2024
公路
中国交通建设集团有限公司

公路

CSTPCD北大核心
影响因子:0.54
ISSN:0451-0712
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