基于模糊贝叶斯网络的低空无人机运行风险评估
Risk assessment of low-altitude unmanned aerial vehicle operation based on fuzzy Bayesian network
耿增显 1陈俊宇1
作者信息
- 1. 中国民航大学 空中交通管理学院,天津 300300
- 折叠
摘要
为解决目前城市低空环境下的无人机(UAV)运行安全风险问题,利用模糊贝叶斯网络(FBN)识别和评估低空无人机运行的关键风险因素.首先,在分析低空无人机运行流程基础上,从人-机-环-管角度分析低空无人机运行过程的风险因素.随后,利用GeNIe软件构建低空无人机运行风险评估贝叶斯网络(BN),利用专家先验知识和模糊集量化分析底事件的先验概率.最后,开展单因素分析、双因素分析以及敏感性分析,并以实例验证网络可行性.研究结果表明:低空无人机运行的关键风险因素为无人机电池故障、运行航线的环境障碍物以及无人机运行监管技术;FBN反向推理分析结果显示,环境相关风险(79%)、无人机设备风险(60%)是无人机运行过程主要风险因素.
Abstract
To solve the current safety risk issues of UAV operations in low-altitude urban environments,a FBN was used to identify and analyze the key risk factors of low-altitude UAV operations.Firstly,risk factors were analyzed from the perspective of human-machine-environment-management based on operation process of low-altitude UAVs.GeNIe software was used to develop a Bayesian network(BN)for risk assessment of low-altitude UAV operations,and the prior probabilities of the underlying events were analyzed using expert prior knowledge and fuzzy sets.Finally,univariate,bivariate,and sensitivity analyses were performed,and the network feasibility was validated.The results indicated that the key risk factors for low-altitude UAV operation were UAV battery failure,environmental obstacles on the operation route,and UAV operation supervision technology.FBN reverse inference showed that environment-related risk(79%)and UAV equipment risk(60%)were the main risk factors in the UAV operation process.
关键词
模糊贝叶斯网络(FBN)/低空无人机(UAV)/风险评估/运行安全/GeNIe软件Key words
fuzzy Bayesian network(FBN)/low-altitude unmanned aerial vehicle(UAV)/risk assessment/operation safety/GeNIe software引用本文复制引用
基金项目
国家重点研发计划(2022YFB4300904)
国家外国专家项目(DL2022202002L)
出版年
2024
NETL
NSTL
万方数据