Identification of Key Risk Hotspots in Mega-Airport Surface Based on Monte Carlo Simulation

Wen Tian, Xuefang Zhou, Jianan Yin, Yuchen Li, Yining Zhang
{"title":"Identification of Key Risk Hotspots in Mega-Airport Surface Based on Monte Carlo Simulation","authors":"Wen Tian, Xuefang Zhou, Jianan Yin, Yuchen Li, Yining Zhang","doi":"10.3390/aerospace11040254","DOIUrl":null,"url":null,"abstract":"The complex layout of the airport surface, coupled with interrelated vehicle behaviors and densely mixed traffic flows, frequently leads to operational conflict risks. To address this issue, research was conducted on the recognition of characteristics and risk assessment for airport surface operations in mixed traffic flows. Firstly, a surface topological network model was established based on the analysis of the physical structure features of the airport surface. Based on the Monte Carlo simulation method, the simulation framework for airport surface traffic operations was proposed, enabling the simulation of mixed traffic flows involving aircraft and vehicles. Secondly, from various perspectives, including topological structural characteristics, network vulnerabilities, and traffic complexity, a comprehensive system for feature indices and their measurement methods was developed to identify risk hotspots in mixed traffic flows on the airport surface, which facilitated the extraction of comprehensive risk elements for any node’s operation. Finally, a weighting rule for risk hotspot feature indices based on the CRITIC–entropy method was designed, and a risk assessment method for surface operations based on TOPSIS–gray relational analysis was proposed. This method accurately measured risk indices for airport surface operations hotspots. Simulations conducted at Shenzhen Bao’an International Airport demonstrate that the proposed methods achieve high simulation accuracy. The identified surface risk hotspots closely matched actual conflict areas, resulting in a 20% improvement in the accuracy of direct risk hotspot identification compared to simulation experiments. Additionally, 10.9% of nodes in the airport surface network were identified as risk hotspots, including 3 nodes with potential conflicts between aircraft and ground vehicles and 21 nodes with potential conflicts between aircraft. The proposed methods can effectively provide guidance for identifying potential “aircraft–vehicle” conflicts in complex airport surface layouts and scientifically support informed decisions in airport surface operation safety management.","PeriodicalId":505273,"journal":{"name":"Aerospace","volume":" 76","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/aerospace11040254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The complex layout of the airport surface, coupled with interrelated vehicle behaviors and densely mixed traffic flows, frequently leads to operational conflict risks. To address this issue, research was conducted on the recognition of characteristics and risk assessment for airport surface operations in mixed traffic flows. Firstly, a surface topological network model was established based on the analysis of the physical structure features of the airport surface. Based on the Monte Carlo simulation method, the simulation framework for airport surface traffic operations was proposed, enabling the simulation of mixed traffic flows involving aircraft and vehicles. Secondly, from various perspectives, including topological structural characteristics, network vulnerabilities, and traffic complexity, a comprehensive system for feature indices and their measurement methods was developed to identify risk hotspots in mixed traffic flows on the airport surface, which facilitated the extraction of comprehensive risk elements for any node’s operation. Finally, a weighting rule for risk hotspot feature indices based on the CRITIC–entropy method was designed, and a risk assessment method for surface operations based on TOPSIS–gray relational analysis was proposed. This method accurately measured risk indices for airport surface operations hotspots. Simulations conducted at Shenzhen Bao’an International Airport demonstrate that the proposed methods achieve high simulation accuracy. The identified surface risk hotspots closely matched actual conflict areas, resulting in a 20% improvement in the accuracy of direct risk hotspot identification compared to simulation experiments. Additionally, 10.9% of nodes in the airport surface network were identified as risk hotspots, including 3 nodes with potential conflicts between aircraft and ground vehicles and 21 nodes with potential conflicts between aircraft. The proposed methods can effectively provide guidance for identifying potential “aircraft–vehicle” conflicts in complex airport surface layouts and scientifically support informed decisions in airport surface operation safety management.
基于蒙特卡洛模拟的大型机场表面关键风险热点识别
机场地面布局复杂,加上车辆行为相互关联,交通流密集混合,经常导致运行冲突风险。针对这一问题,开展了混合交通流下机场地面运行特征识别与风险评估研究。首先,在分析机场地面物理结构特征的基础上,建立了地面拓扑网络模型。基于蒙特卡罗仿真方法,提出了机场地面交通运行仿真框架,实现了对飞机和车辆混合交通流的仿真。其次,从拓扑结构特征、网络脆弱性、交通复杂性等多角度出发,建立了一套完整的特征指数体系及其测量方法,以识别机场地面混合交通流的风险热点,为提取任意节点运行的综合风险要素提供了便利。最后,设计了基于 CRITIC-熵法的风险热点特征指数加权规则,并提出了基于 TOPSIS-灰色关系分析的地面运行风险评估方法。该方法准确测算了机场地面运行热点风险指数。在深圳宝安国际机场进行的仿真表明,所提出的方法具有较高的仿真精度。所识别的地面风险热点与实际冲突区域非常吻合,与模拟实验相比,直接风险热点识别的准确率提高了 20%。此外,机场地表网络中有 10.9% 的节点被识别为风险热点,其中包括 3 个飞机与地面车辆潜在冲突的节点和 21 个飞机之间潜在冲突的节点。所提出的方法可有效指导识别复杂机场地面布局中潜在的 "飞机-车辆 "冲突,为机场地面运行安全管理的知情决策提供科学依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信