Article(id=1156908035370214018, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156907871645556837, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2309280, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1700841600000, receivedDateStr=2023-11-25, revisedDate=1719158400000, revisedDateStr=2024-06-24, acceptedDate=null, acceptedDateStr=null, onlineDate=1753757969943, onlineDateStr=2025-07-29, pubDate=1737993600000, pubDateStr=2025-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753757969943, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753757969943, creator=13701087609, updateTime=1753757969943, updator=13701087609, issue=Issue{id=1156907871645556837, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='3', pageStart='879', pageEnd='1312', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753757930909, creator=13701087609, updateTime=1765095544280, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1204461268821320541, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156907871645556837, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1204461268825514846, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156907871645556837, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1306, endPage=1312, ext={EN=ArticleExt(id=1156908036334903942, articleId=1156908035370214018, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Safety Evaluation of Navigation Forest Fire Rescue Flight Task Scheduling Scheme Based on Flight Path Conflict Detection, columnId=1156262729993277777, journalTitle=Science Technology and Engineering, columnName=Papers·Environmental and Safe Science, runingTitle=null, highlight=null, articleAbstract=

To evaluate the safety of navigation flight task scheduling schemes in forest fire rescue, safety evaluation indicators for navigation rescue task scheduling schemes were proposed by detecting the flight path conflicts of various general aircraft. Using an airspace grid model to model the rescue flight environment, and planning the rescue flight paths of aircraft with different performance constraints based on their respective task scheduling schemes, and conducting trajectory conflict detection to evaluate the safety of the task scheduling scheme. The simulation results show that this method has a 53.8% improvement in time efficiency compared to the direct conflict detection algorithm, and a 6.7% improvement in accuracy compared to the efficient spatiotemporal synchronous route conflict detection method. It can be seen that this method can efficiently and accurately predict track conflicts in rescue flights and evaluate the safety of task scheduling schemes, providing effective decision support for navigation rescue command and scheduling work.

, correspAuthors=Xin-ping ZHU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Hao XU, Ming-hui WANG, Jing-jing QU, Xin-ping ZHU), CN=ArticleExt(id=1156908073630655267, articleId=1156908035370214018, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于航迹冲突检测的通航林火救援飞行任务调度方案安全性评估, columnId=1156262730140078420, journalTitle=科学技术与工程, columnName=论文·环境科学、安全科学, runingTitle=null, highlight=null, articleAbstract=

为评估在森林火灾救援中通航飞行任务调度方案的安全性,通过对各通用航空器的航迹冲突进行检测,提出通航救援任务调度方案安全性评价指标。通过空域栅格模型建模救援飞行环境,基于任务调度方案针对性能约束不同的航空器规划出各自救援飞行航迹并进行航迹冲突检测,从而对任务调度方案进行安全性评估。仿真结果表明:该方法相较于直接冲突判断算法时间效率提升了53.8%,相较于高效的时空同步航线冲突检测方法准确率提升了6.7%,可见该方法能够高效准确地对救援飞行中的航迹冲突进行预测并评估任务调度方案的安全性,为通航救援指挥调度工作提供有效的决策支持。

, correspAuthors=朱新平, authorNote=null, correspAuthorsNote=
* 朱新平(1983—),男,汉族,湖南常德人,教授,博士。研究方向:航空安全、复杂空域管控。E-mail:
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徐浩(1996—),男,汉族,江苏泰兴人,硕士研究生。研究方向:复杂低空空域管控。E-mail:

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徐浩(1996—),男,汉族,江苏泰兴人,硕士研究生。研究方向:复杂低空空域管控。E-mail:

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徐浩(1996—),男,汉族,江苏泰兴人,硕士研究生。研究方向:复杂低空空域管控。E-mail:

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Jinan: Shandong Provincial Market Supervision Administration, 2022., articleTitle=null, refAbstract=null)], funds=[Fund(id=1204786510529799093, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, awardId=2021YFS0319, language=CN, fundingSource=四川省科技计划(2021YFS0319), fundOrder=null, country=null), Fund(id=1204786510596907958, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, awardId=PHD2023-042, language=CN, fundingSource=中央高校基本科研业务费专项(PHD2023-042), fundOrder=null, country=null), Fund(id=1204786510651433910, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, awardId=MZ2024JB01, language=CN, fundingSource=民航火灾科学与安全工程四川省重点实验室自主项目(MZ2024JB01), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1204786506272580442, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, xref=null, ext=[AuthorCompanyExt(id=1204786506280969052, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, companyId=1204786506272580442, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China), AuthorCompanyExt(id=1204786506289357661, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, companyId=1204786506272580442, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国民用航空飞行学院 空中交通管理学院, 广汉 618307)])], figs=[ArticleFig(id=1204786508009022355, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Fig.1, caption=Schematic diagram of flight path conflict judgment scenario, figureFileSmall=jlzpVjFCFQsEETk2dtGAmQ==, figureFileBig=Po4sRmOA3+Mse5ChTaLa4Q==, tableContent=null), ArticleFig(id=1204786508076131221, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=图1, caption=航迹冲突判断场景示意图, figureFileSmall=jlzpVjFCFQsEETk2dtGAmQ==, figureFileBig=Po4sRmOA3+Mse5ChTaLa4Q==, tableContent=null), ArticleFig(id=1204786508168405911, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Fig.2, caption=Algorithm flow for flight path conflict detection, figureFileSmall=7oOv1CKATpmmrKYpUZbPIg==, figureFileBig=w3Nfo55WmTLAUfNspFIXFA==, tableContent=null), ArticleFig(id=1204786508256486297, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=图2, caption=航迹冲突检测算法流程, figureFileSmall=7oOv1CKATpmmrKYpUZbPIg==, figureFileBig=w3Nfo55WmTLAUfNspFIXFA==, tableContent=null), ArticleFig(id=1204786508327789467, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Fig.3, caption=Fire scene airspace simulation environment, figureFileSmall=SbktCwzRIfJR+9Quox1rNQ==, figureFileBig=P6Bcok5Dy7QEIegSmpx00w==, tableContent=null), ArticleFig(id=1204786508390704029, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=图3, caption=火场空域仿真环境, figureFileSmall=SbktCwzRIfJR+9Quox1rNQ==, figureFileBig=P6Bcok5Dy7QEIegSmpx00w==, tableContent=null), ArticleFig(id=1204786508482978719, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Fig.4, caption=The time taken for each algorithm to complete conflict detection, figureFileSmall=Zj+jrFfPKkWV0uye698Qvw==, figureFileBig=tUgSBJjNQ0JeE2PtRZR0JA==, tableContent=null), ArticleFig(id=1204786508566864801, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=图4, caption=各算法完成冲突检测所用时间, figureFileSmall=Zj+jrFfPKkWV0uye698Qvw==, figureFileBig=tUgSBJjNQ0JeE2PtRZR0JA==, tableContent=null), ArticleFig(id=1204786508646556579, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Fig.5, caption=Security evaluation index Qi obtained from each algorithm, figureFileSmall=Rk7Kb0rn+pyOon166v/Uvw==, figureFileBig=9RMIDTdBs3Zqv8JS1ITZaw==, tableContent=null), ArticleFig(id=1204786508705276836, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=图5, caption=各算法所得安全性评价指标Qi, figureFileSmall=Rk7Kb0rn+pyOon166v/Uvw==, figureFileBig=9RMIDTdBs3Zqv8JS1ITZaw==, tableContent=null), ArticleFig(id=1204786508780774310, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Table 1, caption=

Task scheduling plan table

, figureFileSmall=null, figureFileBig=null, tableContent=
任务标号 任务开始时刻 任务结束时刻 任务类型 执飞机型
1 t1S t1E 灭火 直升机H1
2 t2S t2E 灭火 直升机H2
3 t3S t3E 侦查 无人机U1
4 t4S t4E 灭火 直升机H3
), ArticleFig(id=1204786508868854696, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=表1, caption=

任务调度方案表

, figureFileSmall=null, figureFileBig=null, tableContent=
任务标号 任务开始时刻 任务结束时刻 任务类型 执飞机型
1 t1S t1E 灭火 直升机H1
2 t2S t2E 灭火 直升机H2
3 t3S t3E 侦查 无人机U1
4 t4S t4E 灭火 直升机H3
), ArticleFig(id=1204786508944352170, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Table 2, caption=

General aircraft parameter settings

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 类型 平飞速度/
(km·h-1)
转弯速度/
(km·h-1)
洒水速度/
(km·h-1)
1 直升机 120 100 90
2 直升机 120 100 90
3 直升机 120 100 90
4 无人机 80 60
5 无人机 80 60
), ArticleFig(id=1204786509024043948, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=表2, caption=

通用航空器参数设置

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 类型 平飞速度/
(km·h-1)
转弯速度/
(km·h-1)
洒水速度/
(km·h-1)
1 直升机 120 100 90
2 直升机 120 100 90
3 直升机 120 100 90
4 无人机 80 60
5 无人机 80 60
), ArticleFig(id=1204786509095347118, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Table 3, caption=

Number of conflicting flight paths corresponding to task scheduling scheme

, figureFileSmall=null, figureFileBig=null, tableContent=
实验组编号 任务调度方案用时/min 航迹冲突次数
1 120 8
2 116 7
3 122 8
4 120 6
5 114 7
6 116 7
7 114 9
8 120 8
9 118 5
), ArticleFig(id=1204786509183427505, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=表3, caption=

任务调度方案对应航迹冲突次数

, figureFileSmall=null, figureFileBig=null, tableContent=
实验组编号 任务调度方案用时/min 航迹冲突次数
1 120 8
2 116 7
3 122 8
4 120 6
5 114 7
6 116 7
7 114 9
8 120 8
9 118 5
), ArticleFig(id=1204786509254730673, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=EN, label=Table 4, caption=

Risk assessment indicators for corresponding flight path conflicts in experimental group 9

, figureFileSmall=null, figureFileBig=null, tableContent=
冲突序号 冲突风险
强度
相对冲突速度/
(km·h-1)
冲突类型
因子λ
冲突位置
因子ω
1 0.859 91.7 1.0 1.5
2 0.184 174.4 1.0 1.0
3 0.760 207.8 1.5 1.0
4 0.723 138.6 0.5 1.0
5 0.429 140.0 1.0 1.5
), ArticleFig(id=1204786509317645235, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908035370214018, language=CN, label=表4, caption=

实验组9对应航迹冲突风险评价指标

, figureFileSmall=null, figureFileBig=null, tableContent=
冲突序号 冲突风险
强度
相对冲突速度/
(km·h-1)
冲突类型
因子λ
冲突位置
因子ω
1 0.859 91.7 1.0 1.5
2 0.184 174.4 1.0 1.0
3 0.760 207.8 1.5 1.0
4 0.723 138.6 0.5 1.0
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基于航迹冲突检测的通航林火救援飞行任务调度方案安全性评估
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徐浩 , 王明惠 , 瞿菁菁 , 朱新平 *
科学技术与工程 | 论文·环境科学、安全科学 2025,25(3): 1306-1312
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科学技术与工程 | 论文·环境科学、安全科学 2025, 25(3): 1306-1312
基于航迹冲突检测的通航林火救援飞行任务调度方案安全性评估
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徐浩 , 王明惠, 瞿菁菁, 朱新平*
作者信息
  • 中国民用航空飞行学院 空中交通管理学院, 广汉 618307
  • 徐浩(1996—),男,汉族,江苏泰兴人,硕士研究生。研究方向:复杂低空空域管控。E-mail:

通讯作者:

* 朱新平(1983—),男,汉族,湖南常德人,教授,博士。研究方向:航空安全、复杂空域管控。E-mail:
Safety Evaluation of Navigation Forest Fire Rescue Flight Task Scheduling Scheme Based on Flight Path Conflict Detection
Hao XU , Ming-hui WANG, Jing-jing QU, Xin-ping ZHU*
Affiliations
  • College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China
出版时间: 2025-01-28 doi: 10.12404/j.issn.1671-1815.2309280
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为评估在森林火灾救援中通航飞行任务调度方案的安全性,通过对各通用航空器的航迹冲突进行检测,提出通航救援任务调度方案安全性评价指标。通过空域栅格模型建模救援飞行环境,基于任务调度方案针对性能约束不同的航空器规划出各自救援飞行航迹并进行航迹冲突检测,从而对任务调度方案进行安全性评估。仿真结果表明:该方法相较于直接冲突判断算法时间效率提升了53.8%,相较于高效的时空同步航线冲突检测方法准确率提升了6.7%,可见该方法能够高效准确地对救援飞行中的航迹冲突进行预测并评估任务调度方案的安全性,为通航救援指挥调度工作提供有效的决策支持。

冲突检测  /  安全性评估  /  时空过滤  /  空域栅格

To evaluate the safety of navigation flight task scheduling schemes in forest fire rescue, safety evaluation indicators for navigation rescue task scheduling schemes were proposed by detecting the flight path conflicts of various general aircraft. Using an airspace grid model to model the rescue flight environment, and planning the rescue flight paths of aircraft with different performance constraints based on their respective task scheduling schemes, and conducting trajectory conflict detection to evaluate the safety of the task scheduling scheme. The simulation results show that this method has a 53.8% improvement in time efficiency compared to the direct conflict detection algorithm, and a 6.7% improvement in accuracy compared to the efficient spatiotemporal synchronous route conflict detection method. It can be seen that this method can efficiently and accurately predict track conflicts in rescue flights and evaluate the safety of task scheduling schemes, providing effective decision support for navigation rescue command and scheduling work.

conflict detection  /  security assessment  /  spatiotemporal filtering  /  spatial grid
徐浩, 王明惠, 瞿菁菁, 朱新平. 基于航迹冲突检测的通航林火救援飞行任务调度方案安全性评估. 科学技术与工程, 2025 , 25 (3) : 1306 -1312 . DOI: 10.12404/j.issn.1671-1815.2309280
Hao XU, Ming-hui WANG, Jing-jing QU, Xin-ping ZHU. Safety Evaluation of Navigation Forest Fire Rescue Flight Task Scheduling Scheme Based on Flight Path Conflict Detection[J]. Science Technology and Engineering, 2025 , 25 (3) : 1306 -1312 . DOI: 10.12404/j.issn.1671-1815.2309280
中国是森林火灾多发的国家,森林火灾对人们生命财产安全、国家林业资源安全构成重大的威胁,具有较大的社会影响。在历次发生的森林火灾救援中,通用航空救援发挥了关键性作用,特别是交通不利的情况下。在森林火灾救援与应急处置的各项措施中,通用航空救援具有快速高效、机动性强、受地理空间限制少等优点,是许多发达国家普遍采用的有效手段之一。
随着智能化通航救援飞行调度指挥平台[1]的不断发展,生成高效的通航救援飞行任务调度方案成为可能。对此类平台生成的救援飞行任务调度方案进行安全性评估,能够有效地避免参与救援飞行任务的多个通用航空器之间的航迹冲突,为救援航空器提供安全的飞行环境,减轻现场指挥员和飞行员的工作压力,实现救援机群的高效协同救援。
传统航线冲突检测算法[2]多具有时间复杂度高的问题,不适用于复杂飞行场景下的安全保障。在低空冲突探测方面:张翔宇等[3]基于Agent对复杂低空飞行行为进行建模与仿真,分析了复杂低空密集飞行活动相互影响规律;张洪海等[4]构建了低空通用航空器基本飞行行为模型,分析了复杂低空混合飞行态势的安全特性参数影响规律:Shen等 [5]基于低空飞行的自由性、机动性和临时性等特点,从时空维度提升了飞机冲突探测技术,提高了准确性;Wang等 [6]基于通用航空器机载冲突检测手段建立了适用于低空飞行环境下的冲突检测与飞行行为选择仿真系统;Hasini等[7]分析了前人应用人工势场法进行避障算法设计的局限性,提出了一种基于节能的无人机群体防撞算法,在避免无人机碰撞的同时,尽量减少无人机群体能量的消耗;Fu等[8]为保障无人机飞行安全,从冲突感知、检测、避碰和飞行控制等单元对无人机冲突探测与避障系统进行了研究;王世锦等[9]从航空器动力学原理出发,构建了同高度对头和交叉飞行冲突的冲突避让轨迹数学模型用于对低空空域飞行冲突风险的研究。
现面向森林火灾救援,通过空域栅格模型建模救援飞行环境,基于任务调度方案针对性能约束不同的航空器规划出各自救援飞行航迹并进行航迹冲突检测,从而对任务调度方案进行安全性评估,排除安全性较低的任务调度方案,优选安全性较高的任务调度方案,为火灾现场的指挥员与飞行员提供决策支持。
在森林火灾救援过程中,森林火场通常位于地形较为复杂的高山峡谷等区域,空域活动密集、环境复杂,存在较大的安全隐患。救援飞行航迹冲突可定义为,某一时刻,两个通用航空器在执行救援飞行任务时水平和垂直距离均小于安全间隔标准,以致存在冲突的风险。在既定的火场三维空域环境内,若救援指挥中心持续调度通用航空器加入救援作业,势必造成飞行活动航迹密集,冲突可能性增加。针对此,开展基于航迹冲突检测的救援飞行任务调度安全性评估。
首先,针对森林火灾救援飞行空域建立火场空域栅格模型[10],对同一高度空间采用正六边形网格进行水平剖分,得到若干大小相等、高度层相同的空域网格单元对不同高度层空域进行同样的操作,进而得到火场空域三维栅格模型,该空域模型包括起火点,取水点,航空器起降点,物资运送点,障碍物等救援空域关键要素信息;然后,指挥中心持续为各个任务目标地点指派救援航空器,形成任务调度方案如表1所示。
具体对应二维场景如图1所示,根据任务调度方案,航空器H1将由起始点S1前往目标点T1,航空器H2将由起始点S2前往目标点T2;针对任务调度方案和各航空器飞行初始位置和任务目标地点,借助改进A*算法为各通用航空器进行航迹规划[11],确定各航迹点的三维空间坐标和时间坐标,航迹点的三维空间坐标为航迹点所在空域栅格的三维空间坐标,并对两条航迹是否存在航迹冲突设计相应的量化分析模型以评估飞行任务的安全性。
假设通用航空器在相邻两个航迹点之间的飞行视为匀速直线运动。
基于航迹冲突判定基本过程包括时间维度的冲突判定和空间维度的冲突判定。首先,开展时间维度的冲突判定,基于任务调度方案和航迹规划方案,推演通用航空器通过各空域栅格的过程,得到航空器占用各空域栅格的时间段,并对存在空域栅格占用时段重叠的航迹点进一步开展空间维度的冲突判定;然后,针对存在栅格空域占用时段重叠的航迹点进行航迹冲突过滤,若存在两个航迹点之间在三维方向上均小于最小安全距离,则认为该航迹点组合存在航迹冲突的可能性。对于存在航迹冲突可能的航迹点组合,利用该航迹点组合所处的航迹段进行进一步冲突判断,若航迹段在水平和垂直方向均存在实际距离小于安全距离的时刻,则认为该航迹点组合存在航迹冲突,对该航迹冲突进行记录,算法流程如图2所示。
通用航空器Hi救灾飞行航迹定义为Pi= P i , 1 , P i , 2 P i , r , , P i , n - 1 , P i , n。其中:Pi,1为通用航空器Hi的救灾飞行起点;Pi,nHi救灾飞行的终点;Pi,r=(Xi,r,Yi,r,Zi,r,t1i,r,t2i,r)为Hi的任一航迹点;(Xi,r,Yi,r,Zi,r)为Pi,r的三维坐标,航空器在任意相邻两个航迹点之间的运动简化为匀速直线运动;t1i,rHi进入航迹点Pi,r所在栅格的预计时刻;t2i,rHi飞离航迹点Pi,r所在栅格的预计时刻;Hi在任意相邻两个航迹点之间的运动简化为匀速直线运动。
(1)时间维度过滤,取航迹Pi的航迹点Pi,r和航迹点Pj的航迹Pj,u,若Pi,r的占用时间段[t1i,r,t2i,r]与Pj,u的占用时间段[t1j,u,t2j,u]不存在重叠,即t2i,r不满足t2i,rt1j,u,且t1i,r不满足t2j,ut1i,r,则将航迹点组合(Pi,r,Pj,u)储存于集合CT中,CT为存在时段重叠的航迹点组合的集合。
(2)垂直安全距离过滤,对CT中的任一航迹点组合(Pi,r,Pj,u),取航迹点Pi,rPj,u的进行垂直距离比较,若两个航迹点的z坐标差值小于最小垂直安全距离dzmin,则进行水平安全距离过滤。
(3)水平安全距离过滤,对于存在垂直方向存在冲突可能性的航迹点组合(Pi,r,Pj,u),取航迹点Pi,rPj,u进行x坐标比较和y坐标比较,若两个航迹点的x坐标距离差值和y坐标距离差值均小于最小水平安全距离dxymin,则将航迹点组合(Pi,r,Pj,u)储存于集合CTS中,CTS为存在冲突可能性的航迹点组合的集合。
航迹冲突过滤算法如下:
Algorithm 1: Track conflict filtering
Input:输入航迹点Pi,r的时空坐标(Xi,r,Yi,r,Zi,r,t1i,r,t2i,r)
Output:输出存在航迹冲突可能性的航迹点组合的集合CTS
CN= empty_set
CT = empty_set
CTS= empty_set
for i=1 to Nh//时间维度过滤
for r =1 to nhi
for j=i+1 to Nh
for u=1 to nhj
if t2i,rt1j,u or t2j,ut2i,r then
add(Pi,r,Pj,u)to CN
else if
add (Pi,r,Pj,u)to CT
end if
end for
end for
end for
end for
for each(Pi,r,Pj,u)in CT
if Z i , r - Z j , udzmin then //空间维度过滤
if X i , r - X j , udxymin then
if Y i , r - Y j , udxymin then
add (Pi,r,Pj,u)to CTS
else if
add (Pi,r,Pj,u)to CN
end if
end if
end if
end for
该算法中,CN为不存在航迹冲突可能性的航迹点组合的集合,Nh为任务调度方案中航迹的数目,nhi为单个航迹包含航迹点的数目。
集合CTS中任一航迹点组合(Pi,r,Pj,u)所处的航迹在时间段上具有一定程度的重合,同时xyz轴3个方向上均小于最小安全距离,因此存在航迹冲突的可能性,需要对集合CTS中的每一个航迹点组合进行计算以验证是否存在冲突。
集合CTS中任一航迹点组合(Pi,r,Pj,u)中,航迹点Pi,r所处的航迹段为 [Pi,r-1,Pi,r]和[Pi,r,Pi,r+1],航迹点Pj,u所处航迹段为[Pj,u-1,Pj,u]和[Pj,u,Pj,u+1],在航迹冲突验证的过程中,需将Pi,r所处的两个航迹段与Pj,u所处的两个航迹段分别进行冲突验证。
航空器Hi在航迹段[Pi,r-1,Pi,r]中作匀速直线运动,Hj在航迹段[Pj,u-1,Pj,u]中作匀速直线运动。可近似认为航空器Hi通过航迹点Pi,r-1Pi,r的时刻表达式为
t i , r - 1 = t 1 i , r - 1 + t 2 i , r - 1 2 t i , r = t 1 i , r + t 2 i , r 2
同样,Hj通过航迹点Pj,u-1和航迹点Pj,u的时刻分别为tj,u-1tj,u
假设在t时刻航空器Hi与航空器Hj之间在水平方向上的距离小于水平安全距离,t∈[ti,r-1,ti,r]∩[tj,u-1,tj,u],则t时刻航空器Hix方向的坐标可表示为
Xi,t=Xi,r-1+ ( t - t i , r - 1 ) ( X i , r - X i , r - 1 ) t i , r - t i , r - 1
t时刻航空器Hiy方向的坐标可表示为
Yi,t=Yi,r-1+ ( t - t i , r - 1 ) ( Y i , r - Y i , r - 1 ) t i , r - t i , r - 1
t时刻航空器Hiz方向的坐标可表示为
Zi,t=Zi,r-1+ ( t - t i , r - 1 ) ( Z i , r - Z i , r - 1 ) t i , r - t i , r - 1
使用同方法可计算出t时刻航空器Hj在三轴方向的坐标(Xi,t,Yi,t,Zi,t),则航空器Hi和航空器Hjt时刻水平方向的距离dxy(i,j,t)可表示为
dxy(i,j,t)= ( X i , t - X j , t ) 2 + ( Y i , t - Y j , t ) 2
判断航空器Hi与航空器Hjt时刻水平方向是否存在冲突,若存在时刻t使
dxy(i,j,t)dxymin
成立,则说明航迹段[Pi,r-1,Pi,r]与[Pj,u-1,Pj,u]在水平方向存在冲突,记t的解为t∈[ta,tb],此时需进行垂直方向冲突验证;若式(6)不成立,则航迹段[Pi,r-1,Pi,r]与[Pj,u-1,Pj,u]不存在冲突。
若航迹段[Pi,r-1,Pi,r]与[Pj,u-1,Pj,u]在水平方向存在冲突,假设在t时刻航空器Hi与航空器Hj之间在垂直方向上的距离小于垂直安全距离dzmin,t∈[ta,tb],此时航空器Hi与航空器Hj在垂直方向的距离可表示为
dz(i,j,t)= Z i , t - Z j , t
判断航空器Hi与航空器Hjt时刻垂直方向是否存在冲突,若存在时刻t使
dz(i,j,t)dzmin
成立,则说明航迹段[Pi,r-1,Pi,r]与[Pj,u-1,Pj,u]存在冲突,记t的解为t∈[t'a,t'b];若式(8)不成立,说明航迹段[Pi,r-1,Pi,r]与[Pj,u-1,Pj,u]不存在冲突。对航迹段[Pi,r-1,Pi,r]与[Pj,u-1,Pj,u]的冲突验证完成,随后依次计算航迹段[Pi,r-1,Pi,r]与[Pj,u,Pj,u+1],[Pi,r,Pi,r+1]与[Pj,u-1,Pj,u],[Pi,r,Pi,r+1]与[Pj,u,Pj,u+1]的冲突验证,全部完成后,对集合CTS中航迹点组合(Pi,r,Pj,u)的冲突验证完成,此时记录发生冲突的双方航空器空间位置,冲突发生时间等信息,对下一航迹点组合继续进行验证。
在实际救灾飞行中,除了要考虑航空器之间的航迹冲突对飞行安全的影响外,还需考虑灾害区域变化的不确定性对救灾飞行的影响。
在火灾燃烧的过程中,受到周围大气的相互作用,形成火场区的上升气流,给救灾航空器的飞行安全带来很大影响,当航迹冲突发生在火场气流范围内时,会增加航迹冲突发生时的危险性,因此,本文中考虑火场气流给航迹冲突带来的影响,使研究问题更加贴合实际救灾。
针对火场气流做出如下假设:
假设1 火场气流的移动速度小于航空器的速度,且速度恒定。
假设2 火场气流运动方向为直线运动。
假设t时刻火场气流的三维坐标为(XDobs,t,YDobs,t,ZDobs,t),火场气流的水平影响距离为dDobs,垂直影响距离为zDobs,航空器i与火场气流之间的水平距离表示为
dxy(i,Dobs,t)= ( X i , t - X D o b s , t ) 2 + ( Y i , t - Y D o b s , t ) 2
t时刻航空器i与火场气流之间的垂直距离表示为
dz(i,Dobs,t)=Zi,t-ZDobs,t
判断两个航空器之间的航迹冲突是否发生在火场气流影响范围内,若存在时刻t(t∈[t'a,t'b]),使
d x y ( i , D o b s , t ) d D o b s d z ( i , D o b s , t ) z D o b s
d x y ( j , D o b s , t ) d D o b s d z ( j , D o b s , t ) z D o b s
成立,则说明航迹冲突发生在火场气流影响范围内,若式(11)与式(12)均不成立,则说明航迹冲突发生在火场气流影响范围外。
通用航空器救灾的目标是在保证飞行安全的前提下完成救灾任务,所以基于航迹冲突检测对决策支持系统生成的多个任务调度方案进行安全性评估是有必要的。
单个任务调度方案的航迹冲突集合定义为C={C1,C2,…,Ck,…,Cm-1,Cm},Ck为存在航迹冲突的一个航迹点组合,m为单个任务调度方案航迹冲突发生的次数,对于航迹冲突的风险建立多个评价指标[12]
(1)冲突发生率:单个任务调度方案在任务调度过程中单位时间发生的航迹冲突次数,计算公式为
Cp= m t e - t 0
式(13)中:t0为任务调度开始时间;te为任务调度结束时间。
(2)冲突风险强度:通过基于人工势场法的两个通用航空器之间的斥力大小表示通用航空器之间的航迹冲突风险强度,计算公式为
CR(i,j,t)= η d x y ( i , j , t ) 2 1 d x y ( i , j , t ) - 1 d x y m i n , d x y ( i , j , t ) d x y m i n 0 , d x y ( i , j , t ) d x y m i n
式(14)中:η为正比例位置增益系数。
(3)相对冲突速度:发生航迹冲突时,通用航空器i与通用航空器j之间的相对速度Vi,j,t表示为
Vi,j,t=Vi,t-Vj,t
为避免各指标之间数量级差别造成安全性评价误差,需对以上数据进行归一化处理,对于序列{x1,x2,…,xn}进行变化,即
yi= x i - x m i n x m a x - x m i n
航迹冲突的类型是影响任务调度方案安全性的重要因素,因此引入航迹冲突类型因子λ来评估调度方案的安全性,λ的取值为
λ= 1.5 ,   1.0 ,   0.5 ,  
考虑火场气流给航迹冲突带来的影响,引入航迹冲突位置因子ω来评估调度方案的安全性,ω的取值为
ω= 1.5 ,   1.0 ,  
在对任务调度方案进行安全性评估的过程中,航迹冲突的发生率会影响现场指挥员与飞行员的工作负荷,冲突的风险强度与航迹冲突发生时航空器的相对速度会影响航迹冲突发生时的危险程度。同时,航迹冲突发生时,冲突双方航空器类型与航迹冲突发生的位置也对调度方案的安全性评估存在影响。综上,对于调度方案Mi的安全性建立评价指标Qi,即
Qi= 1 C p i k = 1 M i λ i k ω i k C R i k V i k
安全性评价指标Qi值越大,代表该调度方案的安全性越高。
对航迹冲突算法的有效性进行仿真实验,以验证飞行任务调度方案安全性分析方法的有效性。本文算法与直接冲突判断算法和文献[13]中的同步时间航段算法进行对比,直接冲突判断算法不对航迹点组合进行过滤,对每一组航迹点组合直接进行冲突验证,同步时间航段算法事先对基于火场空域的栅格的航迹进行时间同步航迹段计算,通过同步时间段的航迹来进行冲突检测。
在相同的仿真实验场景下,本文中共设置9组实验,安全距离设置参照文献[14],每组实验对应一种任务调度方案,通用航空的数目为5,其中3架为直升机, 2架为无人机,由直升机执行吊桶灭火任务,无人机执行火场侦查任务,根据任务调度方案提供的各航空器的起始点和目标任务点以及任务时间,基于火场空域栅格模型为每个航空器规划航迹,空域栅格模型的栅格大小设置为100 m,栅格高度设置为50 m,火场空域的大小设置为3 km×5 km,设定水平冲突距离为100 m,垂直冲突距离为50 m,火场空域仿真环境如图3所示,表2为通用航空器参数。
分别使用3种冲突判断算法进行检测计算,记录3种算法完成冲突检测所用时间如图4所示,并记录航迹冲突各项数据。
图4所示,根据实验结果,本文算法完成冲突检测所需时间略大于时间同步航段算法,同步时间航段算法所花费的时间相较于本文算法平均减少了3.1%,直接冲突判断算法由于需要对每个航迹点组合进行冲突判断,计算所需时间远大于本文算法与同步时间航段算法,本文算法相较于直接冲突判断算法所花费的计算时间减少了53.8%。各实验组对应任务调度方案的航迹冲突次数如表3所示。
在完成航迹冲突检测计算后,将根据航迹冲突数据计算各实验组航迹冲突的风险评价指标,实验组9共存在5次航迹冲突,根据本文算法计算对应风险指标如表4所示。
根据式(19)计算各实验组对应任务调度方案的安全性评价指标如图5所示,根据实验结果,本文算法计算得到的安全性评价指标与直接冲突判断算法基本相同,本文算法与仿真实验结果相比,平均偏差率均为1.1%,而同步时间航段算法由于在计算过程中过度简化,得到的安全性评价指标与仿真实验结果相比,与仿真实验结果的平均偏差率达到7.8%,准确率较于本文算法降低了6.7%,与仿真实验结果偏差较大。
实验组9所对应任务调度方案安全性评价指标最高,说明实验组9所对应的任务调度方案最佳,能够有效地降低现场指挥员及通用航空器驾驶员的工作压力。
(1)针对基于火场空域栅格的通航救援任务调度方案,提出基于航迹冲突检测的任务调度方案安全性评估方法。
(2)通过对组成航迹的航迹点进行冲突过滤,排除不可能产生航迹冲突的航迹点组合,大幅提高计算效率。
(3)对于存在冲突可能的航迹点组合进行空间三维的航线段冲突验证,相较于文献[12]提出的时空同步高效航线检测方法,本文算法所用时间增加了3.1%,但的准确率提高了6.7%。
(4)仿真结果表明该方法能够高效快速检测火场环境下通用航空器的航迹冲突,评估任务调度方案的安全性,为森林火灾现场的指挥员和飞行员提供有效的决策支持。
  • 四川省科技计划(2021YFS0319)
  • 中央高校基本科研业务费专项(PHD2023-042)
  • 民航火灾科学与安全工程四川省重点实验室自主项目(MZ2024JB01)
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doi: 10.12404/j.issn.1671-1815.2309280
  • 接收时间:2023-11-25
  • 首发时间:2025-07-29
  • 出版时间:2025-01-28
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  • 收稿日期:2023-11-25
  • 修回日期:2024-06-24
基金
四川省科技计划(2021YFS0319)
中央高校基本科研业务费专项(PHD2023-042)
民航火灾科学与安全工程四川省重点实验室自主项目(MZ2024JB01)
作者信息
    中国民用航空飞行学院 空中交通管理学院, 广汉 618307

通讯作者:

* 朱新平(1983—),男,汉族,湖南常德人,教授,博士。研究方向:航空安全、复杂空域管控。E-mail:
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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