Article(id=1245407863041012583, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156262727438951343, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2403444, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1715270400000, receivedDateStr=2024-05-10, revisedDate=1720454400000, revisedDateStr=2024-07-09, acceptedDate=null, acceptedDateStr=null, onlineDate=1774857973108, onlineDateStr=2026-03-30, pubDate=1741363200000, pubDateStr=2025-03-08, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774857973108, onlineIssueDateStr=2026-03-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774857973108, creator=13701087609, updateTime=1774857973108, updator=13701087609, issue=Issue{id=1156262727438951343, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='7', pageStart='2193', pageEnd='3077', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753604116544, creator=13701087609, updateTime=1753771263994, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1156963794699248405, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156262727438951343, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1156963794699248406, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156262727438951343, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3044, endPage=3056, ext={EN=ArticleExt(id=1245407864932642833, articleId=1245407863041012583, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Construction and Visualization of Spatiotemporal Graphs of Surface Movement Resources in Airport Flight Area, columnId=1156262731079607234, journalTitle=Science Technology and Engineering, columnName=Papers·Aeronautics and Astronautics, runingTitle=null, highlight=null, articleAbstract=

Under the condition of airport autonomous operation, perception of the operational environment is a crucial factor constraining the realization of autonomous airport operations. In the process of airport surface traffic operation, understanding the utilization of surface movement resources is a key step in establishing a comprehensive operational environment. The surface movement process at airports is first focused on in this study, and an ontology model for airport surface movement processes is constructed. Based on the structural layout of the airport surface road network, the movement paths were divided, and a "node-edge" model based on the connection between network nodes was established. Meanwhile, building upon the ontology model, dynamic and static attributes of the surface road network were defined as the basic properties of network nodes. With network nodes as the research object, various conflict scenarios existing in aircraft surface movement processes were modeled based on the dynamic attributes of network nodes, thus achieving a dynamic representation of aircraft movement processes at network nodes. Using speed data generated by aircraft dynamics models as a basis, a visualization representation of dynamic graphs of surface movement resource utilization in the presence of aircraft conflict scenarios was designed.Experimental results demonstrate that the model effectively represents both conflict and conflict-free scenarios in surface operations. This enhances the overall perception of surface movement resource utilization among participants in airport surface traffic.

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在机场自治化运行条件下,对于场面运行环境的感知是制约机场实现自治化运行的一个关键因素,而机场场面交通运行过程中对于场面滑行资源占用情况是构建完整的场面运行环境的关键步骤,首先以机场场面滑行过程为研究对象,构建了机场场面滑行过程的本体模型,基于机场的场面路网结构,对路网中的滑行路径进行划分,建立了以路网节点与节点连接关系为基础的“节点-边”模型,同时以本体模型为基础,定义了场面路网的动静态属性作为路网节点的基本属性,在此基础上,以路网节点为研究对象,将航空器场面滑行过程中的存在的多种冲突场景以路网节点的动态属性进行模型表达,从而实现了航空器滑行过程在路网节点上的动态表示。以航空器动力学模型生成的速度数据为基础,设计了在航空器冲突场景下的飞行区场面滑行资源动态图的可视化表示,试验结果表明,该模型可以很好地表示场面运行过程,可以增强场面交通参与者对飞行区场面滑行资源占用状况的全域感知能力。

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常鑫(1991—),男,汉族,河南南阳人,博士,讲师。研究方向:智能交通及交通安全。E-mail:

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常鑫(1991—),男,汉族,河南南阳人,博士,讲师。研究方向:智能交通及交通安全。E-mail:

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常鑫(1991—),男,汉族,河南南阳人,博士,讲师。研究方向:智能交通及交通安全。E-mail:

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caption=航空器重叠区域面积示意图, figureFileSmall=Oegd0ZndXplzbbQUnNKaqQ==, figureFileBig=y4UsderDNx5v/HzXzV5Hjw==, tableContent=null), ArticleFig(id=1245407879319105645, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=EN, label=Fig.11, caption=Overall process of dynamic taxiing resource, figureFileSmall=2lzt1HTtTOkKmX+yraUfQA==, figureFileBig=iyCul+ZUM15IE5ClXQDx2A==, tableContent=null), ArticleFig(id=1245407879478489210, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=CN, label=图11, caption=滑行资源动态图总体流程, figureFileSmall=2lzt1HTtTOkKmX+yraUfQA==, figureFileBig=iyCul+ZUM15IE5ClXQDx2A==, tableContent=null), ArticleFig(id=1245407879570763905, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=EN, label=Fig.12, caption="Node-edge" model of a partial network structure, figureFileSmall=eZ1wJQdGov95UPU/5inA1Q==, figureFileBig=dJldQ+cZZsu8NeAf5z6bxg==, 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articleId=1245407863041012583, language=EN, label=Fig.14, caption=Analysis of node occupancy and conflict areas during takeoff and landing processes, figureFileSmall=GEt7o5v9KjRAlrvcU+NJNw==, figureFileBig=WodQZl7uMYH9L3KnyVzVZA==, tableContent=null), ArticleFig(id=1245407880195715233, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=CN, label=图14, caption=起飞和着陆过程节点占用与冲突区域分析, figureFileSmall=GEt7o5v9KjRAlrvcU+NJNw==, figureFileBig=WodQZl7uMYH9L3KnyVzVZA==, tableContent=null), ArticleFig(id=1245407880325738663, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=EN, label=Table 1, caption=

Static attributes of road network structure and their representations

, figureFileSmall=null, figureFileBig=null, tableContent=
属性名称 英文名称 符号
交叉口名称 intersection name IN
交叉口坐标 intersection coordinates IC
直行距离 straight-line distance SD
弯道距离 curved distance CD
入口宽度 entry width EW
交叉口关联节点 intersection associated nodes IAN
交叉口关联路径 intersection associated paths IAP
路段名称 segment name SN
路段坐标 segment coordinates SC
路段宽度 segment width SW
路段长度 segment length SL
翼展限制 wingspan restriction WR
速度限制 speed limit SL
路段关联节点 segment associated nodes SAN
路段关联路径 segment associated paths SAP
), ArticleFig(id=1245407880413819050, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=CN, label=表1, caption=

路网结构的静态属性及其表示

, figureFileSmall=null, figureFileBig=null, tableContent=
属性名称 英文名称 符号
交叉口名称 intersection name IN
交叉口坐标 intersection coordinates IC
直行距离 straight-line distance SD
弯道距离 curved distance CD
入口宽度 entry width EW
交叉口关联节点 intersection associated nodes IAN
交叉口关联路径 intersection associated paths IAP
路段名称 segment name SN
路段坐标 segment coordinates SC
路段宽度 segment width SW
路段长度 segment length SL
翼展限制 wingspan restriction WR
速度限制 speed limit SL
路段关联节点 segment associated nodes SAN
路段关联路径 segment associated paths SAP
), ArticleFig(id=1245407880518676659, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=EN, label=Table 2, caption=

Pseudocode for parameter calculation process

, figureFileSmall=null, figureFileBig=null, tableContent=
算法
输入:L,l,D,w1,w2, mass, engine_thrust, drag_coefficient, frontal_area, n1, n2, n3, n4, Ds, M
输出:Xi(t),Lo,Lr,Ls,o1,o2
1:初始化参数
2:动力学模型计算速度
3: v(t)=caculate_v(mass, engine_thrust, drag_coefficient, frontal_area)
4:计算Xi(t)
5:Xi(t)= caculate_Xi(t)(v(t),l,L,D)
计算Lo,Lr,Ls
Lo= caculate_Lo(Xi(t),l,L,D)
Lr= caculate_Lr(t)(Xi(t),l,L,D)
Ls= caculate_Ls(t)(Xi(t),l,L,D)
6:对头与追尾冲突判断
7: Compare(n1,n2)
8: while n1=n2 or n1+n2=0 do
if n1=n2 then
D1=caculate_D1(Lo1,Lr1)
D2=caculate_D2(Lo2,Lr2)
ΔD=D1-D2
D_Compare(ΔD, Ds)
If ΔD<Ds then
追尾冲突
End
Else n1+n2=0
D1=caculate_D1(L,Lo1,Lr1)
D2=caculate_D2(L,Lo2,Lr2)
ΔD=D1-D2
D_Compare(ΔD, Ds)
If ΔD<Ds then
对头冲突
End
End while
9:交叉冲突判断
10: Compare(n1, n2, n3, n4)
if n1+n2!=0 or n2+n3!=0 or n3+n4!=0 or n4+n1!=0
ΔL1(t)=caculate_ΔL1(L,l,D,w1,w2,M,Xi(t))
ΔL2(t)=caculate_ΔL2(L,l,D,w1,w2,M,Xi(t))
o1(t)=caculate_o1(L,l,D,w1,w2,M,Xi(t))
o2(t)=caculate_o2(L,l,D,w1,w2,M,Xi(t))
o(t)=(ΔL1(t)* ΔL2(t))/w2^2
if o(t)>0 then
交叉冲突
end if
end if
), ArticleFig(id=1245407880724197564, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=CN, label=表2, caption=

参数计算流程伪代码

, figureFileSmall=null, figureFileBig=null, tableContent=
算法
输入:L,l,D,w1,w2, mass, engine_thrust, drag_coefficient, frontal_area, n1, n2, n3, n4, Ds, M
输出:Xi(t),Lo,Lr,Ls,o1,o2
1:初始化参数
2:动力学模型计算速度
3: v(t)=caculate_v(mass, engine_thrust, drag_coefficient, frontal_area)
4:计算Xi(t)
5:Xi(t)= caculate_Xi(t)(v(t),l,L,D)
计算Lo,Lr,Ls
Lo= caculate_Lo(Xi(t),l,L,D)
Lr= caculate_Lr(t)(Xi(t),l,L,D)
Ls= caculate_Ls(t)(Xi(t),l,L,D)
6:对头与追尾冲突判断
7: Compare(n1,n2)
8: while n1=n2 or n1+n2=0 do
if n1=n2 then
D1=caculate_D1(Lo1,Lr1)
D2=caculate_D2(Lo2,Lr2)
ΔD=D1-D2
D_Compare(ΔD, Ds)
If ΔD<Ds then
追尾冲突
End
Else n1+n2=0
D1=caculate_D1(L,Lo1,Lr1)
D2=caculate_D2(L,Lo2,Lr2)
ΔD=D1-D2
D_Compare(ΔD, Ds)
If ΔD<Ds then
对头冲突
End
End while
9:交叉冲突判断
10: Compare(n1, n2, n3, n4)
if n1+n2!=0 or n2+n3!=0 or n3+n4!=0 or n4+n1!=0
ΔL1(t)=caculate_ΔL1(L,l,D,w1,w2,M,Xi(t))
ΔL2(t)=caculate_ΔL2(L,l,D,w1,w2,M,Xi(t))
o1(t)=caculate_o1(L,l,D,w1,w2,M,Xi(t))
o2(t)=caculate_o2(L,l,D,w1,w2,M,Xi(t))
o(t)=(ΔL1(t)* ΔL2(t))/w2^2
if o(t)>0 then
交叉冲突
end if
end if
), ArticleFig(id=1245407880845832388, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=EN, label=Table 3, caption=

Basic parameters of A320-200

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属性 参数
机型 A320-200
长度 37.57 m(123 ft 3 in)
翼展 34.10 m(111 ft 11 in)
机翼面积 122.6 m2(1 320 ft2)
高度 12.51 m(41 ft 1 in)
客舱宽度 3.70 m(12 ft 1 in)
轴距 12.64 m(41 ft 5 in)
轮距 7.59 m(24 ft 11 in)
机身宽度 3.95 m(13 ft)
机身高度 4.14 m(13 ft 7 in)
最大燃油容量 30 190 L
最大起飞重量 78 000 kg(172 000 lb)
发动机推力 120/98 kN(27 000/22 000 lb)
), ArticleFig(id=1245407880946495691, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=CN, label=表3, caption=

A320-200基础参数

, figureFileSmall=null, figureFileBig=null, tableContent=
属性 参数
机型 A320-200
长度 37.57 m(123 ft 3 in)
翼展 34.10 m(111 ft 11 in)
机翼面积 122.6 m2(1 320 ft2)
高度 12.51 m(41 ft 1 in)
客舱宽度 3.70 m(12 ft 1 in)
轴距 12.64 m(41 ft 5 in)
轮距 7.59 m(24 ft 11 in)
机身宽度 3.95 m(13 ft)
机身高度 4.14 m(13 ft 7 in)
最大燃油容量 30 190 L
最大起飞重量 78 000 kg(172 000 lb)
发动机推力 120/98 kN(27 000/22 000 lb)
), ArticleFig(id=1245407881047158992, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=EN, label=Table 4, caption=

Taxiing route table

, figureFileSmall=null, figureFileBig=null, tableContent=
路径 滑行路径资源节点编号
起飞滑
行路径
384-520-378-376-255-248-243-237-233-230-226-216-212-208-205-200-196-195-193-185-181-177-173-169-165-161-138-135-115-114-113-110-101-104-105-97-98-22-21
着陆滑
行路径
1-2-3-4-5-17-26-65-223-226-416-422-423-425-429-434-436-440-444-445-446
), ArticleFig(id=1245407881152016599, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1245407863041012583, language=CN, label=表4, caption=

滑行路径表

, figureFileSmall=null, figureFileBig=null, tableContent=
路径 滑行路径资源节点编号
起飞滑
行路径
384-520-378-376-255-248-243-237-233-230-226-216-212-208-205-200-196-195-193-185-181-177-173-169-165-161-138-135-115-114-113-110-101-104-105-97-98-22-21
着陆滑
行路径
1-2-3-4-5-17-26-65-223-226-416-422-423-425-429-434-436-440-444-445-446
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飞行区场面滑行资源时空图构建方法
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常鑫 , 陈香庆 , 杨威屏
科学技术与工程 | 论文·航空、航天 2025,25(7): 3044-3056
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科学技术与工程 | 论文·航空、航天 2025, 25(7): 3044-3056
飞行区场面滑行资源时空图构建方法
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常鑫 , 陈香庆, 杨威屏
作者信息
  • 中国民航大学交通科学与工程学院, 天津 300300
  • 常鑫(1991—),男,汉族,河南南阳人,博士,讲师。研究方向:智能交通及交通安全。E-mail:

Construction and Visualization of Spatiotemporal Graphs of Surface Movement Resources in Airport Flight Area
Xin CHANG , Xiang-qing CHEN, Wei-ping YANG
Affiliations
  • College of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
出版时间: 2025-03-08 doi: 10.12404/j.issn.1671-1815.2403444
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在机场自治化运行条件下,对于场面运行环境的感知是制约机场实现自治化运行的一个关键因素,而机场场面交通运行过程中对于场面滑行资源占用情况是构建完整的场面运行环境的关键步骤,首先以机场场面滑行过程为研究对象,构建了机场场面滑行过程的本体模型,基于机场的场面路网结构,对路网中的滑行路径进行划分,建立了以路网节点与节点连接关系为基础的“节点-边”模型,同时以本体模型为基础,定义了场面路网的动静态属性作为路网节点的基本属性,在此基础上,以路网节点为研究对象,将航空器场面滑行过程中的存在的多种冲突场景以路网节点的动态属性进行模型表达,从而实现了航空器滑行过程在路网节点上的动态表示。以航空器动力学模型生成的速度数据为基础,设计了在航空器冲突场景下的飞行区场面滑行资源动态图的可视化表示,试验结果表明,该模型可以很好地表示场面运行过程,可以增强场面交通参与者对飞行区场面滑行资源占用状况的全域感知能力。

智能交通系统  /  场面运行环境建模  /  动态图构建  /  场面冲突  /  本体建模

Under the condition of airport autonomous operation, perception of the operational environment is a crucial factor constraining the realization of autonomous airport operations. In the process of airport surface traffic operation, understanding the utilization of surface movement resources is a key step in establishing a comprehensive operational environment. The surface movement process at airports is first focused on in this study, and an ontology model for airport surface movement processes is constructed. Based on the structural layout of the airport surface road network, the movement paths were divided, and a "node-edge" model based on the connection between network nodes was established. Meanwhile, building upon the ontology model, dynamic and static attributes of the surface road network were defined as the basic properties of network nodes. With network nodes as the research object, various conflict scenarios existing in aircraft surface movement processes were modeled based on the dynamic attributes of network nodes, thus achieving a dynamic representation of aircraft movement processes at network nodes. Using speed data generated by aircraft dynamics models as a basis, a visualization representation of dynamic graphs of surface movement resource utilization in the presence of aircraft conflict scenarios was designed.Experimental results demonstrate that the model effectively represents both conflict and conflict-free scenarios in surface operations. This enhances the overall perception of surface movement resource utilization among participants in airport surface traffic.

intelligent transportation system  /  modeling of operational environments  /  construction of dynamic graphs  /  surface conflicts  /  ontological modeling
常鑫, 陈香庆, 杨威屏. 飞行区场面滑行资源时空图构建方法. 科学技术与工程, 2025 , 25 (7) : 3044 -3056 . DOI: 10.12404/j.issn.1671-1815.2403444
Xin CHANG, Xiang-qing CHEN, Wei-ping YANG. Construction and Visualization of Spatiotemporal Graphs of Surface Movement Resources in Airport Flight Area[J]. Science Technology and Engineering, 2025 , 25 (7) : 3044 -3056 . DOI: 10.12404/j.issn.1671-1815.2403444
随着航空运输业的快速发展,机场运行愈加繁忙,然而当前对于场面交通运行状况的管理还是以人工管理为主,这种方法虽然可以对场面交通运行状态实时监控,但一方面随着航空交通运行数量的增长,人工管理的弊端逐渐成为影响场面交通运行安全的一大因素,另一方面机场自治化转型与智慧机场建设最紧密相关,是实现航空运输未来发展愿景的最重要途径,已成为新一轮国际民航业竞争的重点领域[1]。《“十四五”民用航空发展规划》中提出实施民航科技创新要实现5G、人工智能、北斗系统、无人驾驶等技术与基础设施深度融合,推动重大科技成果民航应用。机场自治化是指通过借助新技术(数字化、信息化和自动化技术等)的应用,实现机场全系统运营规划和对变化的快速响应以及重新规划,以大幅提升航空运输效率和可靠性。机场场面运行过程是航空器和各类机场运行保障车辆在管制规则下,对场面滑行道/机坪的动态占用和释放的过程。建立能够反映场面运行态势的交通场景环境表征方法,并基于此开展场面运行活动轨迹规划和活动冲突控制,具有重要的科学和实践意义。
国内外学者已有许多学者对场面运行环境的建模进行了研究,并取得了一系列研究成果。夏正洪等[2]针对繁忙机场的飞行区场面运行特性进行分析并建立基于Petri网的场面活动模型。Wang等[3]通过使用时空图神经网络来预测机场滑行道网络中的交叉口状态。Li等[4]提出了一种基于多因素特征捕获的时空模型。吴昊等[5]建立多跑道运行全过程着色时延Petri网模型对进离港及场面运行流程进行分析。汤淼等[6]提出了一种基于面向多智能体系统(multi agent system,MAS) 的受控赋时着色Petri网的多跑道机场场面运行活动建模方法。依据表征形式,交通场景环境建模方法大致也可分为两类:栅格化表征和向量化表征。栅格化表征一般使用包含多个深度或颜色通道的图像数据对环境要素进行表示,每个通道表示不同的道路环境元素信息,而后输入循环神经网络或卷积神经网络进行建模。栅格化表征方法因其数据结构与摄像头、毫米波雷达等感知设备类似,是目前在机器学习和自动驾驶领域使用较为广泛的场景建模方法[7-9]。Bansal等[10]将车道、信号灯、限速、路线等元素使用7个俯视、固定分辨率或灰度图像分别表示,作为其算法网络的输入,然后使用一系列循环神经网络进行编码。向量化表征方法主要依托高精度地图,以道路交通元素为单位,逐个进行信息编码形成多个高维向量,实现场景表征[11-13]。在交通领域使用向量化表征对交通场景进行建模的研究中,胡伟超等[14]基于公路交通事故数据确定关键分类变量,构建场景风险特征表征参数,深入分析道路和环境因素对场景事故数量和发生事故严重程度的影响特征。向量化表征的优势在于对高精度地图信息的直接利用,较之基栅格化表征,数据维度小但表征能力强。并且,向量化表征是随着高度结构化的高精度地图供给产生的,将高精度地图重新渲染为图像再利用将不可避免地引入噪声或损失信息。因此,开展向量化的道路交通场景表征方法研究,将在未来飞行区场面自治化运行领域具有极大的理论研究价值和应用前景。
基于上述学者的研究,当前场面运行环境的建模主要分为两类方法:一种是基于有向图建模,这种方法将场面活动区建模“节点-路段”类模型。其中,节点代表活动区的若干关键区域,路段代表两相邻区域之间的滑行区域,并赋予了一定的属性,如路段长度及容量等。但这种方法对场面滑行过程的演化机理的描述不足。另一种是基于Petri网的建模,在离散事件动态系统中是一种逻辑层次的建模方法,它能很好地描述机场场面交通系统中的静态属性、动态响应行为,然而使用Petri网的方法的灵活性较差,对于时变信息和突发事件的表示缺少及时性。随着自动驾驶技术、机器学习等新技术的应用,对于场面运行环境的建模也需要与智能化系统和算法相结合,构建更加精细化的场面冲突检测表征方法和模型,通过场面运行数据,准确获得场面冲突随时空环境变化的动态变化。
以场面交通运行过程为背景,基于本体建模对航空器在场面滑行过程中航空器与机场路网交互所涉及的物理实体,以及不同物理实体在场面运行过程中所具备的动静态属性进行确定,并基于所构建的滑行过程的本体模型,基于“交叉口-路段”的划分方法,对飞行区场面路网结构进行离散化处理,并以离散后交叉口或路段为研究对象,构建飞行区路网结构的有向图模型,在此基础上,将路网结构中的静态和动态属性作为有向图中各节点的特征,构建航空器滑行资源动态图模型,并基于复杂网络分析软件Gephi设计案例对该模型进行可视化表示。
本体用于定义和分类数据的结构,为数据之间的语义关系提供了一个共有的框架。这种结构化和语义化的表达方式不仅增强了数据的可理解性和可用性,而且对实现跨领域知识的整合和共享具有深远的影响。为了确定飞行区场面滑行资源动态图中所包含的具体信息,首先需要对涉及构建该模型的相关概念进行定义,本体可以看作一种对领域知识进行描述的概念化模型,目前本体建模已在公路交通安全[14-15]、航天产品研制[16]与风险管理[17]等领域取得广泛应用。在民航领域中的飞机设计、空管人因建模等领域开展研究,在机场空侧方面的研究主要是场面热点划分和跑道侵入进行建模[18-19]。通过构建本体可以将知识进行细粒度划分。本体依据本体的层次和领域依赖度,本体可分为顶层本体、领域本体、任务本体和应用本体。
其中,领域本体用于支持特定领域内的推理、规划和决策。而机场飞行区场面交通运行过程的描述可以与其他相关的领域本体(如航空器本体、场面车辆本体)进行关联,因此机场飞行区场面交通运行过程的描述可以作为一个领域本体。
本体结构定义为O:(C,R,A,T,I),其中,类(C)表示领域知识的基本概念或种类;关系(R)表示类之间存在的属性关系;属性(A)表示类具有不同特征,即数据属性;数据集(T)表示属性的不同数据类型;实例(I)表示类所具有的不同个例。机场场面交通运行过程主要涉及场面交通实体类、静态属性类、动态属性类三个核心概念,其中场面交通实体是实现场面交通与运行过程的主体,静态属性类是场面交通运行过程中运行主体具有的非时变特征,动态属性是运行主体所具备的随时间变化的特征,本文中采用基于Java语言开发的本体编辑和知识获取开源平台Protégé 5.63进行本体编辑,构建航空器场面交通运行过程的本体模型如图1所示。
当前,关于场面运行环境的有向图建模方法,由于机场场面滑行区包括跑道、滑行道、联络道、交叉口、机坪和机位等结构单元,采用“点-边”形式的有向图G=(V,E)建模(V表示节点,如滑行道交叉口;E表示边,如滑行道等),但这种有向图结构只能对场面结构的几何关系进行描述,却无法有效刻画航空器在场面的滑行活动。此外,这种有向图模型对随时间变化的动态信息无法表示。因此,需要把有向图模型中的节点和边都视作场面滑行资源,并将动态信息作为滑行资源的动态属性,构建滑行资源动态图模型。
对于场面滑行资源动态图的构建,首先需要基于场面路网结构划分为“节点-边”模型,并基于上述场面交通运行过程本体模型中对于场面路网结构的动静态属性确定为滑行资源动态图的动静态特征。通过节点的动态属性随时间的变化,对场面运行状况进行动态描述。
在以往机场场面路网结构的建模过程中[20-22],对于“节点-边”模型的使用是以交叉口为图的节点,路段作为连接两个交叉口之间的边,通过对边赋予不同的权重来表示各节点之间连接关系,这种方法在滑行路径规划过程中具有简化路网结构的作用,侧重于航空器滑行路径规划功能,然而对场面滑行资源的占用情况的研究,提升对滑行资源的全域感知能力来说,该模型将路网中的关键节点(交叉口)中包含的滑行资源进行了简化,并且忽略了路段上的滑行资源。本文中针对该模型存在的缺陷,对常用的“节点-边”模型进行改进。
以常规的机场场面路网系统为研究对象,将场面路网结构做离散化处理,将场面路网结构划分为由弯道和直行路段相互关联的“弯道-路段”模型。并将弯道和路段统一视为构成机场场面路网结构的基础路网节点。即
V=VcVs
式(1)中:V为构成机场路网结构的路网节点集;Vc为由弯道所组成的路网节点集;Vs为由直行路段构成的路网节点集。
在机场路网结构中,交叉口的结构存在多种形式,常见的如十字形交叉口、T形交叉口等,此外,路网结构中的交叉口所定义的是在整个飞行区滑行系统中的交叉口,这种交叉口是广义上的交叉口,滑行道交叉口是该交叉口在滑行道系统中的一种特殊表示,在场面路网结构中交叉口可以通过上文中定义的“弯道-路段”模型中的弯道和路段作为基本结构进行建模,如图2所示。其中不同颜色的节点表示交叉口中的路段和弯道,边代表各节点之间的连接关系。
基于上述离散规则,将跑道、滑行道、停机坪三部分区域的路网结构中的路段和交叉口基本结构进行组合。上述结构可以将场面路网结构进行准确表达,该结构以无向图的形式G=(V,E)表示。其中V表示场面上各个弯道和路段的集合;E表示这些弯道和路段之间的连接关系。可表示为
$\left\{\begin{array}{l}V=\{{V}_{1},{V}_{2},\dots,{V}_{i},\dots {V}_{n}\}\\ E=\{{E}_{1},{E}_{2},\dots,{E}_{j},\dots {E}_{m}\}\end{array}\right.$
根据图论的相关知识可知,节点的连接关系可以通过邻接矩阵来表示,假设场面上的节点数量为 n,用 n 阶方阵 A 表示这些节点的连接关系,用 aij 表示方阵 A 中的元素,表达式为
aij=$\left\{\begin{array}{ll}1,& \mathrm{节}\mathrm{点}\mathrm{i}\mathrm{与}\mathrm{节}\mathrm{点}\mathrm{j}\mathrm{有}\mathrm{连}\mathrm{接}\mathrm{关}\mathrm{系}\\ 0,& \mathrm{节}\mathrm{点}\mathrm{i}\mathrm{与}\mathrm{节}\mathrm{点}\mathrm{j}\mathrm{无}\mathrm{连}\mathrm{接}\mathrm{关}\mathrm{系}\end{array}\right.$
图3所示的无向图为例,无向图中表示部分场面结构的连接关系,用邻接矩阵表示如图4所示。
基于场面交通运行过程的本体模型,对场面路网结构的静态要素进行分析,上一步中构建了路网结构的图模型,其中图的节点代表了路网结构中的交叉口或直行路段,因此,路网结构是以这两种路网结构的基本结构单元为基础构建的,动态图是随时间变化的复杂网络。链接和节点可能出现和消失。一个动态图可以表示为每一时刻下的静态图的组合,动态图可以表示为
Gt={Et,Vt,Fs(t),Fd(t),t}
式(4)中:Gtt时刻的图结构EtVt分别为t时刻存在的节点和边;Fs(t)为t时刻节点的静态特征,Fd(t)为t时刻节点的动态特征。本文所研究的路网静态属性表示的是路网结构在动态图中不随时间变化的基本属性,这些属性在动态图的可视化界面中不显示,具体静态属性如表1所示。
以场面路网结构为研究对象,场面冲突可以理解为场面路网结构中的某一条关联路径在某一时刻被多个场面运动目标占用,并且随着时间变化剩余路径长度逐渐接近安全距离的过程。在这一过程中设计以下四种指标。
(1)节点使用速度v(i,t):表示航空器在路网节点i上运动时,对于该航空器所行驶的当前路段来说,航空器前进的速度即代表了所行驶的路网节点i中被使用的路径,即航空器每一时刻的速度与航空器占用道面路网节点i的速度相同。该速度可用v(i,t)表示,t时刻路径使用速度与航空器的滑行速度关系为
v(i,t)=vt
式(5)中:v(i,t)为该节点的使用速度;vt为航空器(或其他交通参与者)在节点i上的实际滑行速度,二者在数值上相等,考虑到尾流的影响,对于节点i来说,速度范围从航空器开始启用该节点开始至尾流区域完全脱离该节点为结束。
(2)单位使用长度ΔXi(t):当航空器在路网节点i上滑行时,在t时刻到时刻t+1内,由于航空器的速度较大,在单位时间ΔT内的速度变化可以视为不变,因此路网使用速度在单位时间内也不变,因此单位时间内的路段使用长度的计算方法为
ΔXi(t)=v(i,t)ΔT
由于随着时间的变化,使用路径长度会随着航空器的移动不断延长,直到该航空器及其尾流影响距离完全脱离当前路网结构,因此路径的使用距离的计算式为
Xi(t)=ΔXi-1(t-1)+ΔXi(t)
(3)占用路径长度Lo(t):占用路径长度是指从航空器某个路网结构入口准备进入该路网结构开始计算,此时视为启用某条关联路径,随着航空器在该路径上的行驶距离逐渐延长,占用路径长度也会发生相应的变化,在直行路段上的占用路径长度Lo的计算方式如下。
设当前路段的长度为L,航空器的机身长度为l,航空器的尾流影响距离为D,则
L<l+D时,有
$L_{o}(t)=\left\{\begin{array}{ll} X_{i}(t), & 0 \leqslant X_{i}(t)<L \\ L, & L \leqslant X_{i}(t)<l+D \\ l+D+L-X_{i}(t), & l+D \leqslant X_{i}(t)<L+l+D \end{array}\right.$
式(8)中:在Xi(t)小于路径长度L时,占用路径的长度即为单位使用长度,当Xi(t)大于路径长度,小于机身长度l与尾流影响距离D时,此时该路径已完全处于航空器的运动范围内,路径被航空器完全占用,当Xi(t)大于机身长度l与尾流影响距离D并小于路径长度L和机身与尾流影响距离D之和时,此时该路段已逐渐脱离航空器的运动范围。
L>l+D时,有
$L_{o}(t)=\left\{\begin{array}{ll} X_{i}(t), & 0 \leqslant X_{i}(t)<l+D \\ l+D, & l+D \leqslant X_{i}(t)<L \\ l+D+L-X_{i}(t), & L \leqslant X_{i}(t)<L+l+D \end{array}\right.$
式(9)中:在Xi(t)小于机身与尾流影响距离时,占用路径的长度即为单位使用长度,当Xi(t)大于机身与尾流影响距离,小于路径长度时,此时该航空器已完全处于该段路径内,路径完全包含航空器,当Xi(t)大于路径长度并小于路径和机身与尾流影响距离之和时,此时该路段已逐渐脱离航空器的运动范围。
(4)释放路径长度Lr(t):航空器在当前路网结构上滑行时,由于航空器对路网结构的占用存在时间限制,即在航空器正常滑行时,对于当前路网结构的使用存在“未占用-占用-释放”三个过程,释放路径长度与占用路径长度共同用于判断航空器与当前路网结构交互过程。释放路径长度的统计式为
$L_{\mathrm{r}}(t)=\left\{\begin{array}{ll}0, & 0 \leqslant X_{i}(t)<l+D \\X_{i}(t)-l-D, & l+D \leqslant X_{i}(t)<L+l+D\end{array}\right.$
当单位使用长度小于机身与尾流影响距离时,此时该路段完全处于航空器的使用过程中,没有可以释放的滑行资源,当单位使用长度大于机身与尾流影响距离并下小于路径和机身与尾流影响距离之和时,航空器逐渐脱离该节点,所占用的滑行资源开始逐步释放。
(5)剩余路径长度Ls(t):通过计算可以得到路网结构的占用和释放路径长度,由于每一个路网结构的总长是路网结构静态属性,该属性不随着时间变化的常量,因此剩余路径长度的计算方法为
Ls(t)=$\left\{\begin{array}{ll}L-{X}_{i}\left(t\right),& 0\le {X}_{i}\left(t\right)L\\ 0,& L\le {X}_{i}\left(t\right)L+l+D\end{array}\right.$
当单位使用长度小于路径长度时,此时随着单位使用长度的增加,剩余路径长度逐渐减小,当单位使用长度大于路径长度时,在航空器完全脱离前,不再有剩余路径。
(6)关联路径方向n:航空器在场面滑行时,需要首先选择的关联路径,才能确保航空器可以从该路网结构想下一路网结构进行转移,对于交叉口或路段,关联路径是指在该结构单元上,从航空器驶入方向的前序路网结构到航空器驶出方向的后序路网结构,在当前结构上连通前后两个路网结构的路径,为便于计算,以十字交叉口为例,其关联路径按逆时针以此取自然数作为路径编码,由于大多数的路网结构存在双向使用情况,因此关联路径存在相反数,用以表示路网结构中关联路径在同一路径上不同方向的选择。如图5所示,关联路径的表示方法为:以当前机场的进场方向为正值,离场方向为负值。左侧图表示航空器进场路径中在该节点上所需要占用的关联路径,右侧图表示航空器离场时对该节点的路径使用。
航空器的追尾冲突是指在相同机场场面滑行冲突预测周期T内,两架航空器在同一滑行道进行跟进滑行时,航空器j在航空器i 尾部跟进滑行,且航空器j的滑行速度大于航空器i的滑行速度,两架航空器之间的距离随两架航空器的运行逐渐减小。
图6可知,对于场面路网结构来说,追尾冲突是该关联路段先后被两个运动目标使用,并且目标1以一定速度v1在某时刻t1进入该路段并沿该关联路段移动,此后目标2以速度v2在某时刻t2也进入该路段,且与目标1所使用的关联路段相同,此时分别计算目标1和2的占用路径长度和释放路径长度,比较不同时刻下的安全距离,若安全距离在持续缩小,则会发生追尾冲突。该过程的形式化描述为
$\left\{\begin{array}{l} D_{1}=L-L_{\mathrm{ol}}-L_{\mathrm{r} 1}-L_{\mathrm{o} 2}-L_{\mathrm{t} 2} \\ D_{2}=L-L_{\mathrm{o} 1}^{\prime}-L_{\mathrm{r} 1}^{\prime}-L_{\mathrm{o} 2}^{\prime}-L_{\mathrm{r} 2}^{\prime} \\ D_{2}<D_{1} \\ D_{1}-D_{2}<D \\ n_{1}+n_{2}=0 \end{array}\right.$
式(12)中:Lo1Lo2分别为目标1和目标2在前一时刻的路径占用长度;Lr1Lr2为目标1和目标2前一时刻的释放路径长度;D1D2为不同时刻的剩余路径间距;D为目标的最小安全间距;n1n2分别为目标所选择的关联路径。
对于两个移动目标在同一道面结构上运动时,对头冲突是该路段被两个运动目标使用,并且目标1以一定速度v1t1时刻从该结构的一侧进入该路段并沿关联路径运动,目标2以一定速度v2t2时刻从该路段的另一侧进入该路网结构并沿另一关联路径运动(图7),若发生对头冲突,此时该路段的两条关联路径是同一条引导线上不同方向的关联路径,此时分别计算目标1和目标2的占用路径长度和释放路径长度,比较不同时刻下的安全距离,若安全距离在持续缩小,则会发生对头冲突。该过程的形式化描述为
$\left\{\begin{array}{l} D_{1}=L-L_{\mathrm{o} 1}-L_{\mathrm{r} 1}-L_{\mathrm{a} 2}-L_{\mathrm{t} 2} \\ D_{2}=L-L_{\mathrm{o} 1}^{\prime}-L_{\mathrm{r} 1}^{\prime}-L_{\mathrm{o} 2}^{\prime}-L_{\mathrm{r} 2}^{\prime} \\ D_{2}<D_{1} \\ D_{1}-D_{2}<D \\ n_{1}+n_{2}=0 \end{array}\right.$
式(13)中:Lo1Lo2分别为目标1和目标2在前一时刻的路径占用长度;Lr1Lr2为目标1和目标2前一时刻的释放路径长度;D1D2为不同时刻的剩余路径间距;D为目标的最小安全间距;n1n2分别为目标所选择的关联路径。
场面目标在路网上运动时,除了在直行路段发生冲突外,更多的冲突类型是交叉口冲突,对于两个移动目标在同一交叉口上运动时,交叉口冲突是目标1以一定速度v1t1时刻从交叉口的一侧进入该交叉口并沿某一关联路径方向移动,此后目标2以一定速度v2t2时刻从交叉口的另一侧进入,且运动方向是指向交叉口的另一个关联节点,由于交叉口存在弯道和直行路段,因此交叉口冲突存在三种基本类型。以航空器滑行为例,第一种是两架航空器在十字交叉区域发生交叉冲突,图8中深红色区域是潜在发生交叉冲突的区域,第二种是航空器在弯道上发生对头或追尾冲突的弯道冲突,第三种是前机处于十字区域的直行路段处,后机处于弯道发生转向运动,两架航空器发生直行-弯道冲突,本文主要对前两种常见的交叉口冲突进行分析。
弯道冲突中的弯道冲突是指两个移动目标分别在同一包含弯道的引导线上的两条不同关联路径中发生交通过程,该种冲突类型与对头冲突的冲突逻辑类似,分别计算目标1和目标2的占用路径长度和释放路径长度,比较不同时刻下的安全距离,若安全距离在持续缩小,则会发生对头冲突。该过程的形式化描述为
$\left\{\begin{array}{l} D_{1}=L-L_{\mathrm{o} 1}-L_{\mathrm{r} 1}-L_{\mathrm{o} 2}-L_{\mathrm{r} 2}-A \\ D_{2}=L-L_{\mathrm{o} 1}^{\prime}-L_{1}^{\prime}-L_{\mathrm{o} 2}^{\prime}-L_{\mathrm{r} 2}^{\prime}-A \\ D_{2}<D_{1} \\ D_{1}-D_{2}<D \\ n_{1}+n_{2}=0 \end{array}\right.$
式(14)中:Lo1Lo2分别为目标1和目标2在前一时刻的路径占用长度;Lr1Lr2为目标1和目标2前一时刻的释放路径长度;A为弯道的实际长度;D1D2为不同时刻的剩余路径间距;D为目标的最小安全间距;n1n2分别为目标所选择的关联路径。
交叉冲突中的穿越冲突是指航空器在路网结构中的交叉处发生冲突的状况,此时若发生穿越冲突,是发生在以两架航空器的翼展宽度为边长的矩形区域中,本文中主要针对航空器发生交叉冲突的状况对穿越冲突中所涉及的冲突特征进行分析。
图9所示,航空器1是以速度v1t1时刻进入交叉口,其路径是沿水平方向通过该交叉口到达图右侧的下一路网结构,而航空器2是以速度v2t2(t2>t1)时刻进入交叉口,其路径是沿竖直方向通过该交叉口到达图上方的下一路网结构,此时航空器1已滑行至图右侧的虚线位置,需要判断这两架航空器是否会发生交叉冲突,首先,两架航空器先后进入该交叉口,航空器1作为前机,对该路网结构具有优先使用权,前机进入交叉口后,其对该结构的使用距离和占用距离会随着对结构的使用时间的延长而逐渐增加,其占用距离会逐渐覆盖图中的红色区域,红色区域是两架航空器发生冲突的区域,若在同一时间两架航空器同时抵达该区域,航空器会发生碰撞,此时,对于路网结构来说,两架航空器都会对该区域形成一定的占用面积,并且占用的面积相互之间会发生重叠,因此,可以将该区域的重叠面积与总面积的占比作为判断交叉冲突的一个指标,图10所示航空器重叠区域面积示意图,重叠面积占比的计算方法如下:首先计算前机在该面积区域所占用的纵向长度为
$\Delta L_{1}(t)=\left\{\begin{array}{ll}0, & 0 \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2} \\X_{i}(t)-X_{1}-\frac{1}{2} M_{2}+\frac{1}{2} w_{2}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2} \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2} \\w_{2}, & X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2} \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \\w_{2}-X_{i}(t)+l+X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2}+l \\0 & X_{i}(t) \geqslant X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2}+l\end{array}\right.$
式(15)中:M1M2为前机和后机所需穿行的交叉冲突区域直行长度;w1w2分别为前机和后机的翼展宽度;X1为前机进入交叉口至进入冲突区域之间的路径长度。
Xi(t)<X1+$\frac{1}{2}$M2-$\frac{1}{2}$w2时,此时航空器正在通过直行路段,此时冲突区域中被航空器占用的长度(占用长度)为零,当Xi(t)<X1+$\frac{1}{2}$M2+$\frac{1}{2}$w2时,航空器正在穿越交叉区域,当Xi(t)<X1+$\frac{1}{2}$M2-$\frac{1}{2}$w2+l时,此时机身未完全脱离交叉区域,当Xi(t)<X1+$\frac{1}{2}$M2+$\frac{1}{2}$w2+l时,此时机身已脱离该区域,而尾流影响区域未脱离该区域,当Xi(t)>X1+$\frac{1}{2}$M2+$\frac{1}{2}$w2+l时,此时航空器尾流区域脱离交叉区域,对于该区域的影响消失。同理,后机在该面积区域所占用的纵向长度为
$\Delta L_{2}(t)=\left\{\begin{array}{ll}0, & 0 \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \\X_{i}(t)-l-X_{1}-\frac{1}{2} M_{2}+\frac{1}{2} w_{2}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2}+l \\w_{2}, & X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2}+l \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l+D \\w_{2}-X_{i}(t)+l-D+X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l+D \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2}+l+D \\0, & X_{i}(t) \geqslant X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2}+l+D\end{array}\right.$
航空器在该区域所占用的面积区域为
Si(t)=ΔLi(t)wi
式(17)中:Si(t)为航空器i的占用面积;ΔLi(t)为航空器i的占用长度;wi为该航空器的翼展。航空器重叠区域的面积区域s和重叠区域在可潜在冲突区域的面积S(t)占比计算公式为
S(t)=w1w2
O(t)=$\frac{s}{S\left(t\right)}$
基于前后机的占用长度,结合航空器重叠区域面积的计算公式,可以得到前机的冲突区域的面积占比和后机对冲突区域的面积占比的计算方法分别为
$o_{1}(t)=\left\{\begin{array}{ll}0, & 0 \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2} \\\frac{X_{i}(t)-X_{1}-\frac{1}{2} M_{2}+\frac{1}{2} w_{2}}{w_{2}}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2} \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2} \\1, & X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2} \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \\\frac{w_{2}-X_{i}(t)+l+X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}}{w_{2}}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \\0, & X_{i}(t) \geqslant L_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l\end{array}\right.$
$o_{1}(t)=\left\{\begin{array}{ll}0, & 0 \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2} \\\frac{X_{i}(t)-X_{1}-\frac{1}{2} M_{2}+\frac{1}{2} w_{2}}{w_{2}}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2} \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2} \\1, & X_{1}+\frac{1}{2} M_{2}+\frac{1}{2} w_{2} \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \\\frac{w_{2}-X_{i}(t)+l+X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}}{w_{2}}, & X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \leqslant X_{i}(t)<X_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l \\0, & X_{i}(t) \geqslant L_{1}+\frac{1}{2} M_{2}-\frac{1}{2} w_{2}+l\end{array}\right.$
为验证本文中提出的场面滑行资源动态图对场面交通运行状态的动态表示,设计案例对场面交通运行过程与冲突状态进行测试,场面滑行资源动态图的总体流程如图11所示,数据生成以及冲突计算过程的逻辑如表2所示。
按机场运行规定,航空器的滑行速度不得超过50 km/h,约14 m/s,即航空器滑行速度v1v2在0~14 m/s。以两架空客A320 航空器(A320-200)的交通运行过程为例,对不同冲突场景中无冲突下的场面交通运行过程以及冲突状态进行动态图表示。空客A320的基础数据如表3所示。
其中选用质量、发动机推力、阻力系数和投影面积作为计算参数,计算方法采用速度的数值根据初始速度与最终速度的大小关系,分为三种情况进行处理。
(1)如果初始速度小于最终速度,则进入加速阶段。在加速阶段中,通过动力学公式计算加速度, 并根据时间步长不断更新速度,直到达到最终速度,然后保持匀速。
(2)如果初始速度大于最终速度,则进入减速阶段。在减速阶段中,同样根据动力学公式计算减速度,并不断更新速度,直到达到最终速度,然后保持匀速。
(3)如果初始速度等于最终速度,则保持匀速阶段。
以南京禄口机场06-24跑道部分的跑滑结构西北某机场的机场路网结构为基础,按照上述路网节点模型的构建方法,得到路网结构的“节点-边”模型,该路网结构的CAD图如图12所示,由于完整结构较大,为保证图片清晰度,本文中截取部分结构展示。在图中,每个节点都被赋予一个数字编号,用以区分不同节点。构成该机场路网节点共523个,节点之间的边数为769条。案例中,计划起飞滑行路径和着陆滑行路径上所经过的滑行资源节点编号如表4所示。
设计起飞和着陆航空器在节点226处发生交叉冲突。为设计出可能发生冲突的交叉冲突状况,需要控制航空器的运动时间,根据航空器滑行时间推算在着陆航空器接地8.62 s后起飞航空器开始滑行,此时可以得到着陆航空器的尾流影响范围内与起飞航空器发生区域冲突,冲突区域在方框区域内。
基于Gephi的航空器滑行资源动态图如图13所示。其中黄色节点表示当前场面节点正在被航空器的占用,绿色节点表示当前场面节点未被航空器占用以及占用后释放的状态。随着航空器在场面路网中的运动,场面路网中的各节点会基于航空器的占用状况变更节点颜色表示当前节点的使用状况。图13(a)的红色线条和图13(b)蓝色线条分别表示着陆航空器和起飞航空器的滑行路径,其中图13(a)红色实线部分表示着陆航空器在发生冲突前已通过的路径和图13(a)红色虚线部分表示着陆航空器在不发生冲突时的预计滑行路径。当节点由绿色转变为黄色时,表示该节点从未使用状态转变为使用状态,当节点从黄色转变为绿色时,表示该节点上的航空器脱离节点,该节点上的滑行资源被释放,图13(c)红色节点表示两架航空器在某节点处发生冲突。并在后续过程中使用保持冲突状况。本文中所选用的冲突场景为着陆航空器(前机)和起飞航空器(后机)在交叉口滑行过程中发生交叉冲突,图13(a)是基于Gephi构建的飞行区场面滑行资源动态图的总体界面,其中节点1处为黄色,表示此时着陆航空器在跑道滑行,此时所占用的是资源节点1,当航空器机身脱离该资源节点后,由于还有尾流间隔的影响,该区域还受到航空器的影响,因此会短暂的出现多个资源节点被占用的情况[图13(b)],当航空器发生冲突后[图13(c)],该节点转变为红色,表示此时在节点226处发生了运行冲突中的交叉冲突。由于发生了冲突,该点处的始终保持红色,滑行路径在此处中断,航空器的滑行过程结束。
根据前文中的路网资源动态属性的计算方法,无冲突状态下场面滑行资源的占用状况如图13所示。从图14(a)中可以看到,在起飞过程中,此时航空器需要从静止状态开始加速到正常的滑行速度, 此时航空器需要较长的时间加速,相对应的对于节点的占用也花费了较长的时间,此后随着航空器速度的提升,对于节点的占用也逐渐提升,此外航空器在起飞滑行过程中需要经过多个较短的滑行路段,因此在航空器滑行短路段多的滑行阶段,曲线的重叠范围也变得密集,在着陆滑行阶段[图14(b)],此时航空器的滑行速度较大,对于节点的占用速度也较快,达到完全占用节点所花费的时间也较少,且由于着陆过程中的滑行路段的长度较长,占用每个节点所花费的时间也相对更多。在冲突节点处,图14(c)表示前后机的占用长度随时间的变化曲线,前后机在冲突节点处对该节点的占用距离随时间的变化,所考虑的范围是从该节点的距离范围。图14(d)是重叠区域在潜在冲突区域中的占比曲线,可以看出,从前机进入交叉口开始计时,在1.02 s时,前机开始穿越潜在发生交叉冲突区域,在第3.46~3.7 s内前机完全占据交叉冲突区域,之后前机开始脱离该区域,同时后机开始进入该区域,两架航空器对该区域的占用存在重叠,此时开始出现重叠区域,重叠区域的面积占冲突区域的占比发生变化。
基于机场自治化场景下场面交通运行参与者对飞行区滑行资源占用情况的动态表示方法,首先,构建了机场场面交通者滑行过程的本体模型,并以“节点-边”模型为基础,对机场飞行区路网结构单元进行二次划分,构建了以直行路段和弯道为资源节点的“路段-弯道”模型。其次,在“路段-弯道”模型的基础上,通过分析场面路网结构的静态信息和分析滑行中“机-车-设施”交互过程,构建了动态交通场景要素集;同时,考虑航空器滑行时可能存在的冲突场景,以路网的动态属性为参数对航空器的冲突过程进行形式化描述。最后选取交叉口冲突场景进行案例分析,结合路网结构的动态属性,设计了判断冲突的算法流程并通过Gephi软件对冲突场景以动态图的形式进行可视化表达及结果分析。
  • 天津市教委科研计划(2024KJ094)
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2025年第25卷第7期
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doi: 10.12404/j.issn.1671-1815.2403444
  • 接收时间:2024-05-10
  • 首发时间:2026-03-30
  • 出版时间:2025-03-08
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  • 收稿日期:2024-05-10
  • 修回日期:2024-07-09
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天津市教委科研计划(2024KJ094)
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    中国民航大学交通科学与工程学院, 天津 300300
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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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