基于盛行交通流的终端空域运行风险评估方法

支婧文; 张军峰; 马曌

doi:10.3963/j.jssn.1674-4861.2025.02.002

基于盛行交通流的终端空域运行风险评估方法

doi: 10.3963/j.jssn.1674-4861.2025.02.002

南京航空航天大学民航学院南京 210016

基金项目:

国家自然科学基金项目 52372315

南京航空航天大学研究生科研与实践创新项目 xcxjh20230734

详细信息

作者简介:
支婧文（2021—），硕士研究生. 研究方向：交通运输规划与管理. E-mail：zhijingwen0405@163.com

通讯作者:
张军峰（1979—），博士，副教授. 研究方向：交通运输规划与管理、管制自动化与智能化、四维航迹管理等. E-mail：zhangjunfeng@nuaa.edu.cn

中图分类号: V355
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出版历程
- 收稿日期: 2024-07-30
- 网络出版日期: 2025-09-29

Operational Risk Assessment of Terminal Airspace with Prevailing Traffic Flow

College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

摘要

摘要: 运行风险的刻画及评估是提高空域运行的安全性及管理能力中的关键步骤，在结构复杂、起降交织的终端空域运行风险评估更是关键因素。传统碰撞风险模型多集中于事前单机冲突检测及固定航路碰撞风险，在表征终端空域运行结构及事后风险态势分析方面存在不足。针对终端空域运行风险评估问题，从终端空域航迹数据中通过聚类获得盛行交通流，提取其中冲突场景的几何构型，刻画包含航空器机动调整及空域复杂性的冲突结构及冲突场景。结合风险点中涉及交通流的时间、空间分布情况，挖掘历史运行中的空域风险信息，建立单位时间内的航空器预计碰撞次数作为终端空域的风险评估指标。通过对不同时空尺度的指标数值累加，能够实现不同时空域内的风险量化及热点发掘，并对风险较高的交通流及风险热点提供预警，为后续管制调配、战术规划及空域建设提供指导。结果表明：该模型能够很好的表征空域运行风险并发现风险热点，以广州白云机场终端空域为例，发现该空域存在以下运行风险类型及时空风险热点：进场与进场之间的运行风险是广州终端空域的主要风险；VIBOS离场交通流在广州白云机场北向运行时需要重点关注；下午13：00—14：00，以及夜间22：00—02：00是广州终端空域安全运行需要着重考量的时间段。
- 交通安全 /
- 碰撞风险 /
- 终端空域 /
- 盛行交通流 /
- 航迹聚类
Abstract: The characterization and assessment of operational risks represent critical steps in enhancing airspace operational safety and management capabilities, particularly in structurally complex terminal airspaces with multiple intersecting arrival and departure flows. Traditional collision risk models predominantly focus on preemptive single-aircraft conflict detection and fixed-routes, exhibiting limitations in characterizing terminal airspace operational structures and analyzing post-conflict risks. This study develops a methodology that extracts prevalent traffic flows from historical trajectory data through clustering, which identifies geometric configurations of conflict scenarios and incorporating aircraft maneuvering adjustments. By analyzing the spatiotemporal distribution in risk-prone areas, an assessment metric defined as the expected collision frequency per unit time was constructed to quantify the operational risk. Cumulative aggregation across diverse temporal and spatial scales enables risk quantification and hotspot identification, thereby facilitating operational evaluations, early warnings for high-risk traffic flows and spatiotemporal hotspots, and providing guidance for air traffic control, tactical planning, and airspace construction. A case study of Guangzhou Baiyun Airport validates the model's effectiveness in risk characterization and hotspot detection, Key findings include: Conflict risks between arrival flows constitute the primary risk category; The departure flow of VIBOS requires attention under northbound operation; Temporal risk hotspots are concentrated between 13:00—14:00 and 22:00—02:00.
- traffic safety /
- collision risk /
- terminal airspace /
- prevailing traffic flow /
- trajectory clustering

HTML全文

图 1 终端空域运行风险评估技术路线图

Figure 1. Technical roadmap for risk assessment of terminal airspace operation

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图 2 DBSCAN聚类中的集群1

Figure 2. Cluster 1 in DBSCAN clustering

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图 3 对集群1二级聚类产生的4个子集群

Figure 3. Four sub-clusters generated by second-level clustering of cluster 1

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图 4 航空器水平重叠示意图

Figure 4. Schematic diagram of horizontal overlap of two aircraft

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图 5 广州机场进离场航迹示意图

Figure 5. Diagram of arrival and departure trajectories in ZGGG

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图 6 广州机场进离场盛行交通流中心轨迹示意图

Figure 6. Central trajectories diagram of arrival and departure prevailing traffic flow in ZGGG

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图 7 #AA类别构成交叉点交通流示意图

Figure 7. Traffic flow diagram at the intersection points of #AA category

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图 8 #DD类别构成交叉点交通流示意图

Figure 8. Traffic flow diagram at the intersection point of #DD category

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图 9 #AD类别的交叉点示意图

Figure 9. Intersection point diagram of #AD category

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图 10 #AA类别风险时间分布折线图

Figure 10. Risk time distribution line chart of #AA category

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表 1 不同类型交叉点的分布

Table 1. Distribution of different types of intersections

类别	个数	占比/%
#AA	46	27.5
#AD	65	38.9
#DD	56	33.6

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表 2 交叉点预计的月累计碰撞风险

Table 2. Estimated monthly collision risk at intersections

类别	轨迹簇1	轨迹簇2	PH	NCol
	#1	#5	2.15×10^-04	3.04×10^-04
#AA	#0	#6	9.49×10-05	2.65×10^-04
	#0	#6	1.27×10^-04	1.00×10^-04
	#5	#17	1.30×10^-13	1.52×10^-13
#AD	#1	#17	7.66×10^-15	5.73×10^-16
	#3	#17	4.20×10^-16	3.17×10^-17
	#11	#12	6.16×10^-04	2.68×10^-02
#DD	#15	#16	2.27×10^-11	6.32×10^-12
	#15	#16	4.35×10^-12	1.64×10^-12

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