考虑风险异质传播的航空多阶段运行风险演化分析

doi:10.16097/j.cnki.1009-6744.2025.05.027

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (5): 302-311.DOI: 10.16097/j.cnki.1009-6744.2025.05.027

考虑风险异质传播的航空多阶段运行风险演化分析

刘钊瑄¹，周哲旭¹，方晶^*2

1. 北京交通大学，交通运输学院，北京100044；2.民航数据通信有限责任公司，北京100083

收稿日期:2025-07-11 修回日期:2025-08-11 接受日期:2025-08-15 出版日期:2025-10-25 发布日期:2025-10-25
作者简介:刘钊瑄(1993—)，女，山东高密人，讲师，博士。
基金资助:
国家自然科学基金(62301025)；民航协同空管技术与应用重点实验室开放课题基金(ADCC-HTKY-2024-008)。

Aviation Multi-stage Operational Risk Evolution Under Heterogeneous Risk Propagation Mechanisms

LIU Zhaoxuan¹, ZHOU Zhexu¹, FANG Jing^*2

1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 2. Aviation Data Communication Corporation, Beijing 100083, China

Received:2025-07-11 Revised:2025-08-11 Accepted:2025-08-15 Online:2025-10-25 Published:2025-10-25
Supported by:
National Natural Science Foundation of China (62301025)；Open Fund of the Key Laboratory for Civil Aviation Collaborative Air Traffic Management Technology and Applications (ADCC-HTKY-2024-008)。

摘要/Abstract

摘要： 航空运行风险因素演化分析对于民航持续安全运行有着重要作用。当前研究主要聚焦于单一运行阶段的同质化风险传播，较少关注多运行阶段的异质化风险演化。本文以航空器巡航阶段和进离场阶段为研究对象，首先，构建涵盖人员、设备、环境和管理这4个维度的多阶段运行风险有向网络，并引入节点度、接近中心性、介数中心性及PageRank等代表性节点重要性指标识别关键风险要素；其次，考虑到风险节点间复杂关联作用关系，分别采用概率传播、鲁棒传播和SIR传播表征3类异质风险传播过程。结果表明：飞机姿态异常、冲偏出跑道、两机危险接近及紧急下降等关键节点为多阶段航空运行网络的重要风险节点；3种异质风险传播模型下，基于节点度值的识别方法在概率传播和传染病模型(SIR)传播下的风险扩散效应最为显著，鲁棒传播模型下，基于PageRank重要度分值的准确性最高；对于参数敏感性分析实验发掘的节点风险传导参数和网络风险扩散参数双高节点，设置针对性的扩容等冗余措施，可显著提升网络安全性，且中间节点的增容效果普遍优于初始节点。

关键词: 航空运输, 航空安全, 多阶段运行, 异质风险传播, 灵敏度分析

Abstract: Aircraft operational risk analysis is essential for civil aviation safety guarantee. Current studies mainly focus on homogeneous risk propagation during one operational phase, while research on heterogeneous risk propagation across multiple phases is limited. This paper investigates both the cruise and approach/departure phase by constructing directed risk networks covering: personnel, equipment, environment, and management. Typical node influence metrics are introduced including node degree, closeness centrality, betweenness centrality, and PageRank. Besides, three models, i.e., probabilistic, robust and Susceptible Infected Recovered (SIR) are employed to characterize heterogeneous risk propagation. Results indicate that critical nodes such as abnormal flight states, runway excursion, near miss, and emergency descent are of paramount importance in the multi-phase operation risk network. Among the three propagation models, node degree-based identification exhibits the most significant risk diffusion effects under both the probabilistic and SIR models, whereas PageRank has the highest accuracy under the robust propagation model. The parameter sensitivity analysis reveals that nodes with both high transmission and diffusion parameters represent key vulnerabilities. Targeted redundancy measures, such as capacity enhancement, can significantly improve network safety. Notably, reinforcing intermediate nodes proves to be more effective than reinforcing initial nodes.

Key words: air transportation, aviation safety, multi-stage operations, heterogeneous risk propagation, sensitivity analysis

中图分类号:

刘钊瑄, 周哲旭, 方晶. 考虑风险异质传播的航空多阶段运行风险演化分析[J]. 交通运输系统工程与信息, 2025, 25(5): 302-311.

LIU Zhaoxuan, ZHOU Zhexu, FANG Jing. Aviation Multi-stage Operational Risk Evolution Under Heterogeneous Risk Propagation Mechanisms[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(5): 302-311.

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考虑风险异质传播的航空多阶段运行风险演化分析

Aviation Multi-stage Operational Risk Evolution Under Heterogeneous Risk Propagation Mechanisms

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