考虑空中碰撞风险的UAV运行风险评估

doi:10.16265/j.cnki.issn1003-3033.2025.10.0894

摘要/Abstract

摘要： 为提高无人机(UAV)空中交通管理效率、保障飞行安全以及推动UAV在复杂空域环境中的安全应用,聚焦于UAV运行风险评估。首先,针对非结构化空域环境下具有自主感知与决策能力的UAV,基于机载通信导航监视能力、机动特性及系统响应时间等关键参数,构建冲突概率模型和考虑避让机动策略的碰撞概率模型,量化评估空域碰撞风险;然后,鉴于UAV相撞事故不会直接导致人员伤亡,构建综合考虑UAV空中相撞事件与系统失效引发坠机的地面风险评估模型;最后,以1×10^-6死亡人数/飞行小时作为安全目标水平,确定空中飞行所需保持的的安全间隔。结果表明:同时考虑冲突概率和冲突升级为碰撞的概率,可解决自由飞行阶段风险被低估的问题;不同运行场景可容许的碰撞风险最大值有较大差异。

关键词: 无人机(UAV), 运行风险, 碰撞风险, 地面风险, 安全间隔

Abstract:

To improve the efficiency of UAV air traffic management, ensure flight safety and promote the safe application of UAVs in complex airspace environments, the risk assessment of UAV operation was focused in this paper. Firstly, for UAVs with autonomous perception and decision-making capabilities in unstructured airspace environments, based on key parameters such as airborne communication, navigation and surveillance capabilities, maneuvering characteristics and system response time. A conflict probability model and a collision probability model considering avoidance maneuvering strategies were constructed to quantitatively evaluate the airspace collision risks. Then, considering that UAV collision accidents do not directly cause casualties, a ground risk assessment model was constructed that comprehensively considers UAV aerial collision events and crashes caused by system failures. Finally, taking 1×10^-6 deaths/flight hours as the safety target level, the safety separation that needs to be maintained during airborne flights was determined. The results show that considering both the conflict probability and the probability of the conflict escalating into a collision simultaneously can solve the problem of underestimated risks during the free flight stage. The maximum allowable collision risk varies significantly among different operating scenarios.

Key words: unmanned aerial vehicle (UAV), operation risk, collision risk, ground risk, safety interval

中图分类号:

X949

李楠, 闫博芸, 孙廪实, 韩鹏, 郑志刚, 焦庆宇. 考虑空中碰撞风险的UAV运行风险评估[J]. 中国安全科学学报, 2025, 35(10): 91-97.

LI Nan, YAN Boyun, SUN Linshi, HAN Peng, ZHENG Zhigang, JIAO Qingyu. Risk assessment of UAV operation considering risk of mid-air collision[J]. China Safety Science Journal, 2025, 35(10): 91-97.

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参考文献 18

[1]	GOODCHILD A, TOY J. Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO₂, emissions in the delivery service industry[J]. Transportation Research Part D: Transport and Environment, 2017, 61: 58-67. doi: 10.1016/j.trd.2017.02.017
[2]	GERARDO O, THOMAS L, LUIS G, et al. UAS airborne collision severity evaluation, final report volume I[R]. Department of Transportation Federal Aviation Administration, USA, 2017.
[3]	TAN Dayang, CHI Wanchao, MOHAMED S M F B, et al. Study on impact of separation distance to traffic management for small uas operations in urban environment[M]. Transdisciplinary Engineering:A Paradigm Shift. Amsterdam: IOS Press, 2017: 39-46.
[4]	张洪海, 李博文, 刘皞, 等. 自由空域下多旋翼无人机安全间隔标定方法[J]. 系统工程与电子技术, 2023, 45(10): 3149-3156. doi: 10.12305/j.issn.1001-506X.2023.10.19
	ZHANG Honghai, LI Bowen, LIU Hao, et al. Demarcation method of safety separation for multi-rotor UAV in free airspace[J]. Systems Engineering and Electronics, 2023, 45(10): 3149-3156. doi: 10.12305/j.issn.1001-506X.2023.10.19
[5]	励瑾, 钟罡, 张晓玮, 等. 城市低空无人机空中碰撞风险计算方法研究[J]. 现代交通与冶金材料, 2022, 2(5): 20-30.
[6]	WEIBEL R E, HANSMAN R J. Safety considerations for operation of unmanned aerial vehicles in the national airspace system: ICAT-2005-1[R]. Massachusetts Institute of Technology, 2005.
[7]	DALAMAGKIDIS K, VALAVANIS K P, PIEGL L A. On integrating unmanned aircraft systems into the national airspace system[M]. Netherlands: Springer, 2009: 21-49.
[8]	CHE MAN M H, HU Haoliang, LOW K H. Crash area estimation for ground risk of small unmanned aerial vehicles due to propulsion system failures[C]. AIAA Scitech 2022 Forum, 2022: 1506-1522.
[9]	MILANO M, PRIMATESTA S, GUGLIERI G. Air risk maps for unmanned aircraft in urban environments[C]. 2022 International Conference on Unmanned Aircraft Systems (ICUAS), 2022: 1073-1082.
[10]	JIAO Qingyu, LIU Yansi, ZHENG Zhigang, et al. Ground risk assessment for unmanned aircraft systems based on dynamic model[J]. Drones, 2022, 6(11): 324-352. doi: 10.3390/drones6110324
[11]	韩鹏, 赵嶷飞. 基于飞行环境建模的UAV地面撞击风险研究[J]. 中国安全科学学报, 2020, 30(1): 142-147. doi: 10.16265/j.cnki.issn1003-3033.2020.01.022
	HAN Peng, ZHAO Yifei. Study on ground impact risk of UAV based on flight environment[J]. China Safety Science Journal, 2020, 30(1): 142-147. doi: 10.16265/j.cnki.issn1003-3033.2020.01.022
[12]	JAR-DEL-WG6-D.04,Guidelines on specific operations risk assessment (SORA)[S]. 2019.
[13]	岳仁田, 马赵飞. 基于几何关系的无人机低空飞行冲突探测与解脱策略[J]. 中国安全科学学报, 2023, 33(5): 112-120. doi: 10.16265/j.cnki.issn1003-3033.2023.05.2049
	YUE Rentian, MA Zhaofei. Detection and resolution strategy of UAV low-altitude conflict based on geometric relations[J]. China Safety Science Journal, 2023, 33(5): 112-120. doi: 10.16265/j.cnki.issn1003-3033.2023.05.2049
[14]	SHINSUKE E. Aircraft collision models[R]. Massachusetts Institute of Technology, 1982.
[15]	USA Department of Transportation Federal Aviation Administration,AC No: 431.35-1.Expected casualty calculations for commercial space launch and reentry missions[Z]. 2013.
[16]	SHIVELY R J, VU K P L, BUKER T J. Unmanned aircraft system response to air traffic control clearances[J]. Human, 2013, 57(1): 31-35.
[17]	STELZER E K, MORGAN C E, MCGARRY K A, et al. Human-in-the-loop simulations of surface trajectory-based operations[C]. Ninth USA/Europe Air Traffic Management Research and Development Seminar, 2012: 1-12.
[18]	李亚飞, 刘明欢, 王莉莉. 建筑物影响下的无人机城区运行风险评估[J]. 中国安全科学学报, 2022, 32(7): 136-142. doi: 10.16265/j.cnki.issn1003-3033.2022.07.1226
	LI Yafei, LIU Minghuan, WANG Lili. Risk assessment of urban UAV operation under influence of buildings[J]. China Safety Science Journal, 2022, 32(7): 136-142. doi: 10.16265/j.cnki.issn1003-3033.2022.07.1226

驾驶员响应时间	数据通信传输延迟与驾驶员认知决策耗时	系统执行与界面显示滞后	合计
μ	7.63	4.38	12.01
σ	5.66	2.75	6.29

空中交通管制响应时间	告警反应	操作持续时长	合计
μ	4.6	2.3	6.9
σ	4.1	2.7	4.9

场景编号	场景特征	人口密度/ (人·km^-2)	遮蔽系数
1	山地农林、自然保护区、边境等人口稀少且植被茂盛的地区	100	6
2	人口密度较高的城市郊区	1 000	3
3	城市居民区、商业区等人口密度极大且几乎无遮蔽物的地区	10 000	1

安全间隔/m	冲突频率	碰撞概率	空中碰撞风险
2 200	1.29	1.68×10^-6	2.18×10^-6
2 300	1.41	3.12×10^-7	4.41×10^-7
2 400	1.53	5.23×10^-8	8.04×10^-8
2 500	1.67	7.88×10^-9	1.31×10^-8
2 600	1.80	1.07×10^-9	1.93×10^-9

运行场景	安全目标水平	最大允许碰撞风险	地面风险	安全间隔/m
1	1×10^-6	3.89×10^-3	6.76×10^-9	1 600
2	1×10^-6	1.03×10^-4	3.14×10^-7	2 000
3	1×10^-6	—	5.32×10^-6	—