无人机低空飞行障碍物环境风险评估方法研究——以京津新城为例

doi:10.18306/dlkxjz.2021.09.006

Abstract

Abstract:

Unmanned aerial vehicle (UAV) is increasingly widely used, but with the continuous progress of urban development, the safe operation of UAV in cities is increasingly more prominent. Therefore, environmental risk assessment of obstacles has become one of the key issues in the field of low-altitude UAV research. In this study, taking the Beijing-Tianjin New Town as an example, the low-altitude airspace was divided into micro, light, and small UAV flight zones according to the low-altitude UAV types and operating heights. Based on the shape and size of UAVs, their motion constraints, and obstacle constraints, this research proposed an algorithm for approximation point expansion. The algorithm generates an expanded boundary on the basis of the original boundary of the obstacles, and this expanded boundary serves as a transitional zone between high risk and low risk areas in the low-altitude flight environment. Based on the UAV image data of 0.5 m resolution in the Beijing-Tianjin New Town in 2019, this study extracted obstacle elements in different assessment areas, and generated low-altitude flight obstacle environmental risk maps for different UAV types and different heights based on the risk assessment. The study area was divided into high-risk zone, high-risk transitional zone, medium-risk zone, and low-risk zone according to the threat posed to UAVs. The results show that: 1) The risk transitional zone in the micro, light, and small UAV control areas in the study area accounted for 10.9%, 7.3% and 9.0%, respectively, and the sharp-angle convex vertex optimization of the approximate point expansion algorithm can save about 1% of the airspace resources. 2) The proposed method can calculate the potential collision risk area of the UAVs in the flight area based on the mutual influence of the UAVs and the obstacles, and realize the effective assessment of the environmental risk of the low-altitude obstacles and provide a scientific reference for the navigability of the UAVs of different types in the flight area.

Key words: UAV, low-altitude flight environment, approximate expansion algorithm of polygons, risk map, Beijing-Tianjin New Town

HE Hongbo, XU Chenchen, YE Huping. Environmental risk assessment of obstacles in low-altitude flight of unmanned aerial vehicle: Taking the Beijing-Tianjin New Town as an example[J].PROGRESS IN GEOGRAPHY, 2021, 40(9): 1503-1515.

Figures/Tables 14

Fig.1

Fig.2

Fig.3

Tab.1

Distance limitation between UAV and various obstacles

障碍物等级	障碍物类型	不同类型的无人机应保持的最小距离
障碍物等级	障碍物类型	微型 $D lim 1$	轻型 $D lim 2$	小型 $D lim 3$
Ⅰ	民用航路	10 km
Ⅰ	国界线、边境线	我方一侧5 km
Ⅱ	军事机场净空区、民用机场障碍物限制面	2 km
Ⅱ	有人驾驶航空器临时起降点	2 km
Ⅲ	军事禁区及管理区、党政机关、核电站	10 m	20 m	1000 m
	易燃易爆危险品相关企业和仓库、电力设施、加油站、车站码头	10 m	20 m	1000 m
	高塔、电网、风力发电	5 m	10 m	1000 m
Ⅳ	建筑物、高铁、公路	5 m	10 m	500 m
Ⅳ	电线杆、交通设施	5 m	5 m	200 m
Ⅴ	农田、树林、江河湖泊、操场、山川、无人机飞行验证场	获得空域申请后,保证安全前提下,可以飞行

Tab.1

Fig.4

Tab.2

Environmental risk factors for UAV low-altitude operation based on aircraft type and altitude

无人机类型	政策规定安全距离 $D lim$	自身性能安全距离 $D 1$	运行高度H/m	适用场景
微型	$D lim 1$	$V n τ + 12 max (a, b)$	<50	城市航拍/农林植保
轻型	$D lim 2$	$V n τ + 12 max (a, b)$	50~120	城市低空快递/安防监控/公共安全
小型	$D lim 3$	$L min + V n τ + 12 max (a, b)$	120~300	应急救援/空中测绘

Tab.2

Tab.3

Tab.4

Fig.5

Tab.5

Fig.6

Fig.7

Fig.8

Fig.9

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障碍物要素等级	障碍物要素	风险值划定
障碍物要素等级	障碍物要素	原边界内风险值	风险过渡区风险值
Ⅰ	民用航路、国界线	999	900
Ⅱ	机场净空区、机场障碍物限制面	888	800
Ⅲ	军事禁区、核电站、党政机关、易燃易爆物品仓库、加油站、电力设施、车站码头	666	600
Ⅳ	建筑物、路灯、电线杆、高铁、公路	99 70	89 69
Ⅴ	树林、山川、操场农田、水体、无人机飞行验证场	50 30

风险区域	风险指数阈值	风险区描述
高风险区	>0.86	多为飞行限制区以及影响无人机正常飞行的障碍物
高风险过渡区	0.70~0.86	根据无人机机型、障碍物约束得到的风险缓冲区
中风险区	0.28~0.70	无人机在该区域内飞行有潜在航行风险
低风险区	<0.28	无人机在该区域内飞行风险较低

相关参数	微型无人机	轻型无人机	小型无人机
型号	大疆Mini 2	大疆御Mavic 2	智航V330
类型	多旋翼无人机	多旋翼无人机	垂直起降固定翼无人机
长、宽、高/mm	159×203×56	322×242×84	1650×3300×680
机身重量/g	249 g	905g	15000g
最大飞行高度/m	500	500	3500
最大水平飞行速度/(km/h)	40	72	91
续航/min	25~30 min	25~30	90
最小转弯半径	无	无	30 m
障碍物扩张距离参数影响因子	外形+障碍物等级约束	外形+障碍物等级约束	外形+最小转弯半径 +障碍物等级约束

Environmental risk assessment of obstacles in low-altitude flight of unmanned aerial vehicle: Taking the Beijing-Tianjin New Town as an example

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