城市低空无人机飞行计划协同推演与优化调配方法

doi:10.7527/S1000-6893.2024.30018

Abstract

Abstract:

To address the problems of multiple aircraft coordination constraints， frequent conflict risks， and operational inefficiencies faced by UAV cluster flights in complex urban environments， a collaborative deduction and optimal allocation method for urban low-altitude UAV flight plan is proposed. Firstly， for the UAV “individual”， the conflict between UAVs and urban static environment targets is considered， and a three-dimensional path planning method based on probabilistic risk maps is constructed to achieve the initial generation of UAV flight plan. Then， for the UAV “group”， considering the conflict between UAVs， a multi-type conflict cooperative deduction model for UAV flight plan is constructed， and the conflict characteristic indicators such as conflict occurrence rate， conflict risk level， and grid occupancy ratio are designed and metricized. Finally， diversified allocation strategies such as adjusting flight paths， flight speeds， and flight times are designed. Based on the multi-strategy self-adaptive configuration， an optimization and allocation model is established. The optimization performance and parameter sensitivity of the proposed method are verified， demonstrating the optimization performance and parameter sensitivity of urban low-altitude flight plans under different traffic density scenarios. Experiments show that the proposed method can reduce flight plan conflicts by 96.2% on the basis of effectively controlling the risk cost and time cost， completely conflict free flight plan can be obtained for UAV operation scenarios with less than 40 UAVs， and the minimum flight conflict resolution rate for UAVs with less than 100 UAVs can be controlled above 95%. The proposed method is scientific and effective， and can provide a theoretical basis and methodological guidance for safe and efficient management of low-altitude UAV flight activities in complex cities.

Key words: urban low altitude, UAV, air traffic management, flight plan, conflict detection and resolution, operational optimization

CLC Number:

V355

Hua XIE, Site HAN, Jianan YIN, Xiaohui JI, Yichen YANG. Cooperative deduction and optimal allocation method for urban low-altitude UAV flight plan[J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(19): 330018.

Figures/Tables 32

Fig.1

Fig.2

Fig.3

Table 1

Fig.4

Table 2

Table 3

Parameters of conflict detection experiments

参数		数值
决策变量	$x$	［1，100］
	$y$	［1，100］
	$z$	［1，5］
	$v$ /（m·s^-1）	［5，20］
冲突判别因子	$Δ t c o n_t h$	10

Table 3

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Table 4

Parameters related to simulation experiments

基本变量	数值	约束阈值	数值	算法参数	数值
$x$	［1，100］	$Δ t c o n_t h$ /s	10	$p_c r o s s$	0.7
$y$	［1，100］	$t d e l a y m a x$ /s	600	$p_m u t$	0.15
$z$	［1，5］	$T b a t t e r y n$ /s	1 800	$μ$	0.02
$v$ /（m·s^-1）	［5，20］			$n P o p$	100

Table 4

Fig.13

Table 5

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Fig.18

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Table 6

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Fig.25

Table 7

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评价指标	条件	任务1	任务2
路径长度/m	基于风险地图	3 331.862 9	3 777.582 7
路径长度/m	不基于风险地图	3 211.735 4	3 553.962 5
算法时间/s	基于风险地图	3.863 8	3.314 5
算法时间/s	不基于风险地图	1.010 9	0.420 0
转弯数量	基于风险地图	14	11
转弯数量	不基于风险地图	15	19

解的前置条件	目标函数	调整飞行路径	调整飞行速度	调整飞行时间	自适应策略
初始航路网络	风险成本	4.711 9	4.711 9	4.711 9	4.711 9
	时间成本/s	25 159	25 159	25 159	25 159
	冲突数量	105	105	105	105
风险成本最小的非支配解	风险成本	4.654 1	4.711 9	4.711 9	4.679 2
	时间成本/s	26 756	120 966	56 777	38 499
	冲突数量	33	4	3	21
时间成本最小的非支配解	风险成本	4.695 7	4.711 9	4.711 9	4.711 6
	时间成本/s	25 145	120 954	56 777	31 614
	冲突数量	41	4	3	33
冲突数量最小的非支配解	风险成本	4.748 0	4.711 9	4.711 9	4.718 3
	时间成本/s	27 639	120 966	56 779	40 996
	冲突数量	13	2	2	4

拟合方法	目标函数	SSE	Adjusted R-square	RMSE	#Coeff
正弦曲线逼近	时间成本	7.929×10^-5	0.999 5	9.089×10^-4	3
正弦曲线逼近	冲突数量	1.237×10^-8	0.998 2	1.135×10^-5	3
高斯逼近	时间成本	7.612×10⁸	0.992 2	2 801	3
高斯逼近	冲突数量	116.4	0.997 7	1.095	3
指数逼近	时间成本	1.761×10¹⁰	0.822 6	1.340 3×10⁴	2
指数逼近	冲突数量	1 448	0.971 2	3.843	2
威布尔逼近	时间成本	1.640×10¹²	-15.53	1.294×10⁵	2
威布尔逼近	冲突数量	2.622×10⁵	-4.213	51.73	2

无人机数量	冲突数量（解脱前）	冲突数量（解脱后）	解脱百分比/%	求解时间/s
20	1	0	100	1.47
40	14	0	100	1.61
60	28	1	96.43	7.27
80	40	2	95.00	14.33
100	71	4	94.37	16.82
120	96	5	94.79	17.71
140	170	12	92.94	24.60
160	185	12	93.51	26.74
180	210	18	91.43	41.36
200	273	21	92.31	46.29
220	316	23	92.72	62.10
240	317	34	89.27	64.17
260	386	34	91.19	71.37
280	450	44	90.22	75.22
300	459	42	90.85	76.54

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Cooperative deduction and optimal allocation method for urban low-altitude UAV flight plan

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