面向城市低空物流配送的无人机实时航迹双层规划

doi:10.7527/S1000-6893.2025.31621

Abstract

Abstract:

To improve the safety and public acceptance of logistics drones in complex urban low altitude environments， a real-time dual layer path planning method for urban low-altitude logistics distribution drones is proposed. Firstly， the spatial environment is characterized using grid method and digital elevation model， and a risk perception model for urban low altitude environment based on third-party social risks is established. Secondly， a real-time dual layer path planning model for low altitude logistics drones is proposed. For a single drone in the pre tactical stage， the upper layer model aims to minimize third-party social risk costs and navigation time costs， and an improved A* algorithm is used to plan the optimal expected trajectory. For the coordinated operation of unmanned aerial vehicles in the tactical stage， the lower-level model considers the conflict problem between multiple unmanned aerial vehicles and designs a differentiated conflict resolution strategy based on yaw and hover. With the goal of minimizing the deviation from the optimal expected trajectory cost， a real-time path optimization model for unmanned aerial vehicles is established. Experiments have shown that the upper-level model can reduce operational risk by 15.12% compared to Trajectory Planning considering the Flight Duration（TPFD）， and by 10.61% compared to Trajectory Planning considering the Risk Cost（TPRC）. The lower-level model can effectively generate four-dimensional trajectories with low operational risk， short navigation time， and no conflicts. For a fleet of 50 logistics drones and 100 non-cooperative drones operating in coordination， conflicts can be resolved 60 times within a 10 minutes simulation period， with a flight conflict resolution rate of 100%. The additional risks， flight time， flight distance， and number of grid crossings caused by this can be controlled below 3%.

Key words: air transportation, path planning, improved A* algorithm, logistics drones, conflict resolution

CLC Number:

V355

Dan CHEN, Cheng TANG, Yu XIE, Yuanyuan MA, Tianshu XU. Real time dual layer path planning of unmanned aerial vehicles for urban low altitude logistics distribution[J]. Acta Aeronautica et Astronautica Sinica, 2025, 46(16): 331621.

Figures/Tables 22

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Table 1

Parameter Settings

参数	数值	参数	数值
最大航程 $L m a x / m$	5 000	最大俯仰角 $μ m a x$	$± π / 2$
最大转弯角 $β m a x$	$± π / 2$	栅格大小 $l g r i d / m$	5
最大飞行高度 $H m a x / m$	120	最小飞行高度 $H m i n / m$	1
无人机空重m/kg	1.38	$P U A V$	$3.42 × 10 - 4$
$S h i t / m 2$	0.018 8	$S c$	0.5
$v c r / (m · s - 1)$	20	$v c l / (m ⋅ s - 1)$	6
$v d e s / (m · s - 1)$	4	$L s / d B$	110

Table 1

Fig.7

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Fig.13

Table 2

Fig.14

Table 3

Fig.15

Fig.16

Table 4

Fig.17

Table 5

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模型	航迹规划结果				与TPCC对比
模型	风险代价	时间代价/s	航行距离/m	占用栅格数	风险代价/%	时间代价/%	航行距离/%	占用栅格数/%
TPFD	279.03	52.34	966.81	143	-15.12	0.52	-4.84	-4.9
TPRC	230.63	58.85	928.82	137	2.69	-10.61	-0.95	-0.73
TPECN	258.08	52.90	919.53	136	-8.22	-0.54	0.05	0
TPEC	264.77	53.32	927.81	136	-10.55	-1.33	-0.84	0
Dijkstra	241.16	53.93	959.05	149	-1.79	-2.45	-4.07	-8.72
TPCC	236.85	52.61	920.01	136	0	0	0	0

栅格尺寸/m	风险代价	代价对比/%	时间代价/s	代价对比/%	航行距离/m	距离对比/%
5	236.85	0	52.61	0	920.01	0
10	253.30	6.95	54.14	2.90	956.85	4.00
20	303.88	28.30	54.60	3.79	953.46	3.63
30	322.37	36.11	55.67	5.81	943.68	2.57

分析指标	TPCC	LLOT	对比
风险代价	236.85	239.34	2.49
时间代价/s	52.62	53.11	0.49
航行距离/m	920.01	930.01	10
占用栅格数/个	136	138	2
冲突栅格数/个	2	0	-2

模型	航迹规划结果					与LLOT对比
模型	风险代价	时间代价/s	航行距离/m	占用栅格数/个	冲突栅格数/个	风险代价/%	时间代价/%	航行距离/%	占用栅格数/%	冲突栅格数/%
TPFD	9 928.41	1 959.40	35 188.05	5 230	70	-17.78	4.14	-7.12	-2.89	-100
TPRC	7 691.40	2 130.14	32 384.53	5 050	75	6.13	-4.21	0.92	0.57	-100
TPCC	8 150.82	2 016.70	31 986.08	5 010	60	0.15	1.18	2.17	1.38	-100
TPECN	8 390.87	2 026.55	31 426.94	4 850	72	-2.71	0.69	3.99	4.72	-100
TPEC	8 471.33	2 034.59	31 042.27	4 770	55	-3.64	0.29	5.28	6.48	-100
Dijkstra	8 322.98	2 036.13	31 432.56	4 900	72	-1.92	0.21	3.97	3.65	-100
LLOT	8 163.15	2 040.48	32 680.92	5 079	0	0	0	0	0	0

Real time dual layer path planning of unmanned aerial vehicles for urban low altitude logistics distribution

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