物流无人机城市低空轴辐式网络构建方法研究

doi:10.3976/j.issn.1002-4026.2023.06.011

Abstract

Abstract:

Unmanned aerial vehicles (UAVs) have considerable application potential in urban logistics delivery. However, there are many uncertainties in urban low-altitude airspace operation scenarios. Therefore, it is essential to build a safe and orderly logistics UAV delivery network using scientific methods. From the perspectives of delivery economy, operational safety, and features of logistics UAVs, an integer programming model of multilevel hub-and-spoke network was constructed based on the original ground logistics delivery network. A network construction method was proposed, which combines partitioning around medoids(PAM) clustering with distance restrictions and integer programming. Three evaluation indicators were selected, i.e., delivery timeliness, network security, and network structure characteristics, to compare the constructed logistics UAV delivery network with the original ground delivery network. A logistics UAV delivery network was constructed in Jiangning District of Nanjing city to verify the feasibility of the proposed network construction method. The experimental results show that the UAV delivery network constructed using this method has good delivery timeliness while taking delivery costs and safety into account.

Key words: unmanned aerial vehicle, low altitude airspace anagement, logistics and distribution, hub-and-spoke network, partitioning around medoids clustering

CLC Number:

QU Xinyu, YE Bojia, CHENG Yu, LEI Changding. The method to construct an urban logistics unmanned aerial vehicles low-altitude hub-and-spoke network[J].Shandong Science, 2023, 36(6): 86-95.

Figures/Tables 9

Fig.1

Table 1

Table 2

Fig.2

Table 3

Fig.3

Fig.4

Table 4

Fig.5

References 16

[1]	姚虹翔, 叶博嘉, 程予. 低空无人机空中交通管理研究[J]. 科技创新与应用, 2021, 11(25): 183-187.
[2]	VENKATESH N, PAYAN A, JUSTIN C Y, et al. Optimal siting of sub-urban air mobility (sUAM) ground architectures using network flow formulation[C]// American Institute of Aeronautics and Astronautic,Aviation 2020 Forum. Reston, USA: AIAA. 2020: 2921.DOI: 10.2514/6.2020-2921.
[3]	钱欣悦, 张洪海, 张芳, 等. 末端配送物流无人机起降点选址分配问题研究[J]. 武汉理工大学学报(交通科学与工程版), 2021, 45(4): 682-687. DOI: 10.3963/j.issn.2095-3844.2021.04.013.
[4]	任新惠, 王柳. 即时配送下无人机全自动机场分区选址模型[J]. 计算机工程与应用, 2021, 57(10): 266-272. DOI: 10.3778/j.issn.1002-8331.2003-0433.
[5]	CHAUHAN DARSHAN R, AVINASHU, MIGUELF, et al. Robust maximum coverage facility location problem with drones considering uncertainties in battery availability and consumption[J]. Transportation Research Record, 2021, 2675(2): 25-39.
[6]	FENG D K, ZHANG HH, LIU H, et al. Research on location of logistics UAV airport in urban environment[C]// 6th International Conference on Information Science, Computer Technology and Transportation. Xishuangbanna, China: VDE, 2022: 1-5.
[7]	LI S, ZHANG HH, LI Z L, et al. An air route network planning model of logistics UAV terminal distribution in urban low altitude airspace[J]. Sustainability, 2021, 13(23): 13079. DOI: 10.3390/su132313079.
[8]	张洪海, 冯棣坤, 张晓玮, 等. 城市物流无人机起降点布局规划研究[J]. 交通运输系统工程与信息, 2022, 22(3): 207-214. DOI: 10.16097/j.cnki.1009-6744.2022.03.023.
[9]	ZHANG X J, LIU Y, ZHANG Y, et al. Safety assessment and risk estimation for unmanned aerial vehicles operating in national airspace system[J]. Journal of Advanced Transportation, 2018, 2018 (Pt.6): 4731585. DOI: 10.1155/2018/4731585.
[10]	胡莘婷, 戴福青. 基于城区行人安全的无人机运行风险评估[J]. 中国安全科学学报, 2020, 30(8): 137-142. DOI: 10.16265/j.cnki.issn1003-3033.2020.08.020.
[11]	钟罡, 励瑾, 张晓玮, 等. 物流无人机对地风险评估方法研究[J]. 交通运输系统工程与信息, 2022, 22(4): 246-254. DOI:10.16097/j.cnki.1009-6744.2022.04.028.
[12]	李鹏飞, 彪蔚然. 快递网络结构研究进展[J]. 西安邮电大学学报, 2020, 25(1): 34-41. DOI: 10.13682/j.issn.2095-6533.2020.01.004.
[13]	中国民用航空局空管行业管理办公室. 城市场景轻小型无人驾驶航空器物流航线划设规范: MH/T 4054-2022[S]. 北京: 中国民航出版社, 2022.
[14]	中国民用航空局. 无人驾驶航空器飞行管理暂行条例[EB/OL].[2023-01-17]. https://www.gov.cn/zhengce/content/202306/content_6888799.htm.
[15]	中通研究院. “末端+支线”无人机运营场景成本分析[EB/OL].[2023-01-16]. http://hkjjyjzx.zua.edu.cn/info/1066/1264.htm.
[16]	陈欣, 李心茹, 盛寅. 基于复杂网络的长三角航线网络结构特征分析[J]. 交通信息与安全, 2020, 38(4): 139-146. DOI: 10.3963/j.jssn.1674-4861.2020.04.017.

区域等级	区域类型	最小飞行距离(风险值)/m
1级区域	射电天文台、国界线、空中禁区	3 000
2级区域	空中危险区、机场、临时起降点、边境线	2 000
3级区域	卫星地面站等需要电磁环境特殊保护的设施	1 000
4级区域	军事禁区、气象雷达站	500
5级区域	军事管理区,设区的市级(含)以上党政机关、监管场所,生产储存易燃易爆危险品,可燃重要物资的大型仓库、基地,高速铁路	100
6级区域	发电厂、变电站、加油站、大型车站、码头、港口、大型活动现场、普通铁路和国道、住宅建筑区	50

符号	含义
x_ki	表示节点i是否与枢纽点k相连,若相连x_ki=1,否则x_ki=0
d_ki	节点i到枢纽点k间的距离(单位:km)
a_ki	表示节点i与枢纽点k间的航线是否途径禁飞区,若途径a_ki=0,否则a_ki=1
α	绕飞系数,无人机为避障进行绕飞的路径长度与直飞的路径长度间的比值
f	包含供能设备成本和能源使用成本在内的无人机每公里运行能耗成本(单位:元/km)
h	每千克包裹所需的管理费用(单位:元/kg)
c	每个枢纽点的升级建设费用(单位:元)
p	枢纽点数量
D_i	节点i的快递需求量(单位:kg)
y_k	表示是否选点k作为枢纽点,若k为枢纽点y_k=1,否则y_k=0
e_kij	由k到i的航线途径j类区域的网格数
r_j	无人机飞经j类区域的风险值
l_max	无人机最大飞行距离(单位:km)
b_max	无人机最大载荷重量(单位:kg)
C	总配送成本(单位:元)
E	途径区域风险值
F	使用理想点法求解的目标函数

评价指标	原配送网络	新建配送网络
平均路径长度/m	26 158.919 192 3	24 379.966 031 5
安全系数	0.492 631 2	1.563 644 3
平均点度中心性	0.036 363 7	0.050 243 6
平均接近中心性	0.000 039 3	0.000 041 8
平均中介中心性	0.041 462 1	0.073 841 2
点度中心势	0.423 481 6	0.249 492 9
接近中心势	0.000 050 0	0.000 050 0
中介中心势	0.686 613 8	0.598 253 1

The method to construct an urban logistics unmanned aerial vehicles low-altitude hub-and-spoke network

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 16

Related Articles 1

Metrics

Comments

Recommended 0