Using artificial intelligence in airspace system to improve airspace hierarchical governance capability

被引：0

作者：

Chen Z. ^{[1
]}

Tang J. ^{[1
]}

Wang C. ^{[1
]}

Cheng J. ^{[1
]}

Cao S. ^{[1
]}

Shao X. ^{[1
]}

机构：

[1] National Key Laboratory of Airspace Technology, Beijing

来源：

Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2021年 / 42卷 / 04期

关键词：

Air traffic management; Airspace system; Artificial intelligence; Data driven; Hierarchical governance;

D O I：

10.7527/S1000-6893.2020.25018

中图分类号：

学科分类号：

摘要：

To follow the development trend of unmanned platform, diversified users and personalized services in the future aviation field, hierarchical governance is being adopted in airspace operation. With the continuous improvement and accumulation of computing power, algorithms and data, the data driven artificial intelligence method will continue to empower hierarchical airspace system. Firstly, this paper combs the development trend of China's airspace system in terms of five hierarchical scenarios: ultra-low altitude transportation, urban transportation, regional transportation, hub transportation and suborbital transportation. The core difficulties and key issues of airspace operation are summarized. Secondly, the research framework, research contents and key technologies of data-driven artificial intelligence method to solve the scientific problems of airspace operation are proposed. Specific cases of application of artificial intelligence for hierarchical scenarios of airspace are briefly analyzed. Finally, new thoughts on the role of human in airspace operation are presented. © 2021, Beihang University Aerospace Knowledge Press. All right reserved.

引用

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