人工智能赋能空域系统,提升空域分层治理能力

doi:10.7527/S1000-6893.2020.25018

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人工智能赋能空域系统,提升空域分层治理能力

陈志杰, 汤锦辉, 王冲, 程季锃, 曹珊, 邵欣

国家空域技术重点实验室, 北京 100085

收稿日期:2020-11-26 修回日期:2020-11-30 发布日期:2020-12-25
通讯作者: 王冲 E-mail:airspace_chongwang@163.com
基金资助:
中国工程院战略研究与咨询项目（2021-XZ-29）

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

CHEN Zhijie, TANG Jinhui, WANG Chong, CHENG Jizeng, CAO Shan, SHAO Xin

National Key Laboratory of Airspace Technology, Beijing 100085, China

Received:2020-11-26 Revised:2020-11-30 Published:2020-12-25
Supported by:
Strategic Research and Consulting Project of Chinese Academy of Engineering(2021-XZ-29)

摘要/Abstract

摘要： 为应对未来平台无人化、用户多元化、服务个性化的航空发展趋势，空域运行将呈现分层治理的发展趋势。而随着算力、算法与数据的持续提升与积累，数据驱动的人工智能方法将持续为层次化的空域系统赋能。本文从超低空、城市、区域、枢纽、亚轨道等5个层次化场景梳理我国空域系统的发展趋势；提炼得出空域运行面临的核心难点与关键科学问题；提出基于数据驱动的人工智能方法求解空域运行科学问题的研究框架、研究内容和应关注的关键技术；结合层次化典型应用场景，简要分析智能空域运行的具体应用案例；最后对人在空域运行中的作用提出了新的思考。

关键词: 空域系统, 空中交通管理, 分层治理, 人工智能, 数据驱动

Abstract: 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.

Key words: airspace system, air traffic management, hierarchical governance, artificial intelligence, data driven

中图分类号:

V355
TP391

陈志杰, 汤锦辉, 王冲, 程季锃, 曹珊, 邵欣. 人工智能赋能空域系统,提升空域分层治理能力[J]. 航空学报, 2021, 42(4): 525018-525018.

CHEN Zhijie, TANG Jinhui, WANG Chong, CHENG Jizeng, CAO Shan, SHAO Xin. Using artificial intelligence in airspace system to improve airspace hierarchical governance capability[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(4): 525018-525018.

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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

人工智能赋能空域系统,提升空域分层治理能力

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

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