{"title":"无人飞行器低空空域管理与先进空中机动性研究进展","authors":"Nichakorn Pongsakornsathien , Nour El-Din Safwat , Yibing Xie , Alessandro Gardi , Roberto Sabatini","doi":"10.1016/j.paerosci.2025.101085","DOIUrl":null,"url":null,"abstract":"<div><div>Contemporary trends in Uncrewed Aircraft Systems Traffic Management (UTM) and Advanced Air Mobility (AAM) are redefining low-altitude airspace operations, particularly in urban and suburban settings where traditional airspace management approaches are inadequate to support the predicted air transport demands. To address these challenges, the development of an integrated Low-Altitude Airspace Management (LAAM) framework is seen as an essential next step, requiring new flight systems and infrastructure tailored to the distinct challenges of these environments. Cyber technologies, including automation and Artificial Intelligence (AI), play a crucial role in LAAM by integrating data from Communication, Navigation, and Surveillance (CNS) systems to support real-time and automated decision-making for separation assurance and flow management. While human operators and social interactions retain a very important role in LAAM collaborative decision-making processes, the reliance on automation is expected to continue growing, driven by the need to effectively manage the challenges arising from the increasing number and diversity of highly automated and uncrewed aircraft. Regulatory frameworks must adapt to accommodate the unique characteristics of AAM operations, ensuring the adequacy of safety standards and airspace regulations. In particular, airspace design is bound to evolve to accommodate Vertical/Short Take-off and Landing (V/STOL) aircraft’s distinct capabilities and requirements. The deployment of AI in safety-critical systems will require rigorous verification, validation, and certification processes to ensure reliability and trustworthiness. To address these complex and interrelated challenges, a harmonized LAAM Concept of Operations (CONOPS) is needed, which should encapsulate both UTM and emerging AAM requirements, while clearly specifying the role of human operators for various levels of automation. Additionally, new system functionalities should be developed to enhance human-machine teaming by focussing on CNS performance-based airspace modeling and dynamic airspace management. Based on these premises, an integrated approach to Multi-Domain Traffic Management (MDTM) is emerging, with promising future perspectives for the safe, efficient and sustainable operation of highly automated and autonomous flight systems in all present and likely future classes of airspace.</div></div>","PeriodicalId":54553,"journal":{"name":"Progress in Aerospace Sciences","volume":"154 ","pages":"Article 101085"},"PeriodicalIF":11.5000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advances in low-altitude airspace management for uncrewed aircraft and advanced air mobility\",\"authors\":\"Nichakorn Pongsakornsathien , Nour El-Din Safwat , Yibing Xie , Alessandro Gardi , Roberto Sabatini\",\"doi\":\"10.1016/j.paerosci.2025.101085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Contemporary trends in Uncrewed Aircraft Systems Traffic Management (UTM) and Advanced Air Mobility (AAM) are redefining low-altitude airspace operations, particularly in urban and suburban settings where traditional airspace management approaches are inadequate to support the predicted air transport demands. To address these challenges, the development of an integrated Low-Altitude Airspace Management (LAAM) framework is seen as an essential next step, requiring new flight systems and infrastructure tailored to the distinct challenges of these environments. Cyber technologies, including automation and Artificial Intelligence (AI), play a crucial role in LAAM by integrating data from Communication, Navigation, and Surveillance (CNS) systems to support real-time and automated decision-making for separation assurance and flow management. While human operators and social interactions retain a very important role in LAAM collaborative decision-making processes, the reliance on automation is expected to continue growing, driven by the need to effectively manage the challenges arising from the increasing number and diversity of highly automated and uncrewed aircraft. Regulatory frameworks must adapt to accommodate the unique characteristics of AAM operations, ensuring the adequacy of safety standards and airspace regulations. In particular, airspace design is bound to evolve to accommodate Vertical/Short Take-off and Landing (V/STOL) aircraft’s distinct capabilities and requirements. The deployment of AI in safety-critical systems will require rigorous verification, validation, and certification processes to ensure reliability and trustworthiness. To address these complex and interrelated challenges, a harmonized LAAM Concept of Operations (CONOPS) is needed, which should encapsulate both UTM and emerging AAM requirements, while clearly specifying the role of human operators for various levels of automation. Additionally, new system functionalities should be developed to enhance human-machine teaming by focussing on CNS performance-based airspace modeling and dynamic airspace management. Based on these premises, an integrated approach to Multi-Domain Traffic Management (MDTM) is emerging, with promising future perspectives for the safe, efficient and sustainable operation of highly automated and autonomous flight systems in all present and likely future classes of airspace.</div></div>\",\"PeriodicalId\":54553,\"journal\":{\"name\":\"Progress in Aerospace Sciences\",\"volume\":\"154 \",\"pages\":\"Article 101085\"},\"PeriodicalIF\":11.5000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Progress in Aerospace Sciences\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0376042125000119\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, AEROSPACE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Progress in Aerospace Sciences","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0376042125000119","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
Advances in low-altitude airspace management for uncrewed aircraft and advanced air mobility
Contemporary trends in Uncrewed Aircraft Systems Traffic Management (UTM) and Advanced Air Mobility (AAM) are redefining low-altitude airspace operations, particularly in urban and suburban settings where traditional airspace management approaches are inadequate to support the predicted air transport demands. To address these challenges, the development of an integrated Low-Altitude Airspace Management (LAAM) framework is seen as an essential next step, requiring new flight systems and infrastructure tailored to the distinct challenges of these environments. Cyber technologies, including automation and Artificial Intelligence (AI), play a crucial role in LAAM by integrating data from Communication, Navigation, and Surveillance (CNS) systems to support real-time and automated decision-making for separation assurance and flow management. While human operators and social interactions retain a very important role in LAAM collaborative decision-making processes, the reliance on automation is expected to continue growing, driven by the need to effectively manage the challenges arising from the increasing number and diversity of highly automated and uncrewed aircraft. Regulatory frameworks must adapt to accommodate the unique characteristics of AAM operations, ensuring the adequacy of safety standards and airspace regulations. In particular, airspace design is bound to evolve to accommodate Vertical/Short Take-off and Landing (V/STOL) aircraft’s distinct capabilities and requirements. The deployment of AI in safety-critical systems will require rigorous verification, validation, and certification processes to ensure reliability and trustworthiness. To address these complex and interrelated challenges, a harmonized LAAM Concept of Operations (CONOPS) is needed, which should encapsulate both UTM and emerging AAM requirements, while clearly specifying the role of human operators for various levels of automation. Additionally, new system functionalities should be developed to enhance human-machine teaming by focussing on CNS performance-based airspace modeling and dynamic airspace management. Based on these premises, an integrated approach to Multi-Domain Traffic Management (MDTM) is emerging, with promising future perspectives for the safe, efficient and sustainable operation of highly automated and autonomous flight systems in all present and likely future classes of airspace.
期刊介绍:
"Progress in Aerospace Sciences" is a prestigious international review journal focusing on research in aerospace sciences and its applications in research organizations, industry, and universities. The journal aims to appeal to a wide range of readers and provide valuable information.
The primary content of the journal consists of specially commissioned review articles. These articles serve to collate the latest advancements in the expansive field of aerospace sciences. Unlike other journals, there are no restrictions on the length of papers. Authors are encouraged to furnish specialist readers with a clear and concise summary of recent work, while also providing enough detail for general aerospace readers to stay updated on developments in fields beyond their own expertise.