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Low-altitude economy: Shaping the Skies of Tomorrow

2026年05月09日 12:03  

报告题目:Low-altitude economy: Shaping the Skies of Tomorrow

报告人:Guglielmo 教授

邀请人:钟绍鹏 教授

报告时间及地点:2026年5月20日 9:30-12:00 经济管理学院B305

报告人简况:

Guglielmo is Professor in Network Analytics at Lancaster University Management School. His research spans both theoretical and practical aspects of Operational Research, with Air Traffic Management representing one of the most prominent application domains. Some of his work has made key contributions to these application areas, as evidenced by several awards, including the 2013 INFORMS TSL Best Published Paper Award.

His research has been funded by industry, governmental agencies, and the European Commission. He was a recipient of a Fulbright Fellowship at MIT and of a one-year fellowship at the University of Maryland.

He is an Associate Editor for Transportation Science, and he has served on the programme committees of several international conferences, on the advisory boards of European research projects, and on several award committees of the INFORMS TSL Society.

报告内容摘要:

The low-altitude economy is emerging as a new paradigm for economic and societal development, enabled by advances in Advanced Air Mobility (AAM), unmanned aerial systems, digital infrastructure, and intelligent airspace management. By leveraging revolutionary aircraft technologies and innovative operational concepts, AAM has the potential to provide safe, efficient, and sustainable transportation of people and goods while improving connectivity for communities underserved by existing transportation systems.

Drawing parallels with the evolution of the conventional air traffic system, this talk will discuss some of the key challenges that the low-altitude economy may face in the near future, particularly under scenarios of rapid adoption and increased operational density. In particular, the talk will provide an overview of recent developments in Air Traffic Flow Management (ATFM), including trajectory-based operations and the use of machine learning and artificial intelligence to enhance predictive and prescriptive decision-making capabilities. The discussion will highlight how these concepts and technologies may support the scalable, safe, and efficient management of future low-altitude operations.

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