A new algorithm for automatic trailers is expected to revolutionize the taxiing of aircraft, saving millions of dollars in fuel costs in the aviation industry while significantly reducing emissions and noise pollution. This innovative solution, developed by Stefano Zaninotto, Dr. Jason Gauci, and Dr. Brian Zammit of the University of Malta, is detailed in its recent study published in the journal Aerospace.
Stefano Zaninotto and his colleagues created an algorithm designed to manage taxi operations using automated trailers. “Our algorithms are designed to minimize taxi-related delays and route lengths while maximizing the use of trailers,” Zaninotto said. The aviation industry has long struggled to cope with the environmental and economic impacts of aircraft taxiing. Traditionally, aircraft use their engines to taxi, resulting in high fuel consumption and large emissions. In 2022, the taxiing phase constitutes about 1 of the seven total durations of internal flights in Europe, consuming about 5 million tons of fuel per year.
This novel algorithm focuses on optimizing ground operation by deploying electric trailers to move the aircraft between the gate and the runway. The system uses a centralized approach to strategically run to pre-plan all routes, adjust schedules and allocate trailers. By doing so, it aims to eliminate traffic conflicts and increase overall efficiency.
The study highlights several key findings. First, the algorithm successfully reduces taxi delays and emissions. It takes into account various factors such as the battery status of the trailer and the availability of the charging station to ensure the trailer can operate without interruption. The system is also scalable and adaptable, and has been rigorously tested in different airport layouts and traffic volumes.
“Our system addresses the shortcomings of existing approaches by focusing on conflict-free solutions and effective trailer utilization. It can manage multiple active runways and strategically allocate trailers,” explains Zaninotto. Given the diversity of airport environments and Dynamic nature, this adaptability is crucial.
Furthermore, simulations from this study show that fuel savings are substantial. Researchers estimate that using a trailer for sliding can reduce fuel consumption compared to conventional methods. This not only cuts airline costs, but also supports environmental sustainability goals. “Reducing fuel consumption during taxiing is a critical step in achieving carbon neutrality in aviation,” Zaninotto noted.
The system also improves security by constantly monitoring potential conflicts during the scooter operation. This includes checking for conflicts between the aircraft and the trailer and between the trailer itself. The algorithm uses advanced technology to ensure that all movements are coordinated and safe.
In short, this groundbreaking algorithm represents a significant advance in airport ground operations. By leveraging automatic trailers, it provides a practical and effective solution to the challenge of aircraft taxiing. The researchers’ work paves the way for green, more efficient airports to align with the global Sustainable Development Goals.
Journal Reference
Zaninotto, Stefano, Jason Gauci and Brian Zammit. “A no-automatic drag truck algorithm for taxiing without engineering aircraft.” Aerospace 2024, 11, 307. doi: https://doi.org/10.3390/aerospace11040307
About the Author
ing. Stefano Zaninotto Have a bachelor’s degree and master’s degree in civil and environmental engineering from the University of Trieste (Italy) and close to a doctorate in air traffic management from the School of Aeronautics and Astronautics, University of Malta. His doctoral research has led to several papers on algorithms and solutions for automatic trailer scooter systems. ing. Stefano Zaninotto currently works as a data analyst in the private sector, and also serves as a researcher in the Department of Aviation, Transportation and Logistics, and teaches at the Institute of Information and Communication Technology in Mcast (Malta).
Dr. Gao Qi Have a degree in electrical engineering from the University of Malta (Malta) and a PhD in aerospace engineering from Cranfield University in the UK. He is a senior lecturer at the School of Aeronautical Technology, University of Malta and an adjunct assistant professor at Embry-Riddle Aeronautical University (Worldwide). His research interests include: driverless cars (UAV), aerospace applied machine learning, air traffic management (ATM), avionics and human-computer interaction (HCI). Dr. Gauchi is involved in several national and European-funded research projects and is the author/co-author of more than 35 academic papers. He is also one of the inventors of several patent applications.
PhD. Brian Zammit Since joining the university in 2005, he has been involved in research related to avionics, where he served as a research assistant for European-funded projects. His work has led to the creation and co-authorization of several papers and patents related to aircraft operations and optimization. Dr. Zammit received his PhD from the University of Malta in 2015 and has since supervised, jointly supervised and inspected several undergraduate, MSC and PhD candidates. Currently, he is a senior lecturer in the Department of Electronic Systems at the University of Malta, where he teaches the foundations of electronics, instrumentation and data acquisition systems.
