Development of intelligent avionics systems to optimize and automate aircraft trajectories, while reducing the environmental impact of aviation

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Despite the impact of the COVID-19 pandemic, aviation stakeholders suggest that tomorrow's air traffic will be extremely dense. While necessary for global economic development, this expansion will pose several operational, safety, social and environmental challenges. Faced with this situation, it is crucial for the aviation industry to develop new practices and technologies to operate aircraft in a more efficient and environmentally sustainable way. The main objective of this research program is to explore new solutions for the development of intelligent avionics systems to improve air traffic management and reduce aircraft emissions, while enhancing flight safety. The word "intelligent" in this context refers to the ability to learn the performance of an aircraft, as well as the use of artificial intelligence-based techniques to control the motion of an aircraft. In the short term, this research program will focus on the development of solutions to optimize and automate the management of aircraft trajectories on the ground. However, in the longer term, the objective will be to generalize this concept from the ground to the airspace. The strategy for achieving the main objective includes three phases. First, new self-modeling algorithms will be designed to monitor and learn the performance of an aircraft. The objective here is to develop intelligent avionics systems that remain accurate over time. All mathematical model to predict air-craft trajectory, emissions and noise will be also developed during this first step. The second phase will focus on optimizing aircraft trajectories during taxiing and takeoff. Graph neural networks combined with ADS-B data will be considered to model and account ground traffic. Deterministic and evolutionary optimization algorithms will be tested, and their results compared. The optimal solution will be defined as the trajectory that minimizes time, fuel consumption, and emissions, while ensuring safety and feasibility. Finally, the third phase will be devoted to the development of new control algorithms using artificial intelligence and computer vision techniques to enable aircraft to move automatically on the ground. All methodologies will be validated using two professional and highly qualified flight simulators and real flight data. This research program aims to propose new solutions to modernize the current air transport system and move towards a more optimal and autonomous management of aircraft trajectories. In addition, the use of autonomous technologies will make flight procedures more efficient, safer and, most importantly, help reduce emissions. This research program also aims to explore the potential that artificial intelligence can bring to the aerospace field, and thus encourage industry and researchers to pursue this direction. Finally, highly qualified personnel will be trained on innovative research topics, preparing them to make a significant contribution to the Canadian aerospace industry.