Abstract Manager

Le projet vise à améliorer la sécurité des traversées de véhicules de service sur la Route 300, à l’aéroport de Montréal-Trudeau, en automatisant le processus de gestion des déplacements. Actuellement, ces traversées, principalement effectuées pour le service aux aéronefs, sont contrôlées manuellement par la tour de contrôle de l’aéroport.

Après la revue et le recensement de plusieurs solutions potentielles, Stantec a proposé et retenue une solution finale appuyée par un système d’apprentissage automatique basé sur l’intelligence artificielle, permettant une surveillance autonome. Ce système est capable de différencier les objets dans la zone côté piste et d’indiquer aux véhicules en position d’arrêt, le moment sécuritaire pour traverser, offrant ainsi une solution novatrice, pour la gestion autonome de la circulation en zone aéroportuaire.

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The project aims to secure the passage of service vehicles on Route 300, which intersects with Taxiway Charlie at Trudeau International Airport. These service vehicles cater to aircraft (grooming, catering, lav trucks), and the handlers need to use Route 300. Currently, the control tower, operated by human controllers, monitors the passage of these vehicles. Until they receive clearance to cross, the vehicles must remain stationary. Aéroports de Montréal, the owner, wishes to automate this process and make the control fully autonomous. Stantec proposed six innovative solutions, one of which has been selected as the final solution. The concept involves implementing a perimeter intrusion detection system that combines a 360-degree rotating radar and video cameras to help control the traffic. The high-definition radar allows the system to differentiate between various moving objects in the airside zone (aircraft, humans, vehicles, etc.). High-definition cameras provide surveillance images that enable operators to better distinguish critical details for further assessment. The system is equipped with an AI controller that uses machine learning technology, which continuously learns from the movements and improves its decision-making capabilities. It is also proposed to equip the system with a variable message sign that will confirm to service vehicles when it is safe to cross the taxiway. This could be the first application of its kind in Canada using AI to monitor vehicles and aircraft on the airfield.