A novel air traffic management decision support system

摘要

This research project aimed to develop innovative Multi-Objective Trajectory Optimisation (MOTO) and Dynamic Airspace Management (DAM) models and tools to enhance the performance of Air Traffic Management (ATM) and Air Traffic Flow Management (ATFM) systems, simultaneously targeting safety, efficiency and environmental sustainability requirements in line with SESAR and NextGen operational concepts. The novel MOTO and DAM functionalities were implemented and numerically evaluated in the form of automated 4DT Planning, Negotiation and Validation (4-PNV) algorithms within an innovative ATM Decision Support System (DSS) prototype. The 4-PNV system exchanges optimal 4DT intents with Next Generation Flight Management Systems (NG-FMS) on board equipped traffic via suitable data-links. Two different MOTO algorithms were developed to selectively address the en-route context and Terminal Manoeuvring Area (TMA) sectors. A variable set of models and optimality criteria can be selected based on the flight phase, aircraft and airspace states. An operational 4DT smoothing algorithm translates the mathematical Continuous and Piece-Wise Smooth (CPWS) optimal trajectory in a flyable and concisely described 4DT intent, while retaining most of the optimality performances offered by the mathematical solution. The developed MOTO-4D and DAM algorithms support an automation-assisted planning of 4DT intents in strategic and tactical online timeframes, as well as traffic flow and airspace reconfigurations. The models adopted to introduce the environmental performance within the 4DT optimisation framework also enable an estimation of the environmental impacts.