A Multiobjective Optimization Approach for Air Traffic Flow Management for Airspace Safety Enhancement

This work aims to enhance the safety of air traffic in a procedural airspace by air traffic flow management (ATFM) without compromizing air traffic demand. Inc ivil aviation, collision risk is an important indicator for air traffic safety assessment. In this work, we propose a generic ATFM framework based on multiobjective optimization for reducing lateral collision risk of the traffic ina given procedural airspace. T he proposed framework aims to optimize the flight level assignment f or a given set of flight plans such that t he lateral collision risk can be reduced. To achieve this goal, we formulate an optimization problem containing two partially conflicting o bjective functions. We then adopt three well-known evolutionary algorithms, i.e., MODPSO, NSGA-II, and MOEA/D to solve the optimization problem. We specially design some of the operators of those al-gorithms to make them suitable for the optimization problem. We merge the solutions yielded by those three algorithms and filter out the final Pareto solutions. We carry o ut a case study o n the procedural airspace of Singapore flight information region (FIR) with respect to twelve daily traffic data selected from t he real traffic data for December 2019. Experiment results demonstrates that the lateral occupancy which is the key contributor to lateral risk can be reduced by 10.65 % to 93.05 % at a strategic planning level. This research contribute to strategic flight planning by assigning flight levels that m ay reduce t he risk o f collision in procedural airspace.