Fairness metric-based RTA adjustment in the presence of wind uncertainty

Planning flights in windy conditions is a significant challenge in air transportation. Wind data, derived from updated hourly forecasts available prior to departure, serve as the basis for route planning. However, ensuring timely arrival at the destination airport remains difficult due to inaccuracies and uncertainties in these meteorological forecasts. This challenge is compounded in scenarios involving multi-aircraft, as each flight seeks to minimize resource consumption such as flight time and fuel. Therefore, this study has two aims. First, it seeks to optimize airspeeds while accounting for estimated wind uncertainty in order to conserve fuel while adhering to the Required Time of Arrival (RTA) in single-aircraft operations. The first proposed methodology, referred to as the Optimal Airspeed Search Model, integrates principles from Stochastic Programming (SP) and Receding Horizon Control (RHC) frameworks to determine the most suitable airspeed. To achieve this, the flight is segmented, and a backward-propagation strategy is employed to determine airspeeds for all flight segments. The second aim considers scenarios involving multi-aircraft, assuming in-flight negotiation between aircraft and air traffic control centers to achieve fairness among flights. Using the fairness metric-based model, flight RTAs are adjusted to minimize the fairness metric value while maintaining equitable outcomes. The proposed solution optimizes airspeed, reduces fuel consumption, and negotiates fairness among multi-aircraft under RTA constraints using an integer programming approach with a branch-and-bound optimization method.