Flexible Airlane Generation to Maximize Flow under Hard and Soft Constraints

Abstract

A fully capable traffic flow management system must solve a multicriteria optimization problem of simultaneously routing several classes of aircraft through an airspace in which constraints apply in different ways to different aircraft. In this problem, we route several classes of aircraft through an airspace at a fixed flight level in the presence of hard and soft constraints. Hard constraints are formed by hazards through which no aircraft can safely fly (e.g., severe convection, turbulence, or icing). Soft constraints are formed by hazards through which some pilots or airlines decide to fly while others do not (e.g., moderate turbulence or icing). We compute flight paths for two aircraft classes: Class-1 aircraft avoid hard constraints but are willing to fly through soft constraints, and Class-2 aircraft avoid both hard and soft constraints. Our work assists in designing future operational concepts in which jetway routing is retired and aircraft paths are allowed to adjust to the shapes and positions of constraints. We are interested in determining the capacity of an airspace and feasible routes across an airspace with hard and soft constraints, given as input the demand profile indicating how many Class-1 and Class-2 aircraft are scheduled to enter the airspace. We report on experiments both with real and with synthesized weather data.