Automated Flight Routing Using Stochastic Dynamic Programming

Abstract

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

Modeling and optimization of the terminal control area with holding unit

“…Therefore, the optimization of air traffic flow in congested airspace with dynamic convective weather is a challenging problem [19]. In this context, a dynamic programming algorithm is designed to generate a robust solution for airport runway operation [20][21][22]. More importantly, the stochastic dynamic programming algorithm can well adapt to various operational constraints imposed by TCA, such as the minimum interval requirement between consecutive aircraft, the earliest and latest arrival/departure time of each aircraft, etc.…”

Risk-Hedged Approach for Re-routing Air Traffic Under Weather Uncertainty

“…[5][6][7][8]. Works that include weather among the uncertainties affecting traffic management and congestion include [3] and [9][10][11][12][13][14][15][16]. The combinatorial nature of routing problems is manifest in most of these works through the use of discrete optimization models.…”