Deterministic air traffic flow management (TFM) decisions –the state of the art in terms of implementation– often result in “lost” airspace capacity, because the inherent uncertainties in weather predictions make it difficult to determine the number of aircraft that can be safely accommodated in a volume of airspace during a given period. As a result, there is a distinct need for TFM algorithms that utilize available stochastic weather information for improved decision making. To this end, we first develop a methodology to determine the stochastic capacity for a volume of airspace given the forecast weather and associated uncertainty. Then, we use this information as input to a dynamic stochastic optimization algorithm to determine the number of aircraft to send towards a volume, providing specific guidance for routing aircraft in the presence of the uncertainties of adverse weather.
Theme: Network and Strategic Traffic Flow Optimization
Keywords: air traffic flow management, dynamic routing, stochastic capacity, weather
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