Aircraft Operations Lab’s latest research paper, ‘Robust 4D climate-optimal aircraft trajectory planning under weather-induced uncertainties: Free-routing airspace’ has been published in the Journal of Transportation Research Part D: Transport and Environment.
Writen by Abolfazl Simorgh as main author, our research within the ongoing RefMap project introduces an innovative methodology for climate-optimal flight trajectory planning in conditions of meteorological uncertainty. In addition, with this paper we have released the new flight planning technique developed by UC3M as an open-source Python library: ROC V1.0, which can be acessed by researchers worldwide.
Abstract
The non-CO2 climate impact of aviation strongly relies on the atmospheric conditions at the time and location of emissions. Therefore, it is possible to mitigate their associated climate impact by planning trajectories to re-route airspace areas with significant climate effects. Identifying such climate-sensitive regions requires specific weather variables. Inevitably uncertain weather forecasts can lead to inefficient aircraft trajectories if not accounted for within flight planning. The current study addresses the problem of generating robust climate-friendly flight plans under meteorological uncertainty characterized using the ensemble prediction system. We introduce a framework based on the concept of robust tracking optimal control theory to formulate and solve the proposed flight planning problem. Meteorological uncertainty effects on aircraft performance variables are captured using the formulated ensemble aircraft dynamical model and controlled by penalizing the performance index variance. Case studies show that the proposed approach can generate climate-optimized trajectories with minimal sensitivity to weather uncertainty.
Robust 4D climate-optimal aircraft trajectory planning under weather-induced uncertainties: Free-routing airspace. Abolfazl Simorgh, Manuel Soler, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Federica Castino, Feijia Yin. Transportation Research Part D: Transport and Environment, Volume 131, 2024, 104196, ISSN 1361-9209, https://doi.org/10.1016/j.trd.2024.104196