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Impacts of commercial aircraft operation upon the environment, which are caused primarily from emissions of C O 2 , N O x and the formation of contrails, are matter of growing concern, as aviation is one of the fastest developing industrial sectors worldwide and the awareness of its effects is expanding. Recent research has focused on the cost-benefit potential of different mitigation strategies, which optimize flight trajectories with respect to climate and economy, but most of these mitigation strategies cannot be implemented in the near future due to technical challenges. The objective of this paper is to present an interim mitigation strategy, which bridges this time period. In analogy to military exclusion zones, climate restricted airspaces (CRA) are defined based on 3-D climate change functions, characterizing the environmental impact caused by an aircraft emission at a certain location. Regions with climate costs greater than a threshold value are closed in the corresponding month; others are cleared for air traffic. To estimate the cost-benefit potential of this strategy, a preliminary analysis is conducted on the route from Helsinki (EFHK) to Miami (KMIA). Affected flight trajectories are re-routed optimally around resulting CRA with regard to monetary costs for varying threshold values. Therefore, flight simulation algorithms are developed, which solve a non-linear optimal control problem. For each optimized flight trajectory corresponding average temperature response (ATR) and cash operating costs (COC) are expressed relative to a reference great circle trajectory with constant Mach number and compared with the climate mitigation potential of climate optimized trajectories. [ABSTRACT FROM AUTHOR]

The field of automatic collision avoidance for surface vessels has been an active field of research in recent years, aiming for the decision support of officers in conventional vessels, or for the creation of autonomous vessel controllers. In this paper, the multi-ship control problem is addressed using a model predictive controller (MPC) that makes use of obstacle ship trajectory prediction models built on the RBF framework and is trained on real AIS data sourced from an open-source database. The usage of such sophisticated trajectory prediction models enables the controller to correctly infer the existence of a collision risk and apply evasive control actions in a timely manner, thus accounting for the slow dynamics of a large vessel, such as container ships, and enhancing the cooperation between controlled vessels. The proposed method is evaluated on a real-life case from the Miami port area, and its generated trajectories are assessed in terms of safety, economy, and COLREG compliance by comparison with an identical MPC controller utilizing straight-line predictions for the obstacle vessel. [ABSTRACT FROM AUTHOR]