Abstract

Navigation canals are used for transport purposes. In order to allow safe navigation the water level should be kept in a certain range around the Normal Navigation Level (NNL). The water level is disturbed by known and unknown inputs, like tributaries, municipal water flows, rain, etc. Some of these inputs can be used to control the water level. If the geometry requires it, canal reaches are connected by locks. The operation of these locks sometimes can disturb the water level, if the difference between the upstream and downstream water level is large. The objective is to minimize the disturbances caused by these lock operations on the water level in order to maintain the NNL. In this work the global management of the canal reach is discussed and an option to maintain the NNL by active control is introduced. Some inputs to the system, such as other confluences or gates on the side of the locks, can be controlled automatically to react to the disturbances caused by the lock operations using model predictive control to maintain the desired water level.

Abstract

This paper proposes a collaborative air traffic flow management (ATFM) framework, in the scope of trajectory based operations, aiming to improve the cost-efficiency for airspace users (AUs) when facing ATFM regulations. The framework consists of four modules. The first one involves the AUs initially scheduling their preferred trajectories for all their flights. Based on this initial demand, the second module (assumed to be on the Network Manager -NM- side) detects time-varying hotspots (i.e. overloaded sectors along the day). In the third module, hotspot information is shared back to the AUs who plan alternative trajectory options to avoid crossing these congested airspace volumes (in the lateral and vertical domain); as well as providing to the NM different pre-tactical delay management preferences (including ground holding, linear holding, air holding and pre-tactical delay recovery); based on their internal cost breakdown structures. Incorporating all these potential combined options, the last module computes the best trajectory selections and the optimal distribution of delay assignments, such that the cost deviation from the initial status (all the user-preferred trajectories) is minimized. This model is formulated as mixed integer linear programming (MILP) and validated by a real-world case study focused on 24 h of traffic over the French airspace. Results using the proposed framework suggest a significant system delay reduction by nearly 97% over the existing method, whilst yielding an average of less than 100 kg extra fuel consumption and 50 Euro extra route charges for the 11% flights diverted to their alternative trajectories. Peer Reviewed