This paper addresses the generation of aircraft emergency trajectories with obstacle avoidance. After presenting in detail the fast marching tree algorithm, in this paper we propose an improvement of its performance. First, the free space checking function is sped up. Then, the algorithm is used twice, firstly with the sampling of a few points to generate an approximate trajectory, and secondly with a sampling of points close to the first computed trajectory to refine it. The proposed method significantly reduces the computing time of the emergency geometric trajectory generation.

This paper addresses the design of conflict free trajectories for sets of flights crossing areas subject to wind and meteorological hazards. After presenting the collaborative process based on first come first served principle, a dynamic Fast Marching Tree Star algorithm is proposed. The algorithm first computes initial avoidance trajectories and then updates them according to the new position of the hazard areas. Smart samplings are also proposed to reduce as much as possible the computing times. Indeed, the method generates in less than 1 second avoidance trajectories and guarantees safety. Then, a discussion on this method is conducted and shows its inequity. First simulations illustrate the proposed solution approach with promising results. However, to enhance equity between aircraft, the method is improved through a fairer collaborative process.

Aircraft trajectory is one of the most fundamental objects in air traffic management. Its optimization is essential to ensure efficient and sustainable aviation. This survey proposes to study all the phases of a flight, from its prediction several days before day of flight to the landing of the aircraft, including also the study of a possible emergency situation. Each phase of flight raises different issues and is subject to particular constraints. These guide the choice of potentially usable optimization methods. This study proposes, from the context, the issues, and existing studies, a methodology to identify the most appropriate solution algorithms for optimizing each phase of flight. This methodology is based on 5 evaluation criteria: optimality, computing time, adaptability, memory usage, and multi-trajectories. Finally, thanks to it, some methods are compared based on their consistency with solving problem associated to each phase of flight.

We present a software prototype (SafeNcy) capable of automatically choosing and ranking landing sites for emergency situations and of generating four-dimensional (4D) trajectories towards these sites. We describe the modules composing this framework, together with their main capabilities, interactions and the workflow of the full integrated system. Different types of emergencies are firstly categorized. Then, for each type of emergency, landing sites—including off-airport locations—are ranked, and speed and vertical trajectory descent profiles are tailored accordingly. These algorithms take into account several data from different sources, such as terrain databases, weather forecasts and aircraft performance models. We outline a new concept of operations aiming to integrate SafeNcy into the current aircraft operations and air traffic management paradigms. Several scenarios, focusing on total engine flame-out situations, are described and used to validate the framework, as well as to show its main features. The scenarios were designed in cooperation with a group of expert pilots and engineers. SafeNcy is expected to be an additional function for advanced and extended flight management systems, alleviating flight crew’s workload and contributing to a more digital cockpit. It could also be a technical enabler for future unmanned or highly-automated aviation.