Abstract

The current system of Air Traffic Control (ATC) relies on a centralized control architecture. At its core, this system is heavily dependent on manual intervention by human Air Traffic Controllers (ATCos) to ensure safe operations. The capacity of this system is, therefore, closely tied to the maximum workload that can be tolerated by ATCos. Although this system has served the needs of the air transportation industry thus far, the increasing delays and congestion reported in many areas indicates that the current centralized operational model is rapidly approaching saturation levels. To cope with the expected future increases of traffic demand, many researchers have proposed a transition to a decentralized traffic separation paradigm in en route airspaces. Although there are several variants of decentralized ATC, this thesis focuses on a variant known as self-separation. In self-separated airspace, each individual aircraft is responsible for its own separation with all surrounding traffic. To facilitate self-separation, significant research effort has been devoted towards the development of new algorithms for automated airborne Conflict Detection and Resolution (CD&R). However, in spite of over two decades of active research highlighting its theorized benefits, decentralization/self-separation is yet to be deployed in the field. From a technical point of view a lack of understanding on three open issues namely airspace design, airspace safety modeling, and airspace capacity modeling, have impeded its further development and implementation. The goal of this research is to address these three open problems in order to bring self-separated ATC closer to reality. Consequently, the main body of this thesis is divided into three parts, with each part tackling one of the three aforementioned open problems...

Abstract

International audience; Regulations from the ICAO use the term Well Clear without defining it. Now, this definition is needed to design air traffic Detect And Avoid systems. A definition is currently discussed at the ICAO level, with work on the associated Remain Well Clear (RWC) function underway at standardisation bodies level (RTCA, EUROCAE). But many members of the communities impacted by these works are not well aware of their state. To adress this lack of awareness, this paper provides three contributions. First, it derives from ICAO texts the components of a RWC function: boundaries, alerts and guidances. These are linked to essential elements required to define the Well Clear term: a start and end, the actors involved, and the expected actions. Second, it summarizes the current regulatory efforts in RTCA, EUROCAE and ICAO regarding the Well Clear and Remain Well Clear notions. Third, it proposes discussion topics to move forward. From a DAA perspective, the notion of Well Clear is key to unlock RPAS full integration, i.e. operation in all classes of airspaces. Though existing works make good progress, the ressources engaged on this topic seem insufficient when compared with the complexity and importance of the task at hand.

Abstract

traffic predictability is paramount in the air traffc system in order to enable concepts such as Trajectory Based Operations (TBO) and higher automation levels for self-separation. Whereas in simulated environments 4D conflict-free trajectory optimisation has shown good potential in the improvement of air traffc effciency, its application to real operations has been very challenging due to the current lack of information sharing between airspace users. Consequently, such operations are still very limited in scope and rarely attempted in dense traffic situations. Better predictability of other traffc future states would be an enabler for each aircraft to fly its user preferred route without decreasing safety in a self-separation context. But this is not an easy task when basic aircraft parameters such as aircraft weight, performance data or airline strategies are not available at the time of prediction. In this paper the authors propose to compensate this hindrance by continuously integrating the state of the surounding traffc to improve the ownship's knowledge of other aircraft's dynamics. Specifically, conventional position (and velocity) messages, as coming from Automatic Dependent Surveillance Broadcast (ADS-B), are integrated at the ownship. Then, an optimisation problem is formulated, using optimal control theory, that minimises the error with the known states, having the parameters of study (i.e. mass) as decision variables. A scenario with two departing trajectories is used to demonstrate the e ectiveness of this parameter estimation method. In it, the take-off mass of the potential intruder is estimated on- board the ownship and its impact to conflict detection and resolution is presented, demonstrating the big improvements in predictability and safety. Peer Reviewed Document type: Conference object

Abstract

ft need to be separated from other aircraft by either a minimum vertical distance of 1000ft or by a minimum horizontal distance of 5NM to avoid mid-air collisions. Traffic Alert and Collision Avoidance System (TCAS) work well as a tactical safety backups to avoid collision, but cannot perform separation assurance. This paper presents the design aspects of system that would predict separation infringement and provide flight crew with necessary guidance for maintaining separation. This paper discusses formulation of system function based on ADS-B, mathematical models, simulation and results. A system model has been implemented in MATLAB and various encounters with different speed ratios at various conflict angles has been fed as input to system model with a goal of avoidance and recovery to original waypoint. Both Heading and Speed maneuvers are evaluated and results are presented. The required strength of resolution maneuver as a function of conflict geometry is studied and automatic maneuver selection function is implemented in system model and maneuver selection function is evaluated with discussion of results.

Abstract

International audience; In the near future, air traffic control (ATC) will have to cope with a radical change in the structure of air transport [1]. Apart from the increase in traffic that will push the system to its limits, the insertion of new aerial vehicles such as drones into the airspace, with different flight performances, will increase its heterogeneity. Current research aims at increasing the level of automation and partial delegation of the control to on-board systems. In this work, we investigate the collision avoidance management problem using a decentralized distributed approach. We propose an autonomous and generic multi-agent system to address this complex problem. We validate our system using state-of-the-art benchmarks. The results underline the adequacy of our local and cooperative approaches to efficiently solve the studied problem.