Abstract

International audience; This paper describes a study to develop an intelligent air traffic ground control operation system that is able to integrate initiatives from both controllers andautonomous vehicles. We use a multi-agent approach to optimize dynamically a routing and scheduling task while taking into account real-time human suggestions. Weexpect that such mixed-initiative systems combined with autonomous vehicles will permit reduction of congestion and fuel consumption in large airports.

Abstract

n Terminal Manoeuvring Area (TMA) at hub airports is the main problem in Chinese air transportation system. At most of the hub airports, the capacity is near saturated or even overloaded. Civil Aviation Administration of China (CAAC) reported that Air Traffic Management (ATM) is the main cause of delays. Despite the already overloaded ATM system, the Chinese airplanes fleet is continuing to expand. China will become the largest traffic flow in the world before the end of 2035. There is an urgent need to develop a new more efficient method for sequencing and merging arrival flows in TMA, so that airports can maximise the benefits from the emerging Communication, Navigation and Surveillance (CNS) techniques, and consequently increasing capacity. Automation can be highly efficient in ATM, however, due to safety considerations, full automation in ATM is still a challenge. Facing extremely dense operations in complex TMA, we can consider reducing traffic complexity by solving all potential conflicts in advance with a feasible trajectory control for controllers, or automating a large proportion of routine operations, such as sequencing, merging and spacing. As parallel runways are a common structure of Chinese hub airports, in this thesis, we propose a novel system to integrated sequencing and merging aircraft to parallel runways. Our methodology integrates a Area Navigation (RNAV)-based 3D Multi-Level and Multi-Point Merge System (MLMPMS), a hybrid heuristic optimization algorithm and a simulation module to find good, systematic, operationally-acceptable solutions. First, a Receding Horizon Control (RHC) technique is applied to divide 24-hour traffic optimization problem into several sub-problems. Then, in each sub-problem, a tailored Simulated Annealing (SA) algorithm and a trajectory generation module worn together to find a near-optimal solution. Our primary objective is to rapidly generate conflict-free and economical trajectories with easy, flexible and feasible control methods. Based on an initial solution, we continuously explore possible good solutions with less delay and shorter landing interval on runway. Taking Beijing Capital International Airport (BCIA) as a case to study, numerical results show that our optimization system performs well. First, it has very stable de-conflict performance to handle continuously dense traffic flows. Compared with Hill Climbing (HC), the tailored SA algorithm can always guarantee a conflict-free solution not only for the mixed iii or segregated parallel approach (arrivals only) pattern, but also for the independent parallel operation (integrated departures and arrivals) pattern. Second, with its unique Multi-Level Point Merge (ML-PM) route network, it can provide a good trajectory control solution to efficiently and economically handle different kinds of arrival flows. It can realize a shorter flying time and a near-Continuous Descent Approach (CDA) descent for arrival aircraft, compared with baseline. For normal traffic, with near-equal traffic demand for two runways, with landing balancing function ON, the average flying time on different Standard Terminal ARrival (STAR) routes can be reduced up to 8 minutes compared with the baseline. It also realizes an easier re-sequencing of aircraft with more relaxed position shifting as well, compared with conventional sequencing method. Theoretically, the Maximum Position Shifting (MPS) can be up to 6 positions, overcoming the hard constraint of 3 position shifts (MPS "= 3). For asymmetric traffic, with big difference on traffic demand for two runways, with runway balancing function ON, it is more likely to find a conflict-free solution compared with the runway balancing function OFF, and again reduces the average flying time. Third, it is efficient for the segregated parallel approach patterns. Compared with hard constrained position shifting, which is often used in current Arrival Manager (AMAN) system and controller’s manual-control First Come First Served (FCFS) method, it can reduce the average delay, average additional transit time in super dense arrival situations. The average time flown level per flight is less than 12% of total transit time in TMA. Fourth, in independent parallel patterns, it can provide a range of useful information concerning the associated objective value, the average flying time, crossing trajectories in hot spots between arrivals and departures, the efficiency of using different designed sequencing legs in ML-PM route network. Thus, it helps the Air Navigation Service Provider (ANSP) to find the best configuration of ML-PM route network to efficiently satisfy the traffic demand. Last but not least, the computation time of our system is reasonable. It generally needs around 290s-350s for 2 hours of heavy traffic demand with the mixed parallel approach. In conclusion, theoretically, our system realizes good trajectory planning of dense flows at busy airports. It can guarantee a conflict-free solution, increase runway throughput, and minimize delay. At the same time, it can simplify merging, re-sequencing, and improve the economical descent profile with advanced ML-PM route design. Although the methodology defined here is illustrated using the BCIA airport, it could be easily applied to airports worldwide.; La congestion dans les Terminal Manoeuvring Area (TMA) des aéroports en hub est le principal problème dans le transport aérien chinois. Face au trafic extrêmement dense dans les TMAs, nous pouvons envisager d'automatiser une grande partie des opérations de routine, comprenant la planification, le séquencement et la séparation. Nous proposons dans cette thèse un nouveau système automatisé de séquencement des avions et de fusion des flux vers des pistes parallèles, qui sont utilisées dans la plupart des aéroports chinois. Notre méthodologie intègre un réseau de route 3D nommé Multi-Level and Multi-Point Merge System (MLMPMS) basé sur le concept de l'Area Navigation (RNAV) et un algorithme d'optimisation heuristique hybride pour trouver une solution correcte, opérationnellement acceptable. Un algorithme de Simulated Annealing (SA) spécifique et un module de génération de trajectoire collaborent pour rechercher la solution quasi optimale. Notre objectif est de générer en temps réel des trajectoires sans conflit, minimisant la consommation de carburant et permettant des méthodes de contrôle faciles et flexibles. Dans ce but, nous explorons en permanence les solutions possibles avec le moins de retard et assuront l'atterrissage le plus rapide. Nous déterminons quatre variables de décision pour contrôler chaque vol : l'heure et la vitesse d'entrée dans la TMA, le temps de vol sur l'arc de séquencement et le choix de la piste utilisée. La simulation de trajectoire dans les différentes phases de vol est basée sur le modèle de performances BADA. Dans le cas de l'aéroport de Beijing Capital International Airport (BCIA), les résultats numériques montrent que notre système d'optimisation de bonnes performances sur le séquencement et la fusion des trajectoires. Tout d'abord, il permet d'assurer des performances de résolution conflit très stables pour gérer les flux de trafic continuellement denses. Par rapport à l'algorithme Hill Climbing (HC), le SA peut toujours trouver une solution sans conflit, non seulement pour l'approche parallèle mixte ou séparée~(pour les arrivées), mais aussi pour les configurations parallèles indépendantes~(départs et arrivées intégrés). Ensuite, avec un réseau d'itinéraires Multi-Level Point Merge (ML-PM) unique, il peut fournir une bonne solution de contrôle de la trajectoire pour traiter efficacement et économiquement différents types de flux d'arrivée. Il peut réaliser un temps de vol plus court et une descente vers le bas en Continuous Descent Approach (CDA) pour l'avion d'arrivée. Il peut réaliser un re-séquencement plus facile des avions avec un déplacement de position plus relâché. Théoriquement, les Maximum Position Shifting (MPS) peuvent atteindre 6 positions, surpassant la contrainte difficile de 3 positions. Troisièmement, l'algorithme montre son efficacité dans un modèle d'approche parallèle séparé avec une capacité de séquencement plus relâché. Par rapport au décalage de position forcé dur, qui est souvent utilisé dans le système actuel Arrival Manager (AMAN) et la méthode First Come First Served (FCFS) utilisé par les contrôleurs, il peut réduire le délai et le temps de transit moyens dans une situation d'arrivée très dense. Le palier par vol est inférieur à 12\\% du temps de transit total dans la TMA. Quatrièmement, en configuration parallèle indépendant, il peut fournir des informations différentes concernant la valeur objectif associée, le temps de vol moyen, les trajectoires de croisement en point chaud entre les arrivées et les départs, l'efficacité avec différents arcs de séquencement conçus dans le réseau de route ML-PM etc.. Enfin, le temps de calcul de notre système est raisonnable. Il nécessite généralement environ 290s-350s pour 2 heures de forte demande de trafic avec une approche parallèle mixte. En conclusion, théoriquement, notre système réalise une bonne planification de trajectoire en flux denses. Il peut assurer une solution sans conflit, augmenter le débit, minimiser le délai. Dans le même temps, il peut simplifier la fusion, le re-séquencement, l'amélioration du profil de descente économique associé avec la conception de l'itinéraire avancé ML-PM. Bien que la méthodologie définie ici soit appliquée à l'aéroport BCIA, elle pourrait également être appliquée à d'autres aéroports dans le monde.

Abstract

International audience; In past decades, airport ground operations have attracted researchers, with the aim of increasing airport efficiency and reducing the environmental impact of airport operations. Airplane taxi operations have received particular attention for their significant impact on the airport efficiency and pollutant emissions and on the fuel cost for airlines. Alternative solutions have been proposed to the engine-on taxi procedures, including the employment of autonomous vehicles to tow the aircraft between gates and runways. In order to be performed, autonomous taxi procedures require precise planning and scheduling by means of sophisticated management systems. At the base of these management systems, lie algorithms for the solution of the routing problem, which provide feasible paths on the airport surface. Two different approaches can be used: compute the paths on the fly, or pre-compute all the possible paths between all the pairs of starting/ending points on the airport grid and store them in a database that is called when needed. In this paper, four different algorithms are implemented and compared for the computation of paths on the fly: two Hopfield-type neural networks and two algorithms based on graph theory. Furthermore, two algorithms for the generation of the path database are presented: a modified version of the Breadth-first search and an implementation of the k-shortest paths algorithm. Each taxi mission, performed by the tractors, consists of three different events, called phases: one central towing phase, where the tractor tows the aircraft between gate and runway and two repositioning phases in which the tractors move from its actual position to the airplane or from the airplane back to the depot.

Abstract

International audience; In air transportation, especially in airport safety, radar tracks are continuously recorded and may be used for detecting incidents on airport surface. However, all known statistical algorithms, even those based on functional data, are unable to distinguish between a safety critical flight and another one departing from standard behavior, but otherwise safe. In this work, we propose a change of paradigm by representing curves as points in a shape manifold. In this framework, it is possible to use Finsler distances between shapes that explicitly take into account the second derivative and can be able to 1 correctly detect skid situations from deviant trajectories that cannot be considered as a slipped trajectory. This metric is next used in curve clustering for detecting bad runway conditions. Some results on datasets of synthetic and real trajectories are presented, as well as a comparison of existing metrics.; Sur la plupart des plateformes aéroportuaires, les déplacements des aéronefs sont enregistrés en continu par des radars de surveillance et les trajectoires ainsi obtenues peuvent être utilisées pour détecter ou prévenir des incidents lors du roulage, en particu-lier des dérapages. Cependant, l'exploitation de ces données est rendue difficile par le fait que les algorithmes statistiques connus, même ceux basés sur des données fonctionnelles, ne sont pas capables de distinguer les situations réellement dangereuses des déviations au comportement standard qui sont sans gravité. Dans cette étude, nous proposons un chan-gement de paradigme en représentant les trajectoires comme des points dans un espace de formes. Dans ce nouveau cadre, il est possible de construire des distances de type Fins-ler, prenant explicitement en compte les dérivées secondes des trajectoires, et qui sont en mesure de bien séparer les trajectoires présentant un dérapage de celles dont la déviation par rapport au comportement nominal n'est pas due à un manque d'adhérence. Cette métrique est ensuite utilisée dans des méthodes de clustering pour détecter un mauvais état de la piste d'atterrissage. Des résultats sur des jeux de données de trajectoires syn-thétiques et réelles sont présentés ainsi qu'une comparaison avec des métriques existantes. Mots-clés. Similarité entre courbes, espace de formes, données fonctionnelles, classification non supervisée de courbes, sécurité aéroportuaire.

Abstract

International audience; Increasing the level of automation in air traffic management is seen as a measure to increase the performance of the service to satisfy the predicted future demand. This is expected to result in new roles for the human operator: he will mainly monitor highly automated systems and seldom intervene. Therefore, air traffic controllers (ATCos) would often work in a supervisory or control mode rather than in a direct operating mode. However, it has been demonstrated how human operators in such a role are affected by human performance issues, known as Out-Of-The-Loop (OOTL) phenomenon, consisting in lack of attention, loss of situational awareness and de-skilling. A countermeasure to this phenomenon has been identified in the adaptive automation (AA), i.e., a system able to allocate the operative tasks to the machine or to the operator depending on their needs. In this context, psychophysiological measures have been highlighted as powerful tool to provide a reliable, unobtrusive and real-time assessment of the ATCo’s mental state to be used as control logic for AA-based systems. In this paper, it is presented the so-called “Vigilance and Attention Controller”, a system based on electroencephalography (EEG) and eye-tracking (ET) techniques, aimed to assess in real time the vigilance level of an ATCo dealing with a highly automated human–machine interface and to use this measure to adapt the level of automation of the interface itself. The system has been tested on 14 professional ATCos performing two highly realistic scenarios, one with the system disabled and one with the system enabled. The results confirmed that (i) long high automated tasks induce vigilance decreasing and OOTL-related phenomena; (ii) EEG measures are sensitive to these kinds of mental impairments; and (iii) AA was able to counteract this negative effect by keeping the ATCo more involved within the operative task. The results were confirmed by EEG and ET measures as well as by performance and subjective ones, providing a clear example of potential applications and related benefits of AA. Document type: Article