Machine Learning and Cognitive Ergonomics in Air Traffic Management: Recent Developments and Considerations for Certification

Resurgent interest in artificial intelligence (AI) techniques focused research attention on their application in aviation systems including air traffic management (ATM), air traffic flow management (ATFM), and unmanned aerial systems traffic management (UTM). By considering a novel cognitive human&ndash machine interface (HMI), configured via machine learning, we examined the requirements for such techniques to be deployed operationally in an ATM system, exploring aspects of vendor verification, regulatory certification, and end-user acceptance. We conclude that research into related fields such as explainable AI (XAI) and computer-aided verification needs to keep pace with applied AI research in order to close the research gaps that could hinder operational deployment. Furthermore, we postulate that the increasing levels of automation and autonomy introduced by AI techniques will eventually subject ATM systems to certification requirements, and we propose a means by which ground-based ATM systems can be accommodated into the existing certification framework for aviation systems. Document type: Articl

Trajectory optimisation for avionics-based GNSS integrity augmentation system

In this paper, trajectory optimisation algorithms developed specifically for the Global Navigation satellite System (GNSS) Avionics-Based Integrity Augmentation (ABIA) system are presented. The ABIA system is designed to increase the levels of integrity and accuracy (as well as continuity in multi-sensor data fusion architectures) of GNSS in a variety of mission- and safetycritical aviation applications. The trajectory optimisation algorithms can be employed both for flight planning as well as realtime optimisation of manned and unmanned aircraft for all flight phases. Three and six Degrees-of-Freedom (3-DoF/6-DoF) aircraft dynamics models are adopted to generate a number of feasible flight trajectories that also satisfy the GNSS constraints. A detailed simulation case study is presented to evaluate the performance of trajectory optimisation algorithms for GNSS integrity augmentation using an AIRBUS A320 3-DoF aircraft dynamics model. Results confirm that the employed trajectory optimisation algorithms are capable of supporting high-integrity tasks when GNSS is used as the primary source of navigation data

LIDAR Obstacle Warning and Avoidance System for Unmanned Aircraft

The availability of powerful eye-safe laser sources and the recent advancements in electro-optical and mechanical beam-steering components have allowed laser-based Light Detection and Ranging (LIDAR) to become a promising technology for obstacle warning and avoidance in a variety of manned and unmanned aircraft applications. LIDAR outstanding angular resolution and accuracy characteristics are coupled to its good detection performance in a wide range of incidence angles and weather conditions, providing an ideal obstacle avoidance solution, which is especially attractive in military low-level flying platforms such as helicopters and small-size Unmanned Aircraft (UA). In this paper we discuss the integration of the Laser Obstacle Avoidance "Marconi" (LOAM) system on candidate UA platforms. The original LOAM system design and the performed helicopter test activities are summarised, including a brief description of the system architecture and sensor characteristics, together with the system performance models and data processing algorithms for obstacle detection and classification. The paper presents the dynamic modelling and the avoidance trajectory generation algorithm for UA applications. A description of the future planned flight test activities is also included

Peripheral primitive neuroectodermal tumor of seminal vesicles: is there a role for relatively aggressive treatment modalities?

A 50 year old white man received an incidental ultrasound diagnosis of hypoechoic mass interesting the right seminal vesicle. A CT scan showed the presence of a 7.8 cm roundish cyst, originating from the right seminal vesicle. He had been followed by the removal of the right seminal vesicle and both the cystic lesion. The histological findings of the specimen documented the presence of small round cells compatible with Ewing's sarcoma/PPNET. The patient received also adjuvant chemotherapy and radiation treatment. After 10 years, the follow-up is still negative

Interaction between Neuroanatomical and Psychological Changes after Mindfulness-Based Training

Several cross-sectional studies have documented neuroanatomical changes in individuals with a long history of meditation, while a few evidences are available about the interaction between neuroanatomical and psychological changes even during brief exposure to meditation. Here we analyzed several morphometric indexes at both cortical and subcortical brain level, as well as multiple psychological dimensions, before and after a brief -8 weeks- Mindfulness Based Stress Reduction (MBSR) training program, in a group of 23 meditation naïve-subjects compared to age-gender matched subjects. We found a significant cortical thickness increase in the right insula and the somatosensory cortex of MBSR trainees, coupled with a significant reduction of several psychological indices related to worry, state anxiety, depression and alexithymia. Most importantly, an interesting correlation between the increase in right insula thickness and the decrease in alexithymia levels during the MBSR training were observed. Moreover, a multivariate pattern classification approach allowed to identify a cluster of regions more responsive to MBSR training across subjects. Taken together, these findings documented the significant impact of a brief MBSR training on brain structures, as well as stressing the idea of MBSR as a valuable tool for alexithymia modulation, also originally providing a plausible neurobiological evidence of a major role of right insula into mediating the observed psychological changes

Experimental flight testing of night vision imaging systems in military fighter aircraft

This paper describes the research and experimental flight test activities conducted by the Italian Air Force Official Test Centre (RSV), in collaboration with Alenia Aermacchi and Cranfield University, in order to confer night vision imaging systems (NVIS) capability to the Italian TORNADO Interdiction and Strike and Electronic Combat and Reconnaissance aircraft. The activities included design, development, test, and evaluation activities, including night vision goggle (NVG) integration, cockpit instruments, and external lighting modifications, as well as various ground test sessions and a total of 18 flight test sorties. RSV and Litton Precision Products were responsible for coordinating and conducting the installation of the internal and external lights. Particularly, an iterative process was established allowing in-site rapid correction of the major deficiencies encountered during the ground and flight test sessions. Both single-ship (day/night) and formation (night) flights were performed, with testing activities shared among the test crews involved, allowing for a redundant examination of the various test items by all participants. An innovative test matrix was developed and implemented by RSV for assessing the operational suitability and effectiveness of the various modifications implemented. Also important was the definition of test criteria for Pilot and Weapon Systems Officer workload assessment during the accomplishment of various operational tasks during NVG missions. Furthermore, the specific technical and operational elements required for evaluating the modified helmets were identified, allowing an exhaustive comparative evaluation of the two proposed solutions (i.e., HGU-55P and HGU-55G modified helmets). The initial compatibility problems encountered were progressively mitigated by incorporating modifications in both front and rear cockpits at various stages of the test campaign. This process allowed considerable enhancement of the TORNADO NVIS configuration, giving good medium- to high-level NVG operational capability to the aircraft. Further developments also include the internal/external lighting for the Italian TORNADO “Mid-Life Update” and other programs such as AMX aircraft internal/external light modification/testing and the activities addressing low-altitude NVG operations with fast jets (e.g., TORNADO, AMX, MB-339CD), with a major issue being the safe ejection of aircrew with NVG and NVG modified helmets. Two options have been identified for solving this problem, namely, the modification of the current Gentex HGU-55 helmets and the design of a new helmet incorporating a reliable NVG connection/disconnection device (i.e., a mechanical system fully integrated in the helmet frame) with embedded automatic disconnection capability in case of ejection. Other relevant issues to be accounted for in these new developments are the helmet dimensions and weight, the NVG usable field of view as a function of eye-relief distance, and the helmet's center of gravity (moment arms) with and without NVG (effect on aircrew fatigue during training and real operational missions

A new computational technique for the generation of optimised aircraft trajectories

A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection ε-constraint methods is proposed to solve multi-objective aircraft trajectory optimisation problems formulated as nonlinear optimal control problems. This technique is applicable to a variety of next-generation avionics and Air Traffic Management (ATM) Decision Support Systems (DSS) for strategic and tactical replanning operations. These include the future Flight Management Systems (FMS) and the 4-Dimensional Trajectory (4DT) planning and intent negotiation/validation tools envisaged by SESAR and NextGen for a global implementation. In particular, after describing the PSD method, the adaptive bisection ε-constraint method is presented to allow an efficient solution of problems in which two or multiple performance indices are to be minimized simultaneously. Initial simulation case studies were performed adopting suitable aircraft dynamics models and addressing a classical vertical trajectory optimisation problem with two objectives simultaneously. Subsequently, a more advanced 4DT simulation case study is presented with a focus on representative ATM optimisation objectives in the Terminal Manoeuvring Area (TMA). The simulation results are analysed in-depth and corroborated by flight performance analysis, supporting the validity of the proposed computational techniques.peer-reviewe

EFESTO-2: European Flexible Heat Shields Advanced TPS Design and Tests for Future In-Orbit Demonstration - 2

EFESTO-2 is an EU-funded project under Horizon Europe that aims to enhance European expertise in Inflatable Heat Shields (IHS). Building on the achievements of the previous EFESTO project (H2020 funds No 821801), EFESTO-2 focuses on advancing key IHS technologies to increase their Technology Readiness Level (TRL). The project pillars include analyzing the business case for IHS applications, exploring additional aspects of IHS, improving tools and models, and establishing a development roadmap for IHS systems. This paper outlines the project objectives and plan, highlighting ongoing and future activities for the next two years, positioning it within the European re-entry technology roadmap. Funding was provided by the European Union's Horizon Europe program (grant agreement No 1010811041)

Machine Learning and Cognitive Ergonomics in Air Traffic Management: Recent Developments and Considerations for Certification

Resurgent interest in artificial intelligence (AI) techniques focused research attention on their application in aviation systems including air traffic management (ATM), air traffic flow management (ATFM), and unmanned aerial systems traffic management (UTM). By considering a novel cognitive human–machine interface (HMI), configured via machine learning, we examined the requirements for such techniques to be deployed operationally in an ATM system, exploring aspects of vendor verification, regulatory certification, and end-user acceptance. We conclude that research into related fields such as explainable AI (XAI) and computer-aided verification needs to keep pace with applied AI research in order to close the research gaps that could hinder operational deployment. Furthermore, we postulate that the increasing levels of automation and autonomy introduced by AI techniques will eventually subject ATM systems to certification requirements, and we propose a means by which ground-based ATM systems can be accommodated into the existing certification framework for aviation systems

GNSS Performance Modelling and Augmentation for Urban Air Mobility

One of the primary challenges facing Urban Air Mobility (UAM) and the safe integration of Unmanned Aircraft Systems (UAS) in the urban airspace is the availability of robust, reliable navigation and Sense-and-Avoid (SAA) systems. Global Navigation Satellite Systems (GNSS) are typically the primary source of positioning for most air and ground vehicles and for a growing number of UAS applications; however, their performance is frequently inadequate in such challenging environments. This paper performs a comprehensive analysis of GNSS performance for UAS operations with a focus on failure modes in urban environments. Based on the analysis, a guidance strategy is developed which accounts for the influence of urban structures on GNSS performance. A simulation case study representative of UAS operations in urban environments is conducted to assess the validity of the proposed approach. Results show improved accuracy (approximately 25%) and availability when compared against a conventional minimum-distance guidance strategy