The future of UAS: standards, regulations, and operational experiences [workshop report]

This paper presents the outcomes of "The Future of UAS: Standards, Regulations and Operational Experiences" workshop, held on the 7th and 8th of December, 2006 in Brisbane, Queensland, Australia. The goal of the workshop was to identify recent international activities in the Unmanned Airborne Systems (UAS) airspace integration problem. The workshop attracted a broad cross-section of the UAS community, including: airspace and safety regulators, developers, operators and researchers. The three themes of discussion were: progress in the development of standards and regulations, lessons learnt from recent operations, and advances in new technologies. This paper summarises the activities of the workshop and explores the important outcomes and trends as perceived by the authors

Real-time simulations to evaluate the RPAS integration in shared airspace

This paper presents the work done during the first year in the WP-E project ERAINT (Evaluation of the RPAS-ATM Interaction in Non-Segregated Airspace) that intends to evaluate by means of human-in-the-loop real-time simulations the interaction between a Remotely Piloted Aircraft System (RPAS) and the Air Traffic Management (ATM) when a Remotely Piloted Aircraft (RPA) is being operated in shared airspace. This interaction will be evaluated from three different perspectives. First, the separation management, its results are presented in this paper. Secondly, during the next year, the contingency management, also including loss of link situations and, lastly, the capacity impact of such operations in the overall ATM system. The used simulation infrastructure allows to simulate realistic exercises from both the RPAS Pilot-in-Command (PiC) and the Air Traffic Controller (ATCo) perspectives. Moreover, it permits to analyze the actual workload of the ATC and to evaluate several support tools and different RPAS levels of automation from the PiC and ATC sides. The simulation results and the usefulness of the support tools are presented for each selected concept of operations.Peer ReviewedPostprint (published version

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., party-line transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Centers Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events

UAS in the Airspace: A Review on Integration, Simulation, Optimization, and Open Challenges

Air transportation is essential for society, and it is increasing gradually due to its importance. To improve the airspace operation, new technologies are under development, such as Unmanned Aircraft Systems (UAS). In fact, in the past few years, there has been a growth in UAS numbers in segregated airspace. However, there is an interest in integrating these aircraft into the National Airspace System (NAS). The UAS is vital to different industries due to its advantages brought to the airspace (e.g., efficiency). Conversely, the relationship between UAS and Air Traffic Control (ATC) needs to be well-defined due to the impacts on ATC capacity these aircraft may present. Throughout the years, this impact may be lower than it is nowadays because the current lack of familiarity in this relationship contributes to higher workload levels. Thereupon, the primary goal of this research is to present a comprehensive review of the advancements in the integration of UAS in the National Airspace System (NAS) from different perspectives. We consider the challenges regarding simulation, final approach, and optimization of problems related to the interoperability of such systems in the airspace. Finally, we identify several open challenges in the field based on the existing state-of-the-art proposals

Engage D3.5 Opportunities for innovative ATM research (interim report)

This document reports on the topics and academic disciplines of past Exploratory Research projects, notably SESAR Workpackage E (long-term and innovative research) and SESAR Exploratory Research (ER) with a view of tracing the evolution of research as well as opportunities for future research. This analysis is complemented with relevant activities in Engage, such as the Engage thematic challenges

A novel framework to assess the wake vortex hazards risk supported by aircraft in en-route operations

The work presented in this paper was partially funded by the SESAR Joint Undertaking under grant agreement No 699247, as part of the European Union’s Horizon 2020 research and innovation programme: R-WAKE project (Wake Vortex Simulation and Analysis to Enhance En-route Separation Management in Europe - http://www.rwake-sesar2020.eu/). TThis paper presents the simulation environment developed within the framework of R-WAKE project, funded by SESAR 2020 Exploratory Research. This project aims to investigate the risks and hazards of potential wake vortex encounters in the en-route airspace, under current and futuristic operational scenarios, in order to support new separation standards aimed at increasing airspace capacity. The R-WAKE simulation environment integrates different components developed by different partners of the R-WAKE consortium, including simulators for weather, traffic, wake vortex phenomena, wake vortex interactions and different tools and methodologies for safety and risk assessment. A preliminary example is presented in this paper, in which 200 historical trajectories were simulated to show that the novel framework works properly. A WVE encounter has been detected in such first scenario, however with no significant safety effect on the follower aircraft. A second controlled scenario has been then run to force the detection of a severe wake encounter under realistic en-route conditions. Such scenario has given evidences that confirm the safety relevance of the underlying research concept.Peer ReviewedPostprint (published version

Learning-based perception and control with adaptive stress testing for safe autonomous air mobility

The use of electrical vertical takeoff and landing (eVTOL) aircraft to provide efficient, high-speed, on-demand air transportation within a metropolitan area is a topic of increasing interest, which is expected to bring fundamental changes to the city infrastructures and daily commutes. NASA, Uber, and Airbus have been exploring this exciting concept of Urban Air Mobility (UAM), which has the potential to provide meaningful door-to-door trip time savings compared with automobiles. However, successfully bringing such vehicles and airspace operations to fruition will require introducing orders-of-magnitude more aircraft to a given airspace volume, and the ability to manage many of these eVTOL aircraft safely in a congested urban area presents a challenge unprecedented in air traffic management. Although there are existing solutions for communication technology, onboard computing capability, and sensor technology, the computation guidance algorithm to enable safe, efficient, and scalable flight operations for dense self-organizing air traffic still remains an open question. In order to enable safe and efficient autonomous on-demand free flight operations in this UAM concept, a suite of tools in learning-based perception and control systems with stress testing for safe autonomous air mobility is proposed in this dissertation. First, a key component for the safe autonomous operation of unmanned aircraft is an effective onboard perception system, which will support sense-and-avoid functions. For example, in a package delivery mission, or an emergency landing event, pedestrian detection could help unmanned aircraft with safe landing zone identification. In this dissertation, we developed a deep-learning-based onboard computer vision algorithm on unmanned aircraft for pedestrian detection and tracking. In contrast with existing research with ground-level pedestrian detection, the developed algorithm achieves highly accurate multiple pedestrian detection from a bird-eye view, when both the pedestrians and the aircraft platform are moving. Second, for the aircraft guidance, a message-based decentralized computational guidance algorithm with separation assurance capability for single aircraft case and multiple cooperative aircraft case is designed and analyzed in this dissertation. The algorithm proposed in this work is to formulate this problem as a Markov Decision Process (MDP) and solve it using an online algorithm Monte Carlo Tree Search (MCTS). For the multiple cooperative aircraft case, a novel coordination strategy is introduced by using the logit level-$k$ model in behavioral game theory. To achieve higher scalability, we introduce the airspace sector concept into the UAM environment by dividing the airspace into sectors, so that each aircraft only needs to coordinate with aircraft in the same sector. At each decision step, all of the aircraft will run the proposed computational guidance algorithm onboard, which can guide all the aircraft to their respective destinations while avoiding potential conflicts among them. In addition, to make the proposed algorithm more practical, we also consider the communication constraints and communication loss among the aircraft by modifying our computational guidance algorithms given certain communication constraints (time, bandwidth, and communication loss) and designing air-to-air and air-to-ground communication frameworks to facilitate the computational guidance algorithm. To demonstrate the performance of the proposed computational guidance algorithm, a free-flight airspace simulator that incorporates environment uncertainty is built in an OpenAI Gym environment. Numerical experiment results over several case studies including the roundabout test problem show that the proposed computational guidance algorithm has promising performance even with the high-density air traffic case. Third, to ensure the developed autonomous systems meet the high safety standards of aviation, we propose a novel, simulation driven approach for validation that can automatically discover the failure modes of a decision-making system, and optimize the parameters that configure the system to improve its safety performance. Using simulation, we demonstrate that the proposed validation algorithm is able to discover failure modes in the system that would be challenging for humans to find and fix, and we show how the algorithm can learn from these failure modes to improve the performance of the decision-making system under test

Risk Assessment in Air Traffic Management

One of the most complex challenges for the future of aviation is to ensure a safe integration of the expected air traffic demand. Air traffic is expected to almost double its current value in 20 years, which cannot be managed without the development and implementation of a safe air traffic management (ATM) system. In ATM, risk assessment is a crucial cornerstone to validate the operation of air traffic flows, airport processes, or navigation accuracy. This book tries to be a focal point and motivate further research by encompassing crosswise and widespread knowledge about this critical and exciting issue by bringing to light the different purposes and methods developed for risk assessment in ATM

La configuració U-space impacta en la seguretat, capacitat i flexibilitat

El present treball de final de grau està enfocat a l'estudi del concepte U-space, els seus actuals i futurs serveis i procediments per a permetre l'accés de UAVs a l'espai aeri de manera segura, eficient i flexible, i l'anàlisi dels resultats de simulacions estudiant com a diferents configuracions de l'espai aeri impacten en la flexibilitat i capacitat del sistemaEl presente trabajo de final de grado está enfocado al estudio del concepto U-space, sus actuales y futuros servicios y procedimientos para permitir el acceso de UAVs al espacio aéreo de forma segura, eficiente y flexible, y el análisis de los resultados de simulaciones estudiando como diferentes configuraciones del espacio aéreo impactan en la flexibilidad y capacidad del sistemaThe present final degree study is focused on the exploration of the U-space concept, its current and future services and procedures to allow the access of UAVs to the airspace in a safe, efficient and flexible way, and the analysis of the results of simulations studying how different airspace configurations impact on the flexibility and capacity of the syste

System elements required to guarantee the reliability, availability and integrity of decision-making information in a complex airborne autonomous system

Current air traffic management systems are centred on piloted aircraft, in which all the main decisions are made by humans. In the world of autonomous vehicles, there will be a driving need for decisions to be made by the system rather than by humans due to the benefits of more automation such as reducing the likelihood of human error, handling more air traffic in national airspace safely, providing prior warnings of potential conflicts etc. The system will have to decide on courses of action that will have highly safety critical consequences. One way to ensure these decisions are robust is to guarantee that the information being used for the decision is valid and of very high integrity. [Continues.