Aviation is going to change dramatically in the next decade. Urban air mobility will rise, employing drones and sky taxis. By 2030, single pilot operations will probably become a reality. The use of Artificial Intelligence (AI) and intelligent assistants in aviation will not only affect the flight deck but also air traffic and airport operations. These changes represent nothing short of a paradigm shift to next generation aviation. A shift that will change the way we use and think about air transport.
The Chartered Institute of Ergonomics & Human Factors has just released a new white paper exploring the human factors challenges we need to overcome to ensure the safety of the aviation system during this transition. They introduced the white paper “The human dimension in tomorrow’s aviation system” through a free webinar led by Barry Kirwan (EUROCONTROL), Scientific Coordinator of the European research project SAFEMODE. Kathryn Jones (CAA), Suzy Broadbent (BAE Systems), Don Harris (Coventry University), and Andy Batty (BAE Systems) also joined the webinar to provide viewpoints from the civil and military domains on the uncharted journey that aviation is about to undertake.
On-demand on the CIEHF website, you can listen again to the webinar or just download the white paper. The document focuses on the integration of drones, and the implementation of AI and the Single Pilot operations as the most prominent innovations in future aviation. Deep Blue has been exploring these issues for years now in a number of EU-funded research projects. Have a look below at our past and on-going research on these hot topics.
Drones on the rise
By 2022, it is supposed that 8 million drones will cross the skies of Europe. Urban Air Mobility will probably see the biggest increase, with unmanned aerial vehicles providing a variety of services. For example, drones may perform transport infrastructure inspections.
Currently, we are part of Drones4Safety. This project aims at developing a system of autonomous, self-charging, and collaborative drones swarms that can inspect transport infrastructures in a continuous operation setting. Deep Blue joined the project as regulation expert, being also involved in the AW-Drones project.
AW-Drones specifically supports the rulemaking process for the definition of rules, technical standards, and procedures for civilian drones in Europe. To this end, the project will produce an Open Repository of existing technical standards and “best practices”, which will help the European Aviation Safety Agency and the European Commission in their rulemaking process. In addition, the project will propose the most suitable technical standards to comply with existing regulation for all relevant categories of drones operations. Overall, these two outcomes will help to enable safe and reliable drone operations in the European Union.
Safe and efficient use of drones will require their integration into the existing air traffic control procedures and infrastructures. That is why the URClearED project is investigating sense-and-avoid mechanisms for drones. They will allow drones to ensure conflict-free paths, similar to how remain-well-clear (RWC) does with aircrafts to prevent conflict situations.
Similarly, INVIRCAT tackles the rising concerns about safety related to drones within airport manoeuvring areas. The project aims specifically at the safe integration of drones into the existing air traffic control procedures and infrastructures within terminal manoeuvring areas under Instrument Flight Rules.
Artificial Intelligence in aviation
In the near future, Artificial Intelligence will revolutionise aviation. The sector will undertake unprecedented changes. At the moment, autonomous flights are a possibility yet to come; but already, we are using AI to achieve a better integration between human and machine. An integration that will bring more safety and efficiency in the aviation system.
The MAHALO project, which we are coordinating, deals with automation, Artificial Intelligence, and Machine Learning. It aims to answer a simple, yet profound question: should we be developing automation that is conformal to the human, or should we be developing automation that is transparent to the human? Overall, Mahalo will add knowledge on how AI and transparency can improve Air Traffic Management (ATM) performance, capacity, and safety.
The ARTIMATION project addresses the same challenge related to the transparency of AI. Specifically, it deals with the AI algorithms behind the automated system that perform autonomous decision-making in ATM. Most of the time, automated systems are not trusted by their users as the decisions they provide are opaque. In this context, ARTIMATION explores the domain of Explainable Artificial Intelligence (XAI) to provide a model that ensures transparency. This will grant safe and reliable decision support to air traffic management.
Artificial Intelligence could also help tackle the increasing complexity of air traffic management. Complexity destined to increase, for example, with the integration of unmanned aircraft into the air space. Pilots will have to deal with increasing amounts of information and new tasks to accomplish. This opens the way to achieve a different balance in the human-machine interaction. The HARVIS Project aims to frame HMI in terms of partnership, with machines able to better understand humans, and people to engage collaboratively with them. In the cockpit, this partnership will lead to pilots using a set of new technologies, capable of self-learning, anticipating needs and adapting to pilots’ mental states.
Single Pilot operations
Among the challenges that future aviation will need to meet, there is the transition to a single pilot operated flight. SAFELAND aims at creating a valuable solution to support flight and landing of aircrafts operated by a single pilot, following partial or total incapacitation. The project will focus on the ground side. Therefore, it will investigate the interaction of the air traffic controller, operating through a remote cockpit position to manage the flight, with onboard automation and/or a ground based pilot.
Previous research paved the way to projects such as SAFELAND. For example, the ALICIA project focused on developing and testing solutions able to enhance operational capacities. The usability of the new solutions ensured they did not impact negatively on pilots’ workload, situation awareness and workflow. Similarly, the ACROSS project explored and developed applications able to reduce workload during normal operations. It also aimed to support reduced crew operations, either because one pilot has temporarily left the cockpit, or is incapacitated. Finally, it provided technologies able to provide safe recovery from total crew incapacitation situations.