Digital technologies are fundamental enablers to support an increasing set of ATM operational processes and supporting systems. This digitalisation process is expected to unlock the performance expectations envisaged in the SESAR Concept of Operations (CONOPS), thus creating the Digital European Sky, advocated by the whole European aviation industry and depicted in European ATM Master Plan, the Airspace Architecture Study and the Wise Person Group recommendations.
The process of digitalisation is however not new in ATM and significant effort has been invested in the last 10 years in modernising the tools used by Air Navigation Service Providers (ANSPs), the Network Manager (NM), Airport Operators (AOs) and Airspace users (AUs) to automate processes and information exchanges among each other.
Digital solutions have been created to transpose in a digital format the aeronautical information to be exchanged at network level (e.g. the EAD), thus allowing higher accessibility and the application of uniform quality standards to the processes of creation and manipulation of data. However, this just constitutes the first “digitisation” step along the complete digital transformation journey affecting ATM.
Digitalisation, in fact, is much more than exchanging and storing data in digital format. An immense number of new applications are enabled by the availability of these digital data to users, in particular providing additional capabilities for prediction (4D traffic demand, traffic complexity, etc.) based on the observation and processing of historical data and the extraction of meaningful knowledge on the complex interactions behind the ATM system dynamics.
The key digital techniques that make possible generating new forms of intelligence:
- Big data: this family of technologies include all the tools and techniques used in a context where stringent requirements for data management are necessary. These requirements are defined by the 5 Vs of Big Data: Volume, Variety, Velocity, Veracity and Value. The EUROCONTROL’s MUAC Sector Opening Table architect is a clear example of how this digital technology could improve ATM efficiency post-analysing a huge volume and variety of capacity planning process data. Big Data has become the corner stone of the new Network Manager architecture to be deployed between 2020-2030.
- Data science and analytics: all the techniques aimed at the generation of valuable information out of the raw data. In the ATM sector, these analyses focus on the elaboration of critical KPIs that provide aggregated information from raw data. It is important for the data to be prepared following strict standards to enable and facilitate the analytics tasks. Pre-processing the data to unify formats and perform quality checks is usually required prior to the analysis. The EASA Data4Safety programme is currently evaluating the possibility of using advanced analytics to enhance safety levels, analysing a wide set of data as available to different actors involved in aviation safety.
- Artificial intelligence and Machine Learning: computer programs that exhibit human-like intelligence such as logical reasoning, problem solving and learning. The AI focus has moved from supporting simple repetitive tasks to learning and aping human behaviours and tasks. In the ATM sector, initial examples of AI application already exists, such as predictive systems for airspace design, or automatic speech recognition. The number of applications however is likely to grow exponentially as the techniques become more mature and operators start to reap the benefits.
- Cloud computing enable the locations of use, processing, and storage of data to be separated or loosely coupled, thus allowing for effective and consistent access to the same information at multiple locations (or by multiple entities) in a synchronous or asynchronous manner. This also allows to increase the efficiency of applications, their upgrades, operations, and to reduce duplication of development and data storage. The connectivity and sharing of computational resources provide scalable and virtually unlimited capacity for a particular application.
- Customer Relationship Management (CRM): is a technology for managing the company relationships with customers, storing all historical data referring to contact information, service issues, sales records, etc in the same location. Such system increases data accessibility, helping in the provision of a more flexible and efficient service and could facilitate stakeholder interactions and incentive schemes applications in ATM;
- Swarm intelligence: a swarm intelligence system consists of multiple users (e.g. aircraft), who interact locally with one another and with the surrounding local environment. No centralised control of the users exists but, thanks to the continuous interactions, a sort of collective intelligent behaviour emerges.
Real-time information exchanges stakeholders will be key in fostering common situational awareness and collaborative decision making among actors. Different data will be classified according to their accessibility and safety-centrality and a Public Key Infrastructure will allow secure identity and access management of users and providers of information at regional level, thus guaranteeing high security and interoperability at the same time.
Blockchain is seen as a key technology in terms of cybersecurity, being one of the systems hardest to hack. It basically consists of a transactions database that is shared and synchronized on a distributed peer-to-peer network of multiple computers without a centralized control. Each user owns an identical copy of the record, which is automatically updated anytime an information is added. Each participant can see the data and verify or reject it using ad-hoc consensus algorithms. Once validated, the approved data is entered into the registry as a collection of “blocks” and stored in a chronological “chain” that cannot be manipulated. Blockachain has been proposed as a promising technology for implementing a secure PKI to address ADS-B known vulnerabilities.
These technologies feed each other, cybersecurity can be enhanced by AI (e.g autolocking based on behaviour patterns or sensors, such as mouse tracking and biometric sensors) or by machine learning (e.g. learn from previous situations to detect or prevent new ones). This feeding causes a multiplying effect that boost the capabilities of each of them. Cloud enables big data, which feeds machine learning, which in turn enable artificial intelligence and automation.
The new applications enabled by digital technologies in turn can evolve to become formal digital services offered to different users on the ATM market, automating their legacy manual processes or empowering them with new capabilities.
One success case for digitalisation in European ATM is the European Aeronautical information system Database (EAD), since it was motivated by the digitalisation of legacy aeronautical data, and its consultation through a single platform. This brings several advantages since the public availability of the digitised aeronautical information allows better coordination between the multiple stakeholders and an enhanced process efficiency during flight preparation. EAD is currently consulted not only by aviation stakeholders, but also by systems that require EAD data (e.g. weather or AIP). EAD is considered a clear digitalisation success case which has demonstrated users saving more than €60 million since its introduction.
The Network Manager (EUROCONTROL) is currently upgrading its civil ATM architecture, which has these digital technologies core functionalities built-in, especially big data, cloud, predictive algorithms and machine learning.
According to the Airspace Architecture Study, there are several challenges still to overcome. There is limited use of data communications and congested use of spectrum, non-optimal organisation of airspace, limited information sharing and interoperability, limited flexibility of resources use, low automation, to name but a few. The aviation market is evolving fast and so are its requirements towards the ATM system. Traffic growth is already posing important challenges to the system in terms of capacity and the optimisation of resource utilisation will become more critical than ever in the next years. This demands a paradigm change in ATM to ensure that all stakeholders evolve at a faster and synchronised pace then it happened in the last decades; digital technologies are a key lever to face these challenges and convert them into an opportunity to increase service levels and foster business growth.
The expected implementation and integration of digital technologies into the aviation roadmap could be seen as part of the whole digitalisation process in the aviation sector. However, the full digital transformation will be achieved only when these new capabilities permits to re-design the very foundations of the whole operational concept. Virtualisation of service provision for example is foreseen to allow new service provision models and actors to enter into the market, which will imply a complete change on the current business model and this is only the impact of a small part of the picture, let’s see what more the future has to bring to the aviation sector.
ALG is supporting EUROCONTROL, the SESAR Joint Undertaking and other EU agencies in defining what will be the impacts of digitalisation in the future military ATM, considering not only the opportunities and benefits, but also the costs, risks and obstacles it will face. One of the key aspects to consider is the cultural transformation of the involved organisations, since ensuring their commitment to the change from the top to the bottom of the organigram, is an essential condition to implement the change. Our Consultants combine a long experience within the aviation business in all its different components, with the most advanced digital proficiency and mastering the tools to plan and manage the change, thus providing a trusted partner to accompany your Company along this digital journey.