Not so long ago, a daring fellow named Orville Wright took off from a hazy field in North Carolina with his „homebuilt” airplane. He flew an impressive distance of 39 meters, then landed. That day, the Wright Flyer made four take-offs: the Wright brothers intended to take full advantage of the good weather on their day off.
108 years later, the distances flown in public air transport grew a bit longer, but the overall target of getting the most out of the possibilities hasn’t changed. In the last decades the engineering people of the industry unquestionably did a good job: the equipment is capable of running nearly 24/7. We have got instruments that can land an airplane without any intervention of the flight crew, airport opening hours are driven by the traffic much more than by the weather, moreover, the reliability of ground and in-flight systems is increasing as quickly as their maintenance period does.
There are only two factors of the equation that have remained – and will always remain – constant, and these become the ultimate limits of air transportation capacity. These are the physical space available and the loadability of the human mind.
Space, the first constraint, cannot be outflanked, since there are only two states of a given runway, airport gate or piece of airspace in a given moment: occupied or free. However, along with the evolution of information technology, computers are continuously extending the capacity of the human brain, at least on the level of data storage and organization. In the pre-computerized era, decision making required the talent of complementing the data available with good estimations of the missing information, the aim of IT solutions is to make all relevant information available to get rid of the need for this talent.
From the late 70’s computational data management started to gain growing influence in different fields of airline and airport management. This resulted in discrete, standalone systems that were – if at all – loosely interconnected. The responsible people of the different fields of operation could not complain anymore regarding the lack of data primarily needed for decision making. But regardless of the IT efforts, the delay statistics remained proportional to nothing else but the level of traffic at the best run and equipped airports just as well as at the others without the freshest IT infrastructure.
Investigating the roots of the problem FAA came to an interesting finding. It turned out that if the view of decision makers of specific fields was broadened to let them have a glimpse of the situation of the neighboring fields of operation, they could take this extra information into account, which let them make better decisions from the overall point of view. For an apron manager for example, it might be a good idea to get rid of an aircraft parking at a specific gate ASAP, but thinking along the only constraint of cleaning the apron quickly might cause bigger trouble on the taxiways, short of the runways or in the airspace of the terminal area. The investigations clearly pointed out that on the airport side, collaborative decision making is the only way out of the deepening pit of terminal delays.
This required the interconnection of the formerly discrete IT systems, that could be quite easily implemented by IP-based networks and platform-independent design. The challenging part was – and is – the implementation of the new philosophy called A-CDM, the Airport Collaborative Decision Making.
A-CDM votes for collateral information sharing. It appends the requirement of continuous provision of actual data to the responsibility of proper work on a specific field of operation at the airport. Tell the others about your situation to let them take it into account, this will contribute to their decisions fitting your needs better too. On the other hand, be aware of their situation, and make your decisions with regards of them. The result is a smoother, more effective operation, in other words: less delays or a measurable growth in capacity.
To be honest, A-CDM itself is not a new invention. The everyday life of an airport was never imaginable without some information sharing – decision makers of different fields were always trying to complement the puzzle of their situation awareness by talking to other services over the phone since the very beginning. The A-CDM concept is mostly a systematic summary of how it should be done most effectively, taking full advantage of today’s technology of information sharing available. Therefore the visible part of A-CDM is usually another situation display visible from all workstations of a given operations office, with an input console for manual inputs, and a lot of under-the-hood interfaces for automatic data provision.
One of the main advantages of the A-CDM philosophy is that its view extends beyond flight numbers. Instead, equipment is usually identified by tail numbers, setting up a connection between arriving and departing flights, which makes a lot of sense, since delays in the arriving flight will surely cascade onto the departing member of the flight pair. Besides, the interconnection of standalone systems raises trend analysis to the next level: airport-specific nature of traffic, such as variable taxi times can be identified, averaged and taken into account.
Okay then, we have A-CDM up and running, many airports in the US and a growing number in the EU are hooked up, and we can watch airport capacities extending – up to a certain point. Needless to say that A-CDM, just like any other systems invented and implemented by humans, has certain limitations.
First of all, while A-CDM is based on real-time exchange of airside data, a significant portion of delays originate on the land side. Extensive queues at passenger security checkpoints, traffic jam on the airport road, a passenger not showing up at the boarding while his luggage is already loaded, etc. can quickly lead to delays that are unpredictable using the conventional methods. On the top of that, the amount of information that is shared in an A-CDM system became so huge that, without any aid, it is a real challenge to point out the signs of a closing constellation of facts that will lead to a delay with a high probability.
The identification of the deficiencies built in A-CDM called the TITAN project alive. TITAN is an abbreviation for Turnaround Integration in Trajectory And Network. The fully SESAR compatible project, partially funded by the Seventh Framework Programme of the EU, focuses on the terminal turnaround procedure, the main source of delays in public air transport, and aims to prove the feasibility of an IT system layered over Airport CDM that helps the exploration and assessment of possible delays in an intelligent, proactive way.
Among the project deliverables there is a concept of operations described as a service-oriented solution, which is going to be validated by the project participants using state-of-the-art gaming techniques and fast-time simulation, and will lead to a demonstrator tool capable of showing the feasibility of the concept, and to act as a domain for further investigations that, one day will lead to a marketable production system. For the best judgment, a cost-benefit analysis is also to be delivered.
The service oriented approach (SOA) is a vital property of TITAN. This will allow any third party provider (for example queue sensors of the security checkpoint or road traffic information providers) to feed the TIS (TITAN Information Service) module seamlessly with data originating outside of A-CDM. Tailorable automated features are planned to be implemented to provide early warnings for different fields of operation. These warnings are subject to classification according to their majority from the point of view of the given field, and their influence on the on-time operation.
Since the EUROCONTROL whitepaper about Airport CDM does not state that the architecture of a compliant A-CDM system has to be service-oriented, TITAN is intended to wrap the CDM system of an airport up to a broader, SOA-compatible service called TIS (TITAN Information Service). The following diagram shows the preliminary concept of how TITAN gathers information from various sources, including the pre-digested data of A-CDM.
The following table illustrates how CDM related capabilities evolve towards the scenario with TITAN deployed.
Although the project will finish next year by proving or confuting the potential in the idea, one thing can be predicted right now: since there are no degrees of freedom left for sustaining the capacity required by the constant growth of traffic around the large hubs of the world other than somehow making turnarounds more predictable, the result cannot really be anything less than promising.
To read more, visit the TITAN website.