The Eyes & Ears of the Airport: The Importance of A-CDM & Data Sharing

August 1, 2016 Simon Critchley

Passenger looking at flight information display

Delays.

Unquestionably one of the most frustrating and expensive parts of civil aviation. And they don’t come cheap either.

A study by Airlines for America calculated the cost of flight delays to be in the region of $9bn. In Europe a similar study concluded that delays cost as much as €11bn every year. Amazingly, these staggering amounts don’t even take into account the cost to passengers for missed connections, alternative travel and accommodation costs, or the overall impact to the Passenger Experience which we all strive to improve upon.

The air transport process is a complex system with many stakeholders and moving parts and,as a result, delays can be caused by any number of factors.

Although many are unavoidable, the industry is proactively developing new initiatives that will help stakeholders manage and minimize the impact of delays on the rest of the network. Airport Collaborative Decision Making (A-CDM) is being implemented by both Eurocontrol and the FAA as one way of improving communication across the airport and air traffic networks.

The principal of A-CDM is to share information across the various stakeholders within the turnaround process. This up-to-date single source of information is used to generate accurate operational data for the Network Manager Operations Centre (NMOC) in order to efficiently manage airspace requirements.
On the tarmac, improved access to real-time information leads to better resource utilisation for ground handlers and airport operators. Meanwhile, airlines benefit from reduced taxi times and improved on-time performance, which are all key enablers for increasing Airport capacity.

The data that A-CDM generates allows airport operators to benchmark performance and identify improvement areas.

In an environment where capacity constraints are not an uncommon scenario, continuous improvement may be the key to delaying capital investment for a number of years. So with that in mind, I think it’s worth exploring where A-CDM ‘phase 2’ might be able to offer further efficiencies.

Thinking of the practical challenges of delivering A-CDM, accuracy of data is crucial; every minute matters and has a cumulative impact. The key protagonists need to be able to communicate status in real time – or as close to real time as possible.

However, in some situations, that simply isn’t possible.

For example, due to the aforementioned capacity challenges, remote stands arincreasingly used. These stands clearly don’t have the same connectivity to the communication networks that stands at the terminal have. So what happens if there is an unforeseen issue with the turnaround which will delay the flight?

The aircraft isn’t going anywhere, but the despatcher doesn’t have a method of inputting this information into the Airport Operations Database (AODB) in real time. This means that resources are needlessly being allocated that could be more efficiently redeployed where needed, not only at the departing Airport, but down line Airport. Plus, Air Traffic slots remain valid when another flight could benefit.

If the AODB is the brains of the airport, then the data input is the eyes and ears. The success of AODB, and therefore A-CDM, in this increasingly pressurised environment, depends on the quality, validity and timing of the supplied data. In my view, the next generation of A-CDM needs to empower those who hold information to be able to share it, regardless of their location on the airfield. 

FREE WHITEPAPER: Collaborative Decision-Making Across the Airport and Air Traffic Process

About

Simon manages the roadmap for the Chroma Airport Suite

More Content by Simon Critchley
Previous Article
#Innovidual Julie Rosen
#Innovidual Julie Rosen

Julie is a chief data scientist working in national security and healthcare. She leads inference network mo...

Next Article
#Innovidual Ananthakrishna Sarma
#Innovidual Ananthakrishna Sarma

Ananthakrishna is a senior scientist working in numerical weather prediction.