Delay

01 Nov Delay management: calculating late passengers into the system

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A major source of unpredictability in air traffic management is passengers, specifically in the boarding process. Some experts estimate that 75% to 80% of delayed flights are due to passengers boarding late or not at all. The difficulty here is that those passengers are also the customers. It makes sense to consider passenger experience when developing air traffic management concepts to help manage delays.

If passengers need a certain flexibility, the air traffic management system should be able to deliver that.

Waits and delays

Announcements calling for passengers whose flights are closing to proceed to the gate immediately are familiar to anyone who has ever been in an airport. Many of those flights end up delayed because the passenger doesn’t show up and their luggage must be off-boarded. Waiting for missing passengers and off-boarding baggage is probably the most frequent reason for delayed departures.

Meanwhile, air traffic management systems are generally designed around pre-determined flight plans and timetables that air traffic controllers then fit into an overall air traffic plan. Whenever a flight changes because of these delays, the new plan must be added in all over again. This introduces instability and uncertainty into the air traffic management system.

Can’t we just fix the passengers

Imagining ways to reduce delays by stopping passengers from being late is a natural reaction to that uncertainty. Closing gates 15 minutes prior to departure and refusing later passengers, for instance, would allow more time to remove unaccompanied baggage.

However, this idea would also require all passengers to be at the airport 15 minutes earlier, which goes against efforts such as faster check-ins designed to decrease travel time lost waiting at airports.

Examining only the technical aspects is fine when designing for punctuality. But airlines are also concerned with the passenger experience and their preferences. Whether air travellers are willing to accept being at the airport even earlier in exchange for more punctual flights is highly debatable.

Integrating passenger uncertainties

We are currently working on various methods for integrating passenger behaviour data into systems, such as for gate planning in A-CDM, where departure times are continuously updated. Because our expertise covers both airside and landside, we now have the wider operational insights necessary to allow for passenger preferences as well as the effects of their behaviour. This is helping us to develop robust air traffic management systems where delays cause less disruption.

Even though including all the countless variations in passenger behaviour would be impossible, we can no longer afford to ignore them entirely. Through our work on uncertainty, we are now not only much better at determining where uncertainty could be eliminated or reduced, but we are also integrating more uncertainties as legitimate factors into algorithms (in A-CDM, AFOS) where they cannot. If passengers need a certain flexibility, the air traffic management system should be able to deliver that.

About To70. To70 is one of the world’s leading aviation consultancies, founded in the Netherlands with offices in Europe, Australia, Asia, and Latin America. To70 believes that society’s growing demand for transport and mobility can be met in a safe, efficient, environmentally friendly and economically viable manner. To achieve this, policy and business decisions have to be based on objective information. With our diverse team of specialists and generalists to70 provides pragmatic solutions and expert advice, based on high-quality data-driven analyses. For more information, please refer to www.to70.com.

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Maarten Tielrooij
Maarten Tielrooij
Maarten Tielrooij is aviation consultant with a focus on Data Science and Air Traffic Management. With 8 years experience in operational ATM he is familiar with both current operations and concepts under development. He is an experienced user of programming software, modeling and simulation techniques, large databases, and statistical techniques.
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