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The tireless, impossible science of airport delays



Friday morning began with delays at New York's LaGuardia Airport. It's not unusual-New York's airports are famous balky. But this time the cause was nothing prosaic, like a snowstorm. It was manning. Due to the federal government's decommissioning, the airport did not have adequate transport safety management agents and air traffic controllers; things lowered to a stop.

Then it began to spread – Newark, Philadelphia, even though the Atlanta center all started to knock down. And it's scary. Airports are nodes on a global network, and the science that governs how the network behaves means that if a node has a problem, this problem spreads. The international airline exists on some of a knife edge. It doesn't take much to knock it out of optimal flow.

Basically, the delay problem is one of "connected resources"; Flyer land and turn around to perform other flights, and some of the passengers on them also come to other aircraft. If you've ever flown, you know all that, but what it means in practice is that small bugs or delays at an airport are enlarged as they move down the line, multiply and sometimes intensify. "The systems that run these queues are very close to capacity," says Hamsa Balakrishnan, an aviation engineer at MIT, who studies the air transport network. "Both LaGuardia and Newark had wind-related delays today. With full staffing you might have been able to control, but with a drop in staffing, you have delays that then end up spreading to other airports due to connectivity options . "

You can typically expect that the largest airports in the world with most aircraft in and out say or move most people ̵

1; would have the greatest impact on the overall movement across the network. But an airport's "delay propagation multiplier" varies depending on all sorts of things, from how an airport is planned to its overall capacity and even the weather. In a calculation, a minute delay causes an average of 30 seconds of slowdown elsewhere in the network. But some airports are more resilient than others. The time it takes to get from one to the other has an effect. It's so complicated that it kills even the most pristine network models.

Airlines are trying to account for all this by building slump in the schedule. They calculate how long a given flight should take – the "scheduled block time" – and how long the aircraft will use on the ground, "scheduled run time". But then they have a choice. "They deploy buffer time in their schedules and ground operations," says Bo Zou, a transport engineer at the University of Illinois. "They still encounter delays, and a newly created delay for a flight will multiply to the second and third flights. Part of it will be absorbed by the buffer but not all that." Build too small a buffer and the delays multiply more. Build too large a buffer and you don't use your fleet effectively and lose money. "One side is efficiency, the other is robustness," Zou says.

And it constantly changes depending on changing conditions. Some are predictable as winter storms, and some are not as public shutdowns and informal diseases. outs. It is called a "dynamic complex network." It must be constantly adapted.

Because if it doesn't? According to one study, flight delays cost the US economy over $ 30 billion a year. It's not just lost time or flight costs; That's what people on these flights planned to do when they arrived. "A prolonged shutdown, or even slow, would probably affect all kinds of unforeseen things," said Luís Bettancourt, network researcher at the University of Chicago. "The reliability of time-sensitive logistics will break down, and some of these cities' naval character will have to bypass, at least temporarily. A slow down would be most disastrous for big cities, their influence and their economies."

, the government can now get its TSA agents and air traffic controllers back to the station. It will build a bit of resilience back to the airports just in time for a massive snowstorm due to hit the Midwest next week. But the overall health of the airline will still be uncertain.

Therefore, researchers are working to gather more and more data on how it all works (or not). If people cannot plan all of these flights in an efficient and robust manner, an algorithm might. Balakrishnan has even cofounded a startup trying to make it happen. "There are so many moving pieces that it is difficult for a person to come up with all sorts of solutions," she says. "But that's something we know how to make computers do." If you enjoy flying on an unmanageable and incomprehensible network now, wait until it is run by an unmanageable, incomprehensible robot.


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