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Google Flights Will Now Predict Airline Delays -- Before the Airlines Do (techcrunch.com)

Posted by msmash on from the pushing-the-limits dept.

Google is rolling out a few new features to its Google Flights search engine to help travelers tackle some of the more frustrating aspects of air travel -- delays and the complexities of the cheaper, Basic Economy fares. From a report: With the regard to delays, Google Flights won't just be pulling in information from the airlines directly, however -- it will take advantage of its understanding of historical data and its machine learning algorithms to predict delays that haven't yet been flagged by airlines themselves. Explains Google, the combination of data and A.I. technologies means it can predict some delays in advance of any sort of official confirmation. Google says that it won't actually flag these in the app until it's at least 80 percent confident in the prediction, though.

1 of 59 comments (clear)

  1. Machine Learning can do a lot better by Roger+W+Moore · · Score: 3, Interesting

    Some of the airline reservation services display an "ontime" percentage next to the flight - EG This flight is ontime 75% of the time. You don't need machine learning for something that simple statistical analysis will do.

    You do if you want to provide better information than this. For example, I would be fine taking a flight which is 75% on time and the remaining 25% of the time is only 20 minutes late. I would be less happy if 25% of the time the flight was 2 hours late. Also this statistic ignores patterns in the delays. For example, suppose the flight is on time 90% of the time from Mon-Thu but delayed by 2 hours 85% of the time on Friday? This would be completely consistent with the data provided if you average over the week but clearly, you would never want to take this flight on Friday!

    While you might be able to do a simple analysis on a weekly pattern airline schedules are more complex and if the delay is caused by a complex interaction of the crew, plane and airport schedules it will be a lot harder to pick up manually whereas a machine learning algorithm should easily be able to cope with this level of complexity and spot that on the third tuesday and second wednesday of every month your flight is delayed. In fact, if the airlines do not do this already, this might be a useful tool for them to spot and identify problems so they can fix them.