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Artificial intelligence improving bus departure estimates

Artificial intelligence improving bus departure estimates

Accuracy and innovation to provide more predictable service

Customers will be able to better plan their journey on TransLink’s bus network, with a new machine learning algorithm improving the accuracy of departure estimates. The system-wide implementation follows a successful pilot program which saw 13 bus routes utilize this technology.

“We’re proud to have developed the new algorithm in-house, with collaboration from technology companies Microsoft and T4G,” says TransLink CEO Kevin Desmond. “This method is going to result in better information for customers, who can make more informed decisions throughout their journey. During the pilot phase the difference between predicted and actual bus departure times improved by 74%.”

Combining live bus location data with the machine learning algorithm, this innovative methodology improves existing estimates by considering major factors that affect bus departures.  These include weather conditions and journey estimates at different times of day and night.  To ensure accurate predictions for the entire transportation network, the algorithm involves over 16,000 machine learning models.

The new algorithm has been incorporated into TransLink’s Next Bus website and SMS tool (text the bus stop number and bus route number to 33333 for next departure estimates). Third-party applications that are already using our bus departure estimates, such as the Transit App and Google Maps, will also use the new estimation method.


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