Transit city navigation app seeks to solve bad public transit ETAs with machine learning

This post was originally published on this site

Curated by: Startups

 

Transit, a company that has spent its entire life trying to make it easier to get around cities, is unveiling a new machine-learning powered estimated time of arrival prediction feature to help address one of the most annoying things about taking public transit: not knowing when the next bus is going to arrive.

Montreal-based Transit already offers in-app ETAs for arrivals in the 175 cities where it operates around the world, but the information it provides is based on either real-time data provided directly from a city itself, or crowd-sourced information provided directly by its users. The reality is that neither of these is a necessarily reliable or consistent way to offer truly accurate ETAs.

Of course, predicting when something as fickle as a city bus on city roads filled with human-driven cars will arrive is no easy task. And as Transit Communications Lead Stephen Miller explained on a call, the company also takes into account when determining what constitutes ‘accuracy’ that you’re naturally going to have a much wider margin of error when a bus is 20 minutes away vs. when it’s only a minute or two out.

That said, in Montreal where the new machine learning-generated ETA

contactedorg

%d bloggers like this: