Google Maps 101: How AI helps predict traffic and determine routes

Annotation 2020-09-06 200735

Every day, over 1 billion kilometers are driven with Google Maps in more than 220 countries and territories around the world.

When people navigate with Google Maps, aggregate location data can be used to understand traffic conditions on roads all over the world. But while this information helps you find current traffic estimates —whether or not a traffic jam will affect your drive right now—it doesn’t account for what traffic will look like 10, 20, or even 50 minutes into your journey. This is where technology really comes into play.

To predict what traffic will look like in the near future, Google Maps analyzes historical traffic patterns for roads over time. For example, one pattern may show that the 280 freeway in Northern California typically has vehicles traveling at a speed of 65mph between 6-7am, but only at 15-20mph in the late afternoon. We then combine this database of historical traffic patterns with live traffic conditions, using machine learning to generate predictions based on both sets of data.