Crowdsourced Data for Traffic Prediction

Google Maps uses data collected from smartphones to predict traffic conditions. When users have the app open or running in the background, their phones send anonymized GPS data to Google's servers, showing their location and speed.

Creating Real-Time Traffic Maps

By comparing this data with information from other drivers on the same road, Google Maps creates a real-time map of traffic conditions. If the average speed of a group of vehicles drops sharply on a highway, the app detects a slowdown or traffic jam and changes the route's color from blue to orange and then red.

Calculating Alternative Routes

To suggest a new route, the algorithm divides the area into small segments and calculates the travel time for each alternative. It considers factors like speed limits, road types, and potential traffic lights. If the time saved on a secondary route is greater than the time lost on the main route, Google Maps recommends changing routes.

Using Historical Data for Predictions

The app also uses historical traffic data to predict how traffic jams might develop in the coming minutes. This allows users to benefit from a large, collaborative map managed by artificial intelligence, improving their navigation experience.