How does Google Maps estimate traffic conditions?

The color-coded routes on Google Maps—green for clear roads, yellow for slower traffic, and red for congestion—help you pick the quickest route. But how does Google determine the traffic conditions on your route?

Google Maps traffic predictions and suggestions for faster routes rely on two types of data: past travel time information for specific roads at certain times and real-time data from sensors and smartphones that track current vehicle speeds [source: Barth].

Earlier versions of Google Maps relied solely on data from traffic sensors, which were mostly installed by government transportation agencies or private firms specializing in traffic data collection. These sensors, using radar, infrared, or laser radar technology, could detect vehicle size and speed, transmitting the data wirelessly to a server [sources: Machay, Palmer].

The sensor data is used for real-time traffic updates, and once gathered, it becomes part of historical data that aids in predicting future traffic. However, the sensors were mostly limited to highways and major roads since they were generally placed along the most trafficked or problem-prone routes [sources: Machay, Matthews, Palmer].

Starting in 2009, Google began utilizing crowdsourcing to enhance the accuracy of its traffic forecasts. When Android users activate their Google Maps app with GPS turned on, their phones anonymously send data to Google, showing how fast the cars are moving. Google Maps continuously integrates this incoming data from multiple vehicles and uses it to update the traffic layer with colored lines [source: Barth].

As more drivers use the app, traffic predictions become more accurate, as Google Maps can gauge the average speed of vehicles on the same route, avoiding false traffic jam readings, like someone stopping for coffee. If there isn’t enough data to estimate traffic flow for a road section, it will be shown in gray on the traffic map [source: Google Help].

After acquiring Waze in 2013, Google integrated a human element into its traffic analysis. Waze users report incidents like accidents, breakdowns, slowdowns, and even speed traps. These reports are marked as points on Google Maps, with small icons for construction zones, crashed cars, or speed cameras [sources: Palmer, Waze].