How do Google Maps know traffic routes?

Manu was late for work. Not once did she remember hitting the snooze button on her phone, but she was late. It was 8:40, but her working hours would begin at 9:00. What she needed was a traffic-free route, and she had Google Maps to help her find it. She sighed in relief as she saw that a blue-lined route was available. Without a second thought, she grabbed her bag and bike keys and rushed out the door.

Google maps

Wow! Manu sure was lucky for that blue line! Whether you go to school, college, work, or even a distant market, more than once, you would have taken out your phone and opened Google Maps. It is a web-mapping platform that is utilised by many consumers on a daily basis, and was created by Google. It provides people with well-displayed maps, satellite imagery, location search,  aerial photography, and many more incredible features. But one of its highly underlooked uses is something we often take less than ten seconds to check, and that would be its traffic detection capability. Whatever vehicle you take, be it a car, bus, bike, or auto, etc. Google Maps proves to be a highly efficient assistant in letting you know which route will ensure that you get to your destination on time. In this case, the colour of the lines indicating the roads is what a user pays attention to. Blue line means its ‘go!go!go!’, orange line means ‘slight traffic’, and red line means ‘Do not enter unless you want to be late!’

How does it do it?

So here’s the big question. How exactly can this app on your phone take up the role of a seer and tell you which road is the best choice for your travels? Well, there are many ways it does it, but three methods stand out from the rest. History, real-time information sensors, and machine-learning. 

Firstly, there’s history. They say learning from the past can help you make decisions for the future. This principle is also utilised by Google Maps when detecting traffic within the multiple pathways to your destination. The app analyses and studies traffic patterns from the past, and the average speed vehicles drive on a certain road at different times of day. By studying this historical database of information, Google Maps can make a prediction on what road will hold traffic at a certain timeframe.

Secondly, we have real-time information sensors. This information is brought to your phone from traffic sensors installed by government agencies or private companies that are particularly skilled in traffic data collection. GPS information on speed, direction, and location is all sent to Google Maps, which uses it to predict traffic flow. Radar and infrared technology are used to transfer wireless data to the server. The real-time information also comes from other smartphones with Google Maps when users enable the GPS. 

Thirdly, machine learning is a prominent feature that the app uses to analyse the data provided by the previous two sources of information (history and real-time data). Ever since it acquired DeepMind, the app uses Graph Neural Networks, a machine-learning architecture, to create a complex interconnected structure of road networks and traffic signals. These predictions are affected by many external factors like weather, road blocks, accidents, etc.