How Google Maps is using AI and Machine Learning to understand post-COVID traffic

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​AI meets ML

As people traverse over 1 billion kms with help from Google Maps in more than 220 countries, the company is using artificial intelligence (AI) machine learning (ML) models to predict whether the traffic along your route is heavy or light, an estimated travel time, and an estimated time of arrival (ETA), reports IANS.

AP

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​Improving traffic accuracy

Google has partnered with DeepMind, an Alphabet AI research lab, to improve the accuracy of its traffic prediction capabilities.”Our ETA predictions already have a very high accuracy bar, in fact, we see that our predictions have been consistently accurate for over 97 percent of trips,” said Johann Lau, Product Manager, Google Maps.

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​Learning from data

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.

Getty Images

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​Varied sources

Two other sources of information are important to making sure Google recommends the best routes — authoritative data from local governments and real-time feedback from users. Authoritative data lets Google Maps know about speed limits, tolls, or if certain roads are restricted due to things like construction or Covid-19. “And incident reports from drivers let Google Maps quickly show if a road or lane is closed, if there’s construction nearby, or if there’s a disabled vehicle or an object on the road,” Google added.

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​Looking at the big picture

So how exactly does this all work in real life? Say you’re heading to a doctor’s appointment across town, driving down the road you typically take to get there. When you leave the house, traffic is flowing freely, with zero indication of any disruptions along the way. With Google Maps’ traffic predictions combined with live traffic conditions, we let you know that if you continue down your current route, there’s a good chance you’ll get stuck in unexpected gridlock traffic about 30 minutes into your ride—which would mean missing your appointment. As a result, Google Maps automatically reroutes you using its knowledge about nearby road conditions and incidents—helping you avoid the jam altogether and get to your appointment on time.

PTI