Google Maps using DeepMind AI to predict your arrival time

San Francisco, September 4

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).

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 per cent of trips," said Johann Lau, Product Manager, Google Maps.

"This technique is what enables Google Maps to better predict whether or not you'll be affected by a slowdown that may not have even started yet," Lau said in a statement on Thursday.

To predict what traffic will look like in the near future, Google Maps analyzes historical traffic patterns for roads over time. "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," Lau said.

The predictive traffic models are also a key part of how Google Maps determines driving routes. "If we predict that traffic is likely to become heavy in one direction, we'll automatically find you a lower-traffic alternative. We also look at a number of other factors, like road quality," Google said. IANS

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