Google Maps Collaborated with DeepMind AI to Improve Eta Times
Daniel Johnson — September 6, 2020 — Tech
Google has partnered with DeepMind AI in order to improve the accuracy of travel times on the Google Maps platform. The partnership was able to improve travel time accuracy up to 50% in a number of different major cities including Berlin, Jakarta, São Paulo, Sydney, Tokyo, and Washington D.C. The new features can also alert users to potential traffic before it occurs.
Previously the platform used data related to previous travel times as well as current traffic patterns, which was shown to be accurate for over 97% of the time. However, integrated DeepMind AI technology allowed the platform to predict future traffic patterns. In order to accomplish this DeepMind created a graphic neural network, which was able to derive insights from data related to the time of year, road conditions, speed limits, as well as current closures and accidents.
Image Credit: Shutterstock
Previously the platform used data related to previous travel times as well as current traffic patterns, which was shown to be accurate for over 97% of the time. However, integrated DeepMind AI technology allowed the platform to predict future traffic patterns. In order to accomplish this DeepMind created a graphic neural network, which was able to derive insights from data related to the time of year, road conditions, speed limits, as well as current closures and accidents.
Image Credit: Shutterstock
Trend Themes
1. Improved Travel Time Accuracy - DeepMind AI technology has significantly improved travel time accuracy on Google Maps, offering disruptive innovation opportunities for transportation and logistics industries.
2. Predictive Traffic Patterns - DeepMind's graphic neural network enables Google Maps to predict future traffic patterns, opening up disruptive innovation opportunities for traffic management and urban planning industries.
3. Real-time Traffic Alerts - Google Maps' collaboration with DeepMind AI allows for real-time traffic alerts, presenting disruptive innovation opportunities for smart city technology and navigation app industries.
Industry Implications
1. Transportation and Logistics - The improved travel time accuracy powered by DeepMind AI offers disruptive innovation opportunities for optimizing transportation routes and enhancing delivery services.
2. Traffic Management - DeepMind's predictive traffic patterns can revolutionize traffic management systems, providing disruptive innovation opportunities for efficient traffic flow and congestion reduction.
3. Smart City Technology - Real-time traffic alerts from Google Maps and DeepMind collaboration present disruptive innovation opportunities for integrating transportation data into smart city infrastructure for improved mobility.
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