Ford has announced that it will be using Google’s Prediction API for an ongoing research project that seeks to improve performance for plug-in hybrid vehicles.
The automaker already has two years worth of data it’s hoping to convert into real-time driving predictions. Information like where a vehicle travels, and what time of day, may someday be used to make a car more energy efficient by knowing when best to charge, how to optimize the drivetrain, and the quickest route to take.
Ford’s example of this technology might work is a bit futurist, but follows that a driver could tell the car that they were going to work in the morning. Knowing how long the journey will take, the car could charge itself just enough for the complete trip, or enough to reach an available charging station. For plug-in hybrid vehicles, the car could switch to all-electric mode if entering proposed “low emission zones” that are already in cities like London, Berlin, and Stockholm.
Ford notes such personal data would be of great concern, and says encrypted information is one of its highest priorities. We recently noted a similar user-data collection program for smart meters, which could potentially be used in tandem with Ford’s technology to ensure drivers are getting the best rates on electricity when charging their vehicles.