Google's Prediction API Could Optimize Your Car's Fuel Efficiency

google prediction API for fuel efficiency ford photo

Image: Ford
Learning Machines are Upon Us
One-size-fits-all is rarely optimal, and that goes for cars too. Engineers have to consider many tradeoffs when they tune a car's drivetrain, and settings that work well in one condition usually don't work as well in another... But that might be about to change thanks to work by Ford and Google. Using sophisticated predictive software to analyze your driving habits, they could optimize the vehicle's operation to squeeze the most out of every drop of fuel or kilowatt-hour of electricity. Read on for more details.
google prediction API for fuel efficiency ford photo

Image: Ford
This week, Ford researchers are presenting a conceptual case of how the Google Prediction API could alter the performance of a plug-in hybrid electric vehicle at the 2011 Google I/O developer conference. In this theoretical situation, here's how the technology could work:

  • After a vehicle owner opts in to use the service, an encrypted driver data usage profile is built based on routes and time of travel. In essence, the system learns key information about how the driver is using the vehicle
  • Upon starting the vehicle, Google Prediction will use historical driving behavior to evaluate given the current time of day and location to develop a prediction of the most likely destination and how to optimize driving performance to and from that location
  • An on-board computer might say, “Good morning, are you going to work?” If the driver is in fact going to work, the response would be, “Yes,” and then an optimized powertrain control strategy would be created for the trip. A predicted route of travel could include an area restricted to electric-only driving. Therefore, the plug-in hybrid could program itself to optimize energy usage over the total distance of the route in order to preserve enough battery power to switch to all-electric mode when traveling within the EV-only zone

"Once the destination is confirmed, the vehicle would have instant access to a variety of real-time information so it can optimize its performance, even against factors that the driver may not be aware of, such as an EV-only zone," said McGee. (source)

This type of technology will be especially useful with plug-in hybrids and fully electric vehicles, since optimizing their charging patterns is crucial to convenience and energy efficiency. For example, with a plug-in, if the car knows that this is a short trip with a charging station on the other end, it can do as much of it in electric mode as possible. If it's a longer trip, it can predict which parts of the trip are more efficiently done in electric mode and which portions are better done with the gasoline engine (and depending on what type of trip it is, the gasoline engine might be tuned via software to be more efficiently used).

Real Privacy Concerns Need to be Addressed First...
There's a Big Brother aspect to all this data gathering that will need to be addressed (and it's not just for this, but also for many online companies like Facebook). But if these privacy issues can be worked through, this could help the cars of the future be more convenient and more efficient.

Via Ford
More on Green(er) Cars
All Prius Models Will Be 'Plug-In' Starting in 2014
Nissan NV200 to Become New York City's "Taxi of Tomorrow", Electric Version in 2017
Ford Focus ECOnetic Diesel to Get 67 MPG (But Only Available in Europe)

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