Ford Plans to Use Google Prediction API to Optimize Energy Efficiency

Posted by at 8:29 pm on May 10, 2011

Ford is planning to use Prediction API to have cars operate more efficiently. Ford researchers are taking the power of cloud computing, analytics and Google’s API set to identify technologies that could make tomorrow’s vehicles smart enough to change how they perform to deliver optimal driveability and fuel efficiency.

Machine Learning Software

Using Google’s Prediction API with more than two years of Ford’s own predictive driver behavior research and analysis; Ford can convert information such as historical driving data – where a driver has traveled and at what time of day for example – into useful real-time predictions, such as where a driver is headed at the time of departure.

Another way to look at this; Ford is applying Google’s and their own software in the same manner as a web site that tells you what TV shows or music you may like based on past behavior.  Ford is just taking this type of software, Machine learning, and applying it to the auto field.

“The Google Prediction API allows us to utilize information that an individual driver creates over time and make that information actionable,” said Ryan McGee, technical expert, Vehicle Controls Architecture and Algorithm Design, Ford Research and Innovation. “Between Google Prediction and our own research, we are discovering ways to make information work for the driver and help deliver optimal vehicle performance.”

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.

Ford  Examples of 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.

Because of the large amount of computing power necessary to make the predictions and optimizations, an off-board system that connects through the cloud is currently necessary.  This is an area where all know that Google shins in.

So Now My Car is Tracking Me

Ford  was very upfront that it will respect user privacy in the way it uses location and vehicle data in its application design. This is an area we hope to speak to Ford and Google soon to get greater detail on soon.  Google, for example, has dune a great job in telling users what an app will do with data when you install an app on an Android phone.  At the same time user must still read those concise messages, and yes even those long terms of services.

What Does the Future Hold

“Anticipating the driver’s destination is just one way that Ford is investigating predicting driver behavior,” said McGee. “This information can ultimately be used to optimize vehicle performance attributes such as fuel efficiency and driveability.”

Helping drivers comply with regulations could be among those needs. For example, the French government is considering creating zones that would mandate vehicles have lower emissions.  Cities such as London, Berlin, and Stockholm already have such zones.

If a vehicle were able to predict exactly when it might be entering such a zone, it could optimize itself in a way to comply with regulations, such as switching the engine to all-electric mode.

In the USA some areas let all electric cars use the HOV lanes, regardless of the number of passengers.  So a plug-in hybrid gas-electric car could know with the power of the cloud to run in electric-only mode in those HOV lanes.

Work is now underway to study the feasibility of incorporating other variables such as driver style and habits into the optimization process so Ford can further optimize vehicle control systems, allowing car and driver to work together to maximize energy efficiency.

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