Ford aims to use Google's Prediction API to bolster analytics

Ford said that it will use Google’s new Prediction API, which uses cloud computing, storage and external data for analytics, and combine it with its own research and development on driver predictive behavior.
Ford on Tuesday said that it will use Google’s new Prediction API, which uses cloud computing, storage and external data for analytics, and combine it with its own research and development on driver predictive behavior. The goal: Create cars that can optimize fuel economy and efficiency based on driver habits.

The announcement, made at Google’s I/O conference in San Francisco, is an interesting tag-team. Ford has strong auto technology partnerships with Ford and Nuance to name a few. The tie-up with Google highlights how algorithms that connect public and private data will be needed to enhance the driver experience.

Ford presented a case study on how Google’s Prediction API could be used to enhance the performance of a plug-in hybrid electric vehicle. For instance, an electric vehicle driver could have access to a route that would take into account battery usage, optimize power and work out details to stay in all-electric mode in a city.

Among the key points:

* Ford will add Google’s Prediction API to its research and analysis.
* Google’s API can convert historical driving data into real time predictions.
* The outcome from the algorithm combination will be used to predict routes.

Today, the combination of Google and Ford data is largely conceptual—as are the outcomes. Ford envisions something like this happening:

* Vehicle owner opts into the predictive service and driver data is collected and encrypted. The system learns over time and all data is encrypted for privacy and security.
* When the car is started Google Prediction will use history to optimize routes and performance based on location and time of day.
* The car via voice recognition would confirm its predictions based on input from the driver.

The next step for Ford is to use conduct feasibility studies for using Google’s Prediction API. In the big picture, Ford’s Google I/O announcement signals that in-car technology is moving beyond infotainment to more complicated tasks.

Johannes Kristinsson, system architect, Vehicle Controls Architecture and Algorithm Design, at Ford said:

“Ford already offers cloud-based services through Ford SYNC, but those services thus far have been used for infotainment, navigation and real-time traffic purposes to empower the driver. This technology has the potential to empower our vehicles to anticipate the driver’s needs.”