Ford to make cars smarter with Google Prediction

Running the Google Prediction API in a cloud could help hybrids adapt to drivers, Ford said

Ford Motor Co. wants to use the Google Prediction API to predict driver behavior and use that input to make cars perform better.

The company's goal is to use cloud-based storage and computing to collect and process information about how drivers use their vehicles. Accessing those resources over a wireless network, a vehicle could automatically change how it performs, according to Ford.

The Google Prediction API, released last year by Google Labs, is designed for giving an application information about past user actions so it can better predict future behavior. The API (application programming interface) uses pattern-matching and machine learning and is designed to be simple to use, according to Google. On its information page about the API, Google said it could help a website recommend products to regular visitors, detect what a user would consider spam e-mail, and predict how much a user would be likely to spend on a given day.

Ford is extending this technology from the Web to the road. On Tuesday at the Google I/O conference in San Francisco, Ford will present one conceptual case for the use of this technology in a plug-in hybrid electric vehicle. If the owner started the car on a weekday morning, the car could use its recent driving history to predict that this will be a trip to the office. An automated voice would ask the driver to confirm this, and if the driver said, "Yes," the car could prepare to handle the route to the office intelligently.

In the example presented at Google I/O, the hybrid could favor its gasoline engine on the first part of the trip to set aside battery power for an electric-only section of road that it knew was coming up later on the route. But knowledge about location, routes and driver behavior could also help a car in other ways, according to Ryan McGee, a technical expert at Ford. For example, the vehicle could shift to full electric power while close to the driver's home, in order to reduce noise and pollution. A car with access to the predictive tool could also use different techniques to save energy for later, depending on an individual's style of driving, McGee said.

A large amount of information about a driver's preferences and driving behavior could be stored in a profile in the cloud and then accessed when that driver got in the car, according to Ford. The company emphasized that drivers would have to opt in to such a service so none of this data would be collected unless they agreed to it. The profile would also be encrypted to protect the information from unauthorized use.

Ford doesn't expect smarter cars to start changing drivers' behavior by throttling back their acceleration or limiting their speed to save energy, McGee said. Rather, the idea is to help the car program itself to adapt to each driver's style.

The company won't discuss any plans for car features or services based on this technology, and due to logistical issues, its software demonstration at Google I/O doesn't even use an actual vehicle. But McGee said products based on this type of intelligence might reach the market some time after 2015.

Stephen Lawson covers mobile, storage and networking technologies for The IDG News Service. Follow Stephen on Twitter at @sdlawsonmedia. Stephen's e-mail address is stephen_lawson@idg.com

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