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2016 Tech of the Year | Autoblog Minute

Deliberation on the winners of Autoblog's Tech of the Year Award is under way. Nominees for best car in 2016 are: the Tesla Model S, the Chevy Volt and the BMW 7 series. Nominees for best tech in 2016 are: Apple CarPlay, Android Auto, VW's MiB II with AppConnect, Ford Sync 3, Audi Virtual Cockpit, the Smart Cross Connect App, and Volvo Sensus. Autoblog's Chris McGraw reports on this edition of Autoblog Minute. Audi BMW Chevrolet Ford smart Tesla Volvo Technology of the Year Autoblog Minute Videos Original Video volt android auto ford sync 3

Ford reveals EcoBoost-powered Riley prototype for Daytona 24

It's not the first time Ford has participated in the Daytona Prototype class as an engine supplier, but in revealing this new EcoBoost V6-powered Riley Technologies prototype for the new United SportsCar Championship, Ford is making a statement: "We want to show Ford EcoBoost's capabilities as an engine that provides both performance and fuel economy, on and off the track," says Jamie Allison, director of Ford Racing.
In addition to supplying the 3.5-liter twin-turbocharged V6, Ford had its production designer Garen Nicoghosian give the racecar brand-inspired design cues with support from Ford Racing chief aerodynamicist Bernie Marcus.
The car is scheduled to compete at next year's Rolex 24 at Daytona on January 25-26, but before that, Michael Shank Racing is working with Ford at another goal. Driving his Ford Thunderbird, NASCAR champion Bill Elliott set the track's top speed record at 210.364 miles per hour during a qualifying run for the Daytona 500 - way back in 1987 -- and Ford thinks it's about time for that record to fall. What better time the introduction of this new Ford-powered Daytona Prototype? Michael Shank Racing plans to use the twin-turbo V6-powered racer to beat Elliott's record, and it expects to begin prepping for the top-speed run on October 9. Scroll down for the full press release below on Ford's latest race effort.

Ford partnering with MIT, Stanford on autonomous vehicle research

Ask any car engineer what's the biggest variable in achieving fuel economy targets, and he'll tell you "the driver." If one human can't understand human driving behavior enough to be certain about an innocuous number like miles per gallon, how is an autonomous car supposed to figure out what hundreds of other drivers are going to do in the course of a day? Ford has enlisted the help of Stanford and the Massachusetts Institute of Technology to find out.
Starting with the automated Fusion Hybrid introduced in December, MIT will be developing algorithms that driverless cars can use to "predict actions of other vehicles and pedestrians" and objects within the three-dimensional map provided by its four LIDAR sensors.
The Stanford team will research how to extend the 'vision' of that LIDAR array beyond obstructions while driving, analogous to the way a driver uses the entire width of a lane to see what's ahead of a larger vehicle in front. Ford says it wants to "provide the vehicle with common sense" as part of its Blueprint for Mobility, preparing for an autonomous world from 2025 and beyond.