THE GIST

- Google's fleet of robotic Toyota Priuses has now logged more than 190,000 miles.

- The cars could reduce road accidents, congestion and fuel consumption.

Once a secret project, Google's autonomous vehicles are now out in the open, quite literally, with the company test-driving them on public roads and, on one occasion, even inviting people to ride inside one of the robot cars as it raced around a closed course.

Google's fleet of robotic Toyota Priuses has now logged more than 190,000 miles (about 300,000 kilometers), driving in city traffic, busy highways, and mountainous roads with only occasional human intervention. The project is still far from becoming commercially viable, but Google has set up a demonstration system on its campus, using driverless golf carts, which points to how the technology could change transportation even in the near future.

Stanford University professor Sebastian Thrun, who guides the project, and Google engineer Chris Urmson discussed these and other details in a keynote speech at the IEEE International Conference on Intelligent Robots and Systems in San Francisco last month.

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Thrun and Urmson explained how the car works and showed videos of the road tests, including footage of what the on-board computer "sees" [image below] and how it detects other vehicles, pedestrians, and traffic lights.

Google has released details and videos of the project before, but this is the first time I have seen some of this footage -- and it's impressive. It actually changed my views of the whole project, which I used to consider a bit far-fetched. Now I think this technology could really help to achieve some of the goals Thrun has in sight: Reducing road accidents, congestion, and fuel consumption.

Urmson, who is the tech lead for the project, said that the "heart of our system" is a laser range finder mounted on the roof of the car. The device, a Velodyne 64-beam laser, generates a detailed 3D map of the environment. The car then combines the laser measurements with high-resolution maps of the world, producing different types of data models that allow it to drive itself while avoiding obstacles and respecting traffic laws.