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Autonomous Vehicle Navigation in Rural Environments without Detailed Prior Maps (MIT)

Self-driving technology for back roads

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Source: MIT CSAIL: Teddy Ort, Liam Paul, Daniela Rus

According to MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers, navigating roads less traveled in self-driving cars is a difficult task mainly because self-driving cars are usually only tested in major cities where countless hours have been spent meticulously labeling the exact 3D positions of lanes, curbs, off-ramps, and stop signs.

Daniela Rus, director of CSAIL said, “The cars use these maps to know where they are and what to do in the presence of new obstacles like pedestrians and other cars. The need for dense 3D maps limits the places where self-driving cars can operate.”

Further, the millions of miles of U.S. roads that are unpaved, unlit, or unreliably marked are often much more complicated to map, and get a lot less traffic, so companies aren’t incentivized to develop 3D maps for them anytime soon meaning that there are huge swaths of America that self-driving cars simply aren’t ready for.

One way around this is to create systems advanced enough to navigate without these maps, therefore Rus and her team at CSAIL have developed MapLite, a framework that allows self-driving cars to drive on roads they’ve never been on before without 3D maps.

Technical Paper link
MIT’s Summary



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