My son and I were driving on a road in the Sierra Nevada Mountains a few weeks ago where it was not straight for more than 500 feet. We turned constantly down a steep narrow road with no guard rail that dropped thousands of feet into a steep drainage for over an hour. After we survived, I told him that a driverless car will never be built that can navigate that type of country road.
Well I may be wrong again, if you are willing to believe some of the researchers at good old MIT’s Computer Science and Artificial Intelligence Lab or CSAIL. They have developed a new system called MapLite which is capable of self-driving without the need for 3D-mapped roads, making it a lot better suited to tackling the vast majority of roads in the U.S. and around the world.
In contrast, MapLite uses sensors for all aspects of navigation, relying on GPS data only to obtain a rough estimate of the car’s location. The system first sets both a final destination and what researchers call a “local navigation goal,” which has to be within view of the car. Its perception sensors then generate a path to get to that point, using LIDAR to estimate the location of the road’s edges. MapLite can do this without physical road markings by making basic assumptions about how the road will be relatively more flat than the surrounding areas.
“The reason this kind of ‘map-less’ approach hasn’t really been done before is because it is generally much harder to reach the same accuracy and reliability as with detailed maps,” says CSAIL graduate student Teddy Ort, who was a lead author on a related paper about the system. “A system like this that can navigate just with on-board sensors shows the potential of self-driving cars being able to actually handle roads beyond the small number that tech companies have mapped.”
MapLite still has some limitations. For example, it isn’t yet reliable enough for mountain roads, since it doesn’t account for dramatic changes in elevation. Aha, maybe I wasn’t wrong.
At least they are honest enough to admit it.
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