A research team from MIT built a self-driving car to operate on rural roads, without the need for high-definition maps. HD maps are one of the big limiting factors for self-driving cars, which need the maps in order to localize themselves on the road with near-exact precision.
Unfortunately, HD maps are super-expensive to build and maintain, so any progress on this front is a big deal.
The MIT project, MapLite, uses a combination of open-street map data and lidar data to navigate through unmapped environments. Instead of trying to build a map as it goes (a technique known as “simultaneous localization and mapping”), the vehicle merely uses lidar to identify flat, drivable surfaces, and then identifies a viable trajectory to reach its next waypoint.
All of this seems pretty straightforward, but what really struck me was a seemingly obvious thing they mention in the PR writeup.
“I imagine that the self-driving cars of the future will always make some use of 3-D maps in urban areas,” says [MIT graduate student Teddy] Ort. “But when called upon to take a trip off the beaten path, these vehicles will need to be as good as humans at driving on unfamiliar roads they have never seen before. We hope our work is a step in that direction.”
I had always kind of assumed that vehicles relying on HD maps would be a stuck within their geofences, but of course that’s not necessarily the case. A vehicle could use HD maps in urban areas, and then a non-HD map system in other areas. And of course there could be segments of the world in which neither approach is viable and thus those areas would be completely off-limits (until the mapping gets done, say).
Totally obvious when I write it down, but not something I had ever quite pieced together on my own.