In terms of “Level 5 autonomy”—that is, autonomy anywhere any time—we are still some years away, and this is because of both technical and regulatory challenges.
If we want self-driving cars to be viable global technology, this reliance on detailed prior maps is a problem. Today’s autonomous vehicles are not able to drive in rural environments where we do not have maps—in other words, on the millions of miles of roads that are unpaved, unlit, or unreliably marked. At the MIT CSAIL, we began developing MapLite as a first step for enabling self-driving cars to navigate on roads that they have never been on before using only GPS and sensors. Our system combines GPS data—like the kind you would find on Google Maps—with data taken from LIDAR sensors. Together, these two elements allow us to autonomously drive a car on multiple unpaved country roads and reliably detect the road more than 100 feet (30 meters) in advance. Other researchers have been working on different map-less approaches with varying degrees of success. Methods that use perception sensors like LIDAR often have to rely heavily on road markings or make broad generalizations about the geometry of road curbs. Meanwhile, vision-based approaches can perform well in ideal conditions, but have issues when there is adverse weather or bad lighting. In terms of “Level 5 autonomy”—that is, autonomy anywhere any time—we are still some years away, and this is because of both technical and regulatory challenges.