Today’s autonomous vehicles require hand-labeled 3-D maps, but MIT CSAIL’s MapLite system enables navigation with just GPS and sensors.
MapLite combines simple GPS data that you’d find on Google Maps with a series of sensors that observe the road conditions.
The team developed a system of models that are “parameterized,” which means that they describe multiple situations that are somewhat similar. For example, one model might be broad enough to determine what to do at intersections, or what to do on a specific type of road.
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.
MapLite differs from other map-less driving approaches that rely more on machine learning by training on data from one set of roads and then being tested on other ones.
News Source: http://news.mit.edu/2018/self-driving-cars-for-country-roads-mit-csail-0507
