A team of MIT researchers from its Computer Science and Artificial Intelligence Laboratory (CSAIL) have tested MapLite on a Toyota Prius outfitted with a range of LIDAR and IMU sensors.
MapLite is a framework that allows self-driving cars to drive on roads they’ve never been on before without 3-D maps. MapLite combines simple GPS data with a series of sensors that observe the road conditions.
In tandem, these two elements allowed the team to autonomously drive on multiple unpaved country roads in Devens, Massachusetts, and reliably detect the road more than 100 feet in advance. (As part of a collaboration with the Toyota Research Institute, researchers used a Toyota Prius that they outfitted with a range of LIDAR and IMU sensors.)
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 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 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.
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. As a next step, the team hopes to expand the variety of roads that the vehicle can handle. Ultimately they aspire to have their system reach comparable levels of performance and reliability as mapped systems but with a much wider range.
This project was supported, in part, by the National Science Foundation and the Toyota Research Initiative.