MIT’s new system allows a self-driving car to situate itself in snowy conditions.
Car companies have been feverishly working to improve the technologies behind self-driving cars. But so far even the most high-tech vehicles still fail when it comes to safely navigating in rain and snow.
This is because these weather conditions wreak havoc on the most common approaches for sensing, which usually involve either lidar sensors or cameras. In the snow, cameras can no longer recognize lane markings and traffic signs, while the lasers of lidar sensors malfunction when there’s, stuff flying down from the sky.
MIT researchers have recently been wondering whether an entirely different approach might work. Specifically, what if we instead looked under the road?
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed a new system that uses an existing technology called ground-penetrating radar (GPR) to send electromagnetic pulses underground that measure the area’s specific combination of soil, rocks, and roots. Specifically, the CSAIL team used a particular form of GPR instrumentation developed at MIT Lincoln Laboratory called localizing ground-penetrating radar, or LGPR. The mapping process creates a unique fingerprint of sorts that the car can later use to localize itself when it returns to that particular plot of land.
Photo courtesy of the researchers
In tests, the team found that in snowy conditions the navigation system’s average margin of error was on the order of only about an inch compared to clear weather. The researchers were surprised to find that it had a bit more trouble with rainy conditions, but was still only off by an average of 5.5 inches. This is because rain leads to more water soaking into the ground, leading to a larger disparity between the original mapped LGPR reading and the current condition of the soil.
The researchers said the system’s robustness was further validated by the fact that, over a period of six months of testing, they never had to unexpectedly step in to take the wheel.
It demonstrates that this approach is actually a practical way to help self-driving cars navigate poor weather without actually having to be able to ‘see’ in the traditional sense using laser scanners or cameras.
This is the first time that developers of self-driving systems have employed ground-penetrating radar, which has previously been used in fields like construction planning, landmine detection, and even lunar exploration.
While the system represents an important advance, it’s far from road-ready. Future work will need to focus on designing mapping techniques that allow LGPR datasets to be stitched together to be able to deal with multi-lane roads and intersections. In addition, the current hardware is bulky and 6 feet wide, so major design advances need to be made before it’s small and light enough to fit into commercial vehicles.
News Source: MIT
