By Michael Thomsen For Dailymail.com
Published: 20:27 GMT, 25 February 2020 | Updated: 20:27 GMT, 25 February 2020
Researchers from MIT have developed new self-driving car system capable of navigating in low visibility settings, including in fog and snow.
The system relies on Localizing Ground Penetrating Radar (LGPR), which takes readings the shape and composition of the road directly below and around the car with electromagnetic pulses.
Other self-driving car systems use a combination of Lidar, radar, and cameras to develop a real-time topographical model of where the car is in space.
A team of researchers at MIT have created a new self-driving car system capable of navigating in low-visibility settings, including fog and snow
These systems are generally reliable but have been vulnerable to visual tricks like fake road signs and lane makers, and can become significantly less reliable during bad weather conditions.
The LGPR system aims to improve on these vulnerabilities by focusing on the road itself and not the open space in front of the car.
To work, the LGPR system needs access to GPS data about the roads it’s travelling on, as well as a reference set of LGPR data to compare against the live sensor readings from the car.
To do this the MIT team sent out a car with a human driver to build a reference set of LGPR data, which catalogs small changes in road height, potholes, or other minute irregularities that form a kind of fingerprint-like textural map of the road.
‘If you or I grabbed a shovel and dug it into the ground, all we're going to see is a bunch of dirt,’ MIT’s Teddy Ort told Engadget.
‘But LGPR can quantify the specific elements there and compare that to the map it's already created, so that it knows exactly where it is, without needing cameras or lasers.’
The car uses 'Localizing Ground Penetrating Radar' or LGPR, which takes a detailed reading of the ground directly below the car, not out in front of it
The system combines GPS data with LGPR data about the composition of the