Using LiDAR sensors, MIT researchers have developed an autonomous vehicle navigation system for rural roads with “no detailed, three-dimensional map for the vehicle to reference,” reports Rob Verger of Popular Science. “The solution for urban mapping really doesn’t scale very well to a huge portion of the country,” explains graduate student Teddy Ort.
MapLite, a system developed by CSAIL researchers, allows autonomous vehicles to drive on roads they’ve never driven before without 3D maps, writes Andrew Hawkins of The Verge. If it becomes commercial, MapLite could ensure “that the safety benefits from autonomous driving [are] extended to residents in rural communities,” suggests Hawkins.
CSAIL researchers have developed a system that uses LIDAR and GPS to allow self-driving cars to navigate rural roads without detailed maps, writes Tracey Lindeman of Motherboard. Autonomous ride-hailing or car-sharing is important in rural communities because “the carless in these areas have few transportation options; many small communities don’t even have public buses,” notes Lindeman.
Eric Mack writes for Forbes about a new system from MIT researchers that uses GPS in conjunction with LIDAR and IMU sensors to power self-driving vehicle navigation. Graduate student Teddy Ort says the system “shows the potential of self-driving cars being able to actually handle roads beyond the small number that tech companies have mapped.”
MapLite, a new system developed by CSAIL, aims to help autonomous vehicles navigate uncharted areas, writes Jesus Diaz for Co.Design. “[I]f autonomous cars can reach the millions of people who live beyond the city and are unable to pilot their own vehicles,” said graduate student Teddy Ort, “they will be uniquely capable of providing mobility to those who have very few alternatives.”
In an essay for The Daily Beast, researchers at the MIT AgeLab explore the extent to which driving is a “secondary” activity when piloting a vehicle, and caution that automation on its own cannot protect drivers from distractions. “While these technologies can nudge us in a safer direction, the decision to practice safer phone habits ultimately lies in the hands of drivers,” they write.
Emily Matchar of Smithsonian details research out of the Media Lab, which seeks to help both autonomous and standard vehicles avoid obstacles in heavy fog conditions. “You’d see the road in front of you as if there was no fog,” says graduate student and lead researcher Guy Satat. “[O]r the car would create warning messages that there’s an object in front of you.”
In a commentary for Nature, Ashley Nunes, Bryan Reimer and Joseph Coughlin of the MIT AgeLab discuss how current legislation does not sufficiently account for the risks associated with operating autonomous vehicles. “Policymakers need to work more closely with academics and manufacturers to design appropriate regulations,” they write. “This is extremely challenging because the research cuts across many disciplines.”
MIT Media Lab researchers have created a system that can detect obstacles through fog that are not visible to the human eye, writes Darren Weaver for CNBC. “The goal is to integrate the technology into self-driving cars so that even in bad weather, the vehicles can avoid obstacles,” explains Warren.
MIT researchers have developed a new imaging system that could allow autonomous vehicles to see through dense fog, writes Andrew Liszewski of Gizmodo. The laser-based system, which used a new processing algorithm, was able “to clearly see objects 21 centimeters further away than human eyes could discern,” Liszewski writes.
Research scientist Bryan Reimer speaks to WBUR about the ramifications for the autonomous vehicle industry in response to the recent fatality caused by a self-driving Uber. “As we look forward…we need to work together in ways through policy, technology development, advocacy, to set a pathway to safety,” Reimer says.
Researchers in CSAIL are developing a steering program for drones that allows them to process uncertainty and avoid hitting objects while flying autonomously. Called Nanomap, the drone uses depth measurements to determine the safest path. “This technique creates an on the fly map that lets the drone handle uncertainty as opposed to being ready in every situation,” writes John Biggs for TechCrunch.
Skydio, an autonomous drone startup founded by a group of MIT alumni, has showcased a new drone that can lock-on, follow and record its subject, writes Lucas Matney of TechCrunch. One possible use for the device is to “launch the drone, lock onto yourself, and ski down a mountain while the R1 tracked you to the bottom while capturing 4K footage,” Matney explains.
CSAIL researchers have developed a new navigation method that allows drones to process less data, have faster reaction times, and dodge obstacles without creating a map of the environment they’re in, writes James Vincent of The Verge. “Because we’re not taking hundreds of measurements and fusing them together, it’s really fast,” said graduate student Peter Florence.
A drone navigation system developed by CSAIL researchers doesn’t rely on intricate maps that show the location of obstacles, but adjusts for uncertainties, reports Martin Finucane of The Boston Globe. The system could be used in “in fields from search-and-rescue and defense to package delivery,” notes Finucane.