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.”
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.
Graduate student Achuta Kadambi speaks with the BBC’s Gareth Mitchell about the new depth sensors he and his colleagues developed that could eventually be used in self-driving cars. “This new approach is able to obtain very high-quality positioning of objects that surround a robot,” Kadambi explains.
CSAIL researchers have discovered that some traffic jams are caused by tailgating, writes Thomas Tamblyn for HuffPost. Maintaining an equal distance in front of and behind a vehicle, “could have a dramatic effect in reducing travel time and fuel consumption without having to build more roads or make other changes to infrastructure,” explains Prof. Berthold Horn.
Forbes reporter Laurie Winkless writes that MIT researchers have found that if drivers maintained fixed distances between the cars in front of and behind them they would be able to reduce traffic jams. “We humans tend to view the world in terms of what’s ahead of us, so it might seem counter-intuitive to look backwards,” explains Prof. Berthold Horn.
CNN reporter Matt McFarland writes that CSAIL researchers have proposed that outfitting cars with cruise control systems that maintain equal distances between cars could help alleviate phantom traffic jams. The researchers’ simulations showed, “keeping the same distance between the vehicle in front and the vehicle trailing a car prevents traffic jams.”
CSAIL researchers have found that if drivers could maintain an equal distance between cars they would be able to reduce the number of traffic jams, reports Matt Burgess for Wired. The researchers found that, “by adding sensors to the back of cars that take into account the speed of following vehicles, it will be possible to better regulate traffic.”
Researchers in the MIT Senseable City Lab have partnered with the City of Cambridge to gather information about air pollution, infrastructure decay, and traffic, writes Haniya Rae for CityLab. The researchers have outfitted five garbage trucks with “accelerometers, air-quality sensors, infrared cameras, and wireless signal monitors,” in an effort to “collect data on the state of the city.”
In an article for Scientific American about the future of robotics, Prof. Emeritus Rodney Brooks highlights Prof. Dina Katabi’s work developing devices that use wireless signals to detect a person’s emotions.
STAT reporter Eric Boodman writes that MIT researchers have engineered living materials that glow when they detect certain chemicals. Boodman notes that the researchers hope the living sensors “could at some point be used to pick up dangerous toxins or the chemical signs of disease.”
Prof. Daniela Rus speaks to the BBC’s Gareth Mitchell about the robots developed by CSAIL that can modify their behavior based on brain waves detected by a human operator. “We imagine operating prosthetic devices, a wheelchair, even autonomous vehicles,” says Prof. Rus.
CSAIL researchers have developed a system that allows robots to correct their mistakes based on input from the brainwaves of human operators, reports Wired’s Matt Simon. “It’s a new way of controlling the robot,” explains Prof. Daniela Rus, “in the sense that we aim to have the robot adapt to what the human would like to do.”
Anthony Cuthbertson of Newsweek writes that CSAIL researchers have developed a system that allows robots to change their actions based on feedback from the brain waves of a human operator. “Imagine robots or smartphones that could immediately correct themselves when you realize they’re making a mistake,” says PhD candidate Joseph DelPreto.
CSAIL researchers have developed a system that allows robots to detect brain signals generated by human operators, writes Oscar Williams of Huffington Post. The researchers hope the new system could “pave the way for more seamless interactions between robots and humans.”