U.S. Transportation Secretary Elaine L. Chao recently announced that the FAA is awarding $2.6 million in research, education, and training grants to universities that make up the agency’s Air Transportation Center of Excellence (COE) for UAS, which is also known as Alliance for System Safety of UAS through Research Excellence (ASSURE). The grants are designed to advance specific goals and projects. “The research funded by these grants will provide valuable data as the Department leads the way to chart a course for the safe integration of drones into our national airspace,” Secretary Chao said.

To help driverless cars learn to navigate a variety of worse-case scenarios before they begin operating on real roads, researchers at MIT have invented a simulation system to train driverless cars that creates a photorealistic world with “infinite” steering possibilities.  According to the researchers, control systems—also known as “controllers” —for autonomous vehicles largely rely on real-world datasets of driving trajectories from human drivers. The vehicles use this data to learn how to emulate safe steering controls in different situations. Researchers note, though, that real-world data from hazardous “edge cases,” such as nearly crashing or being forced off the road or into other lanes, are rare.

As part of a collaborative project, researchers at Queensland University of Technology (QUT) in Queensland, Australia will use drones and infrared imaging to identify wildlife populations in bushfire affected areas.

Mathematicians have discovered that a drone equipped with microphones and a speaker—with the help of algebra and geometry—can echolocate similarly to how bats use echolocation to orient themselves with their surroundings. According to Purdue University associate professor of mathematics and electrical and computer engineering Mireille “Mimi” Boutin, this signal processing research could have potential applications for people, underwater vehicles and even cars.