Locomation, the provider of what it calls the world’s first trucking technology platform to offer human-guided autonomous convoying, has announced a research project with the Transportation Research Center Inc. (TRC) in East Liberty, Ohio. Alongside TRC’s extensive research and development team, Locomation will actively test at the research center to advance its autonomous truck platforms, in an effort to facilitate more innovation on the testing and validation of the company's autonomy technology.

A team of researchers from Oklahoma State University (OSU) has been recognized with the University Leadership Initiative (ULI) Award from NASA, and will receive $5.2 million in funding over the next four years to address some of NASA’s strategic research initiatives. Featuring faculty members and students from the College of Engineering, Architecture and Technology, the OSU team will seek to improve real-time weather forecasting of low-level winds and turbulence in both rural and urban environments, with the ultimate goal of improving safety for UAS flying in Advanced Air Mobility (AAM) operations.

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.