The Virginia Tech Mid-Atlantic Aviation Partnership and the Virginia Tech Transportation Institute recently participated in the latest iteration of NASA’s Unmanned Aircraft System (UAS) Traffic Management (UTM) research program.

A series of research flights conducted during the research program focused on how to enable unmanned vehicles to detect and avoid each other, which is one of the most complex issues in unmanned traffic management, and in the UAS industry in general.

“What we call detect-and-avoid is one of the biggest challenges for unmanned-aircraft integration,” says Mark Blanks, the director of the Virginia Tech Mid-Atlantic Aviation Partnership, which operates the university’s FAA-designated UAS test site.

“If you’re flying a manned aircraft, you always have the pilot’s eyes as a backstop. With unmanned aircraft, once it’s out of the operator’s sight, you don’t have that failsafe. So you need a technological solution that’s equivalent or better.”

As part of the NASA project, the team tested two detect-and-avoid-technologies. One was an airborne radar, while the other is a type of radio that allows aircraft and ground vehicles to communicate directly with each other.

“A single, perfect solution for detect-and-avoid is unlikely — the industry is probably going to need a combination of several technologies, depending on the aircraft and the context,” says John Coggin, the aviation partnership’s chief engineer, who led the tests.

“So what we’re doing here is field-testing a couple of the promising candidates, seeing how they perform, and how well they work in concert, and how they integrate with traffic-management software.”  

Echodyne provided the compact radar system used in these tests.

The other piece of technology that was evaluated during testing was a dedicated short-range communication (DSRC) system. ANRA Technologies provided a traffic-management platform that integrated the radar and DSRC signals.

According to Virginia Tech, this was one of the first tests of DSRC for unmanned-aircraft operations, but the university notes that it’s being “widely investigated” for intelligent ground-transportation networks. The stretch of the Virginia Smart Road used for the testing has nine embedded DSRC nodes, which the team used during the testing.

Most of the research was conducted on the Smart Road’s Surface Street Expansion area, a site that recently opened and is designed specifically for automated vehicle evaluation in an urban setting.

“The fantastic infrastructure already in place at VTTI was a major factor in winning the award from NASA to conduct this research,” Blanks says.

“We’re exploring what’s possible with autonomous technologies in multiple modes of transportation, and we’re fortunate to have the experts in ground transportation right here at Virginia Tech.”   

The main focus of the test series was aircraft, but one set of experiments involved a ground vehicle as well. Virginia Tech points out that as autonomous and intelligent transportation becomes more common, “different types of vehicles will need to be able to communicate smoothly with each other so that they can coordinate when necessary, or stay out of each other’s way.”

“We’ve long recognized that DSRC offers great potential for communication between low-flying aircraft and surface vehicles,” comments Andy Alden, a co-principal investigator on the project and researcher at VTTI.

“Integration of communication and detect-and-avoid applications at the nexus of air and ground modes will enable future Urban Air Mobility operations such as package delivery and passenger transport.”

Testing took place over the course of two weeks. During that period, the team put the suite of communications and traffic-management technologies through its fair share of testing, including stress-testing it with some “real-world curveballs” like another UAS that (as a deliberate feature of the test) wasn’t communicating properly, a manned aircraft flying nearby, and a UAS on a high-priority public-safety mission that needed right-of-way.

ANRA’s traffic management platform used the radar and DSRC signals to identify and track both cooperative and noncooperative aircraft, which provided a centralized picture of the operation, and communicated with NASA’s platform.

Virginia Tech says that ultimately, third-party software like ANRA’s will interface with a national system managed by the FAA. NASA is playing the central “regulator” role during the research program.

This is the third year that Virginia Tech has participated in NASA’s UTM research program.

​Below: This drone is carrying equipment designed to allow it to automatically detect and avoid other aircraft, as part of a research project conducted by the Virginia Tech Mid-Atlantic Aviation Partnership, the Virginia Tech Transportation Institute, NASA, and corporate partners.