Aspiring to smoother traffic

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There are few better feelings than hitting all green lights on your drive home. Brian Mark’s research aims to bring you that feeling more often. Ideally, technology can help you hit a “green wave” by keeping your car within an optimal speed bracket, says professor of electrical and computer engineering Brian Mark. The increasing likelihood of autonomous vehicles on the road offers a prospect even more promising than the idea of creating an app for human drivers, originally proposed in joint work of Mark and Dr. Mel Friedman, a retired physicist from the Army Night Vision and Electronic Sensors Directorate in Fort Belvoir, Virginia.  Through Mason's Office of Technology Transfer, Friedman and Mark recently submitted a U.S. patent application on a method for coordinating traffic lights and reducing traffic congestion.

“It probably will work even better with connected and automated vehicles,” explains Mark, “so you know the car itself is programmed to keep on the green wave. Like, if you have to turn right, you might not be on the green wave; so ... you might have to catch up to the green wave ahead of you or slow down to catch the green wave behind you.”

Mark supervised a senior design project to move toward his goal sponsored by the Army Strategic Program for Innovation, Research, and Employment (ASPIRE). Three George Mason Electrical and Computer Engineering department teams participated in ASPIRE, supervised by Qilian Li, Brian Mark, and Cameron Nowzari, respectively. As part of the program, in addition to several Zoom meetings, the seniors attended a spring meeting at Fort Belvoir, Virginia, where they presented their project progress.

Mark’s ASPIRE team constructed a model of a connected and automated vehicle. Sara Sulaiman Alaraini, Colin Graves, Corey Jones, Nitin Mandadi, Andrew Mokhtare, and Adham Obeid modified a remote-control vehicle to operate autonomously on a tarp designed like a road system, complete with centralized traffic light–controlled intersections. The team outfitted the car with sensors, a camera, and arUco tags to help it stay oriented in its environment.

"The traffic lights are connected to a centralized server, and the car is able to automatically stop at a traffic light and then go when it turns green,” said Mark.

“Through the centralized server you can indicate the destination ... It will automatically calculate the path through the street grid, and the car will just go to that destination and obey all the traffic lights as it goes.”

Mark hopes a future senior design team can further extend the project by incorporating multiple cars to simulate traffic scenarios.

“The next project would be if you have a bunch of cars. And they're all following green waves, so that they're all obeying the traffic lights. But they never really have to stop unless they have to turn. That would be the ultimate demonstration of this concept.”