Imagine getting through your evening commute safely and seamlessly without ever having to wait at a red light or stop sign. This is what a research team at the University of Missouri's College of Engineering is studying in terms of self-driving roads.
Dan Lin, a professor in Electrical engineering and computer science, and Jian KangThe doctoral student has developed a universal intersection traffic management system for autonomous vehicles. The system is known as Dynamic Autonomous Vehicle Stream Handling or DASH.
DASH relies on intersection managers to detect cars as they approach an intersection and then signal vehicles to either accelerate, slow down, or weave so that all cars can get through without interruption.
"The vehicles would provide basic information about speed, direction and the path they want to go: left, right, or straight," Lin said. "The intersection manager – a small local server – would calculate the plan for all the cars that enter in a given period of time."
Now Kang is working on ensuring security. Should an autonomous vehicle be compromised near an intersection, other neighboring cars could be alerted and react accordingly. This includes maintaining a safe distance between vehicles approaching the intersection so that cars can stop in time.
"Without the security, this type of system will not be deployed because a single malicious car could crash an entire intersection," Lin said. "We want other cars to collect this information and evacuate it as quickly as possible, or just stop and let the vehicle drive past."
Relax if you are already thinking of self-driving cars pulling you through a traffic light intersection. Systems like DASH won't be possible until all vehicles on the road are autonomous – likely in decades, Lin said.
But that doesn't mean it won't happen. Research is usually at least a decade ahead of development, she said. As a PhD student, Lin suggested that an application could help motorists find gas stations nearby.
"It seemed very futuristic 15 years ago," she said. "Now we're looking for the nearest gas stations with our mobile devices."
Source: University of Missouri