New technique helps autonomous vehicles navigate complex traffic situations

Developed at North Carolina State University, the technique allows autonomous vehicle software to make the relevant calculations more quickly, thereby improving traffic and safety in simulated autonomous vehicle systems.

“Right now, the programs designed to help autonomous vehicles navigate lane changes rely on making problems computationally simple enough to resolve quickly, so the vehicle can operate in real time,” said Ali Hajbabaie, corresponding author of a paper on the work and an assistant professor of civil, construction and environmental engineering at NC State. “However, simplifying the problem too much can actually create a new set of problems, since real world scenarios are rarely simple.”

Hajbabaie continued: “Our approach allows us to embrace the complexity of real-world problems. Rather than focusing on simplifying the problem, we developed a cooperative distributed algorithm. This approach essentially breaks a complex problem down into smaller sub-problems, and sends those to different processors to solve separately. This process, called parallelisation, improves efficiency significantly.”