Minority autonomous cars can optimize traffic flow, experiments show

May 11, 2017 //By Julien Happich
Minority autonomous cars can optimize traffic flow, experiments show
In a recent paper titled "Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments", researchers from the University of Illinois have examined the impact of autonomous vehicles on regulate traffic flow and revealed that just a few self-driving cars (representing as few as 5 percent of all the cars in traffic) can dramatically improve traffic flow.

Funded by the National Science Foundation’s Cyber-Physical Systems program, the research was led by a multi-disciplinary team of researchers with expertise in traffic flow theory, control theory, robotics, cyber-physical systems, and transportation engineering.

The presence of just a few autonomous vehicles can eliminate the stop-and-go driving of the human drivers in traffic, along with the accident risk and fuel inefficiency it causes, long before autonomous cars ever become mainstream, or even if they remained a minority type of vehicle.

The team conducted field experiments in Tucson, Arizona, in which a single autonomous vehicle circled a track continuously with at least 20 other human-driven cars.

Recorded in video, the experiment shows that under normal circumstances, human drivers naturally create stop-and-go traffic, also known as "phantom traffic jam" even in the absence of bottlenecks, lane changes, merges or other disruptions.

By controlling the pace of the autonomous car in the study, they were able to smooth out the traffic flow for all the cars, eliminating waves and reducing the total fuel consumption by up to 40 percent. What's more, simple and easy to implement control strategies were able to achieve that goal. Next on their roadmap, the researchers plan to study the impact of autonomous vehicles in denser traffic with more freedom granted to the human drivers, such as the ability to change lanes.

University of Illinois - www.illinois.edu

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