Massive field test showing how AI smooths traffic flow
Channel: UC Berkeley
Date: 2022-11-23

Researchers deployed a fleet of 100 semi-autonomous vehicles to test whether a new AI-powered cruise control system can help smooth the flow of traffic and improve fuel economy. 

Many traffic jams are caused by human behavior: a slight tap on the brakes can ripple through a line of cars, triggering a slowdown — or complete gridlock — for no apparent reason. 

But in a massive traffic experiment that occurred outside of Nashville last week, scientists tested whether introducing just a few AI-equipped vehicles to the road can help ease these “phantom” jams and reduce fuel consumption for everyone. The answer seems to be yes.

Over the course of five days, researchers conducted one of the largest traffic experiments of its kind in the world, deploying a fleet of 100 Nissan Rogue, Toyota RAV4 and Cadillac XT5 vehicles onto a busy stretch of Nashville’s I-24 during the morning commute. Each vehicle was equipped with an AI-powered cruise control system designed to automatically adjust the speed of the vehicle to improve the overall flow of traffic — essentially turning each car into its own “robot traffic manager.” 

“Driving is very intuitive. If there’s a gap in front of you, you accelerate. If someone brakes, you slow down. But it turns out that this very normal reaction can lead to stop-and-go traffic and energy inefficiency,” said Alexandre Bayen, associate provost and Liao-Cho Professor of Engineering at the University of California, Berkeley. “That’s precisely what AI technology is able to fix — it can direct the vehicle to things that are not intuitive to humans, but are overall more efficient.”

Bayen is principal investigator of the CIRCLES Consortium, a multi-university research collaboration dedicated to using machine learning to improve traffic flow and increase energy efficiency. Last week’s experiment, which was carried out in coordination with Nissan North America, Toyota, General Motors and the Tennessee Department of Transportation, was the first time the AI technology pioneered by CIRCLES has been tested at this scale. 

“By conducting the experiment at this large of a scale, we hope to show that our results can be reproduced at the societal level,” said CIRCLES co-PI Maria Laura Delle Monache, an assistant professor of civil and environmental engineering at UC Berkeley. “Even when only a few vehicles behave differently, the overall system can be impacted, making it better for everyone on the road and not only for those with AI-equipped vehicles.”
CONT'D

For full story, visit: https://news.berkeley.edu/2022/11/22/massive-traffic-experiment-pits-machine-learning-against-phantom-jams/
Video by Roxanne Makasdjian, Alan Toth, and CIRCLES Consortium
Music: Dyalla - Organic Guitar House, https://www.youtube.com/watch?v=09Uw_OaLsX0

http://news.berkeley.edu/
http://www.facebook.com/UCBerkeley
http://twitter.com/UCBerkeley
http://instagram.com/ucberkeleyofficial