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- A Nissan trial with UC Berkeley and Contra Costa Transportation Authority showed how connected vehicles can help reduce congestion
- Nissan’s Cooperative Congestion Management (CCM) trial yielded 85% fewer hard-braking events and 70% less time stopped in traffic over 600 miles of testing
- ProPILOT Assist, Nissan’s advanced driver assistance technology, powered the CCM trial with cameras and radar sensors
Americans spend roughly a week each year stuck in traffic, according to CNBC. Nissan is testing a potential solution: vehicles equipped with ProPILOT Assist and innovative inter-car communication that could make commutes safer and more efficient.
Through a partnership with Contra Costa Transportation Authority (CCTA) and the University of California, Berkeley, a team at Nissan’s Advanced Technology Center – Silicon Valley (NATC-SV) is working to help reduce congestion.
Called Cooperative Congestion Management (CCM), the program is designed to smooth traffic by optimally coordinating vehicle speeds. Computer simulations established the concept, indicating travel times could be reduced by 18% and fuel economy could improve by up to 42%.
“Our goal is to eliminate the waste of stop-and-go traffic,” said Zvi Guter, senior manager of mobility research, who is leading the CCM project at Nissan’s Silicon Valley lab.
How does Cooperative Congestion Management work?
In typical traffic patterns, drivers often follow too closely. This prevents them from seeing slowing traffic ahead, leading to hard braking when approaching the slower traffic. This creates stop-and-go waves, which are less efficient than traveling at a steady pace.
“Stop-and-go traffic is often due to the imperfection of human driving behavior,” Guter said.
CCM’s goal is to predict and guide collective behavior, which would reduce the inefficiencies of human driving and create a steadier, more efficient traffic environment. The CCM trial uses data from one “probe” vehicle to help others keep an appropriate distance and speed. The “probe” vehicle is ahead and supplies congestion data to a second set of vehicles 30 to 60 seconds behind. The second set of vehicles then gently adjusts their speeds in advance of the jam, creating a smooth buffer for trailing cars.
It relies on ProPILOT Assist, Nissan’s semi-autonomous driver assistance technology available on most U.S. models. This reduces the need for hard braking and allows traffic to flow more consistently instead of entering a stop-and-go pattern.
Data from a “probe” vehicle allows following vehicles to adjust their speed, smoothing traffic by reducing inefficient stop-and-go patterns.
During 600 miles of testing on Interstate 680 in the San Francisco Bay Area, vehicles with CCM software logged 85% fewer hard-braking incidents and 70% less time stopped in traffic. It also reduced the incidence of vehicles following too closely and risking rear-end accidents.
Backed by an Automated Driving Systems grant from the U.S. Department of Transportation, CCTA oversaw project design, coordination and data collection to evaluate how Nissan’s technologies can improve traffic flow, enhance safety and reduce congestion on one of Contra Costa County’s most congested corridors.
“Our testing indicates CCM doesn’t just make commuting more comfortable and efficient – but safer, too,” Guter said.
The team says ProPILOT Assist has been critical to the project’s success, thanks to its sophisticated array of cameras and radar sensors.
“Nissan’s advanced tech and high-quality hardware made integrating the CCM software much easier,” said Jerry Chou, a senior researcher at Nissan’s Silicon Valley office.
Real-world testing showed Cooperative Congestion Management reduced hard-braking events by 85%.
Overcoming technical and social challenges
Undertaking the project was a daunting endeavor.
“One of the biggest challenges was demonstrating the effectiveness of the system in traffic with just a handful of controlled vehicles,” Chou said. “The success of the trial, even with a small number of controlled vehicles, demonstrates how the system can begin to influence collective traffic behavior and provides a glimpse of potential future benefits.”
For more than three years, the Nissan team developed the project with research lead Jonathan Lee from Professor Alexandre Bayen’s lab at UC Berkeley. Another substantial challenge they faced was adjusting for human behavior. For example, when one of the test vehicles begins gently slowing down ahead of a traffic jam, its driver might try to override the system and “fill the gap” between it and upcoming traffic.
“In order to make this more acceptable to the human driver, we’re trying to enhance the vehicle interface to let the driver know why we’re slowing down,” said Joy Carpio, a researcher at Nissan’s Silicon Valley office.
A view from inside a CCM-equipped Nissan Ariya during testing on I-680 in the San Francisco Bay Area.
The team said educating people about CCM and helping them understand how it can help them save time and money is critical.
“It requires cooperation. If drivers don’t accept the solution, it will be difficult to implement,” Carpio said.
Scaling up for the future
When will communicating cars start to impact traffic everywhere? While the team cannot yet say when the technology will be implemented at scale, the fact that it’s already showing results in real-world testing is promising.
“The hope is that by using more common technology like 4G LTE to communicate, CCM can easily scale up to accommodate more users,” Guter said.
For the next phase of the project, the team wants to better understand how the average driver interacts with the system.
“We want our system to seamlessly account for human behavior,” Carpio said.
The team believes CCM’s success depends on drivers understanding how it works and the potential benefits – from shorter commutes to reduced emissions.
“It doesn’t just have the potential to make Nissan drivers safer and more comfortable – it has a positive impact on the transportation system as a whole,” Guter said.
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About Nissan Technical Center – Silicon Valley
Based in Santa Clara, Calif., the Nissan Advanced Technical Center – Silicon Valley (NATC-SV) is the center of global excellence for artificial intelligence and next-generation mobility solutions at Nissan. Researchers and scientists at the center study robotics – combined with computer, data and social sciences – to improve mobility today and invent real solutions for tomorrow.
Zvi Guter is a senior manager of Tech Mobility research at NATC-SV. He holds a Bachelor of Science in computer science and a Master of Science in applied mathematics.
Fang Chieh “Jerry” Chou is a senior researcher at NATC-SV. He holds a Bachelor of Science, Master of Science and Ph.D. in mechanical engineering.
Joy Carpio is a researcher at NATC-SV. She holds a Bachelor of Science and Master of Science in electronics engineering, and a Ph.D. in systems engineering.
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