That vision took a step closer to reality in a groundbreaking Cooperative Congestion Management (CCM) trial. Conducted in partnership with the Contra Costa Transportation Authority (CCTA), the University of California, Berkeley, software consultancy DAVTEQ, and Advanced Mobility Group, the trial demonstrated how connected vehicles equipped with Nissan’s ProPILOT Assist driver-assistance technology could ease congestion and reduce unsafe driving behaviors.
The results were striking. Across 600 miles of testing along Interstate 680 in the San Francisco Bay Area, the system achieved 85% fewer hard-braking events and 70% less time spent stopped in traffic. The findings suggest that even with a limited number of vehicles, CCM could make commuting not only smoother but also safer.
Tackling the stop-and-go problem
Most traffic jams are not caused by accidents or construction, but by small inefficiencies in how humans drive. Drivers following too closely may fail to notice slowing traffic until the last second, slamming on their brakes. That creates a ripple effect, causing “stop-and-go waves” that spread backward through traffic.
“Stop-and-go traffic is often due to the imperfection of human driving behavior,” explained Zvi Guter, senior manager of mobility research at Nissan’s Advanced Technology Center – Silicon Valley (NATC-SV). “Our goal is to eliminate the waste of stop-and-go traffic.”
The CCM system seeks to counter this natural tendency. It uses a “probe” vehicle to collect congestion data, which is then shared with a group of vehicles trailing 30 to 60 seconds behind. These vehicles gently adjust their speeds in advance, creating a buffer zone that absorbs the slowdown before it turns into a stop-and-go pattern.
At the heart of the system is Nissan’s ProPILOT Assist technology, available on many U.S. Nissan models. ProPILOT uses cameras and radar sensors to maintain lane position and safe following distances. For the CCM trial, engineers layered new communication software on top of ProPILOT to allow the vehicles to coordinate speeds in response to real-world congestion.
Results from real-world testing
Computer simulations conducted before the trial suggested that coordinated driving could cut travel times by 18% and improve fuel economy by as much as 42%. The real-world results supported those predictions, showing dramatic reductions in unsafe and inefficient driving behaviors.
During the 600 miles of testing, vehicles operating with CCM software experienced:
- 85% fewer hard-braking events
- 70% less time spent completely stopped
- Fewer instances of unsafe tailgating
“Our testing indicates CCM doesn’t just make commuting more comfortable and efficient—but safer, too,” Guter said.
The project was supported by an Automated Driving Systems grant from the U.S. Department of Transportation. The Contra Costa Transportation Authority coordinated the trial, overseeing project design and data collection to evaluate how Nissan’s technologies could help ease congestion in one of the Bay Area’s busiest corridors.
Jerry Chou, senior researcher at NATC-SV, credited Nissan’s hardware for enabling the trial’s success. “Nissan’s advanced tech and high-quality hardware made integrating the CCM software much easier,” he said.
Overcoming challenges
Despite its promising results, the project faced technical and human challenges. One of the biggest hurdles was proving the effectiveness of the system with only a handful of test vehicles.
“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,” Chou explained.
Human behavior added another layer of complexity. For instance, when a test vehicle slowed down in anticipation of a traffic jam, some drivers were tempted to override the system to “fill the gap.” Nissan researchers are working on better ways to communicate with drivers about why the vehicle is slowing.
“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, researcher at NATC-SV.
Education will be key to gaining acceptance, Carpio added. “It requires cooperation. If drivers don’t accept the solution, it will be difficult to implement.”
Scaling up for the future
The natural question is when such technology might be available to everyday drivers. While there is no set timeline, the team is optimistic. Because the system relies on widely available technology such as 4G LTE for vehicle communication, scaling it up could be relatively straightforward.
“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.
The next phase of research will focus on how average drivers interact with the system in different real-world conditions. “We want our system to seamlessly account for human behavior,” Carpio explained.
Researchers believe that success will depend on helping drivers understand the benefits—from shorter commutes and fewer accidents to lower 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.
Why this matters
Traffic congestion costs the U.S. economy billions of dollars each year in lost time and wasted fuel. It also contributes to road rage, stress, and harmful emissions. By addressing one of the root causes of congestion—inefficient human driving—CCM could be a game-changer.
The potential benefits include:
- Shorter, more predictable commutes
- Fewer accidents caused by tailgating and hard braking
- Improved fuel efficiency and reduced emissions
- A smoother, less stressful driving experience
If widely adopted, systems like CCM could help cities and states make better use of existing roadways without the need for costly expansions.
About Nissan’s Silicon Valley research center
The Nissan Advanced Technology Center – Silicon Valley (NATC-SV), based in Santa Clara, California, serves as a global hub for artificial intelligence and next-generation mobility research. Scientists and engineers at NATC-SV focus on robotics, data science, and human-machine interaction, with the goal of inventing practical solutions for future transportation challenges.
Project leaders include:
- Zvi Guter, senior manager of Tech Mobility research, with a background in computer science and applied mathematics.
- Fang Chieh “Jerry” Chou, senior researcher, with advanced degrees in mechanical engineering.
- Joy Carpio, researcher, with expertise in electronics and systems engineering.
Their combined efforts, alongside academic and public sector partners, are helping lay the groundwork for smarter, safer, and more efficient mobility solutions.