Connectivity & Autonomy

Game-Changing Research

Connectivity and autonomy are rebooting transportation, fundamentally changing how vehicles are designed, engineered, manufactured, sold, serviced, and used. Lawrence Berkeley National Laboratory (Berkeley Lab) is on the cutting edge of connected and autonomous vehicle research.

Connectivity & Autonomy

Smart grid graphicFuture transport systems will certainly be connected, data-driven, and highly automated, revolutionizing transportation in the U.S. and the world. Communities will enjoy many benefits, including improved mobility for the elderly and disabled, enhanced transit connections, increased safety and energy efficiency, and decreased air pollution.

Connected and autonomous vehicles (CAVs) research is exploding. Berkeley Lab and University of California, Berkeley (UC Berkeley) are partnering on pioneering research in systems modeling, vehicle and highway automation, traffic system modeling, and vehicle dynamics and control, along with active vehicle and intersection safety.  

They apply and extend advanced communications technologies to track and transmit velocity and distances between vehicles and infrastructure improving safety and reducing fuel consumption. They also engage a host of machine language techniques, including deep learning and deep reinforcement learning, to optimize traffic conditions and improve air quality. (See article "Machine Learning to Help Optimize Traffic and Reduce Pollution".)

These complex multi-year projects require extensive collaboration among researchers from Berkeley Lab, multiple UC Berkeley departments, and other universities and corporate research centers.

Collaborations and Partnerships

Partners for Advanced Transportation Technology (California PATH)

California PATH is a research center of the Berkeley Institute for Transportation Studies

California PATH addresses California’s multitude of economic, environmental, and transportation challenges while developing the next generation of transportation professionals in these areas:

  • Vehicle automation
  • Vehicle and infrastructure connectivity
  • Transportation safety and security
  • Next-generation transportation corridor management
  • Innovative transit solutions to improve ridership
  • Advanced transportation decision support
  • Fleet and vehicle energy and emission reduction
  • Deep learning for automotive perception Berkeley DeepDrive 

Xiao-Yun Lu, research engineer at California PATH and affiliate at Berkeley Lab, addresses some of these challenges.

One area of focus is on how cooperative adaptive cruise control (CACC) can enhance traffic flow stability and improve safety. CACC builds on adaptive cruise control (ACC) ability to automatically adjust a vehicle’s speed to maintain a safe distance from vehicles ahead. In CACC, distances and velocity are not derived from periodic radar or laser positioning as in ACC, but are continuously transmitted through a message system. Lu and his colleagues explore multiple applications of this communication technology and build models to quantify their impact on traffic mobility and vehicle fuel consumption for heavy-duty trucks and passenger vehicles.

Another technology, Dedicated Short Range Communications (DSRC), is an open-source protocol for highly secure, high-speed wireless communication between vehicles and transportation infrastructure. Lu has applied DSRC vehicle-to-vehicle (V2V) communication in the control design, simulation, implementation, and field test of three-truck platooning for mobility and energy efficiency improvement. (See video "3-Truck CACC Test" and slideshow "Overview of California PATH’s Cooperative Truck Platooning Systems.")

Lu also engages multiple research approaches to tackle freeway traffic bottlenecks, including freeway corridor traffic detection, modeling, simulation, optimal control algorithm development, and field implementation. This work has included coordinating freeway corridor ramp metering and arterial corridor intersection traffic signal controls. One aspect of this work is the following project:

Traffic Microsimulation of Energy Impacts of CAV Concepts at Various Market Penetrations.

This project aims to enhance traffic microsimulation models with additional CAV concepts, including signalized arterial and freeway environments. The team is also simulating the interactions of the CAV vehicles with conventional vehicles over a range of traffic volumes and market penetration levels to show the trends in performance and ultimately measure and evaluate the energy, mobility, and emission impact of mixed traffic with different levels of CAVs.

The Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) Consortium

Dr. Alexandre Bayen, faculty scientist at Berkeley Lab, is Principal Investigator for CIRCLES. Bayen is also the Liao-Cho Professor of Engineering at UC Berkeley and the Director of the Institute of Transportation Studies. CIRCLES is a consortium of researchers and engineers from Berkeley Lab, UC Berkeley, Rutgers University, University of Arizona, Temple University, Vanderbilt University, Toyota North America, and General Motors Research.

CIRCLES researchers aim to improve the future of transportation and advance the convergence of artificial intelligence, simulation, traffic engineering, and vehicle technology in the context of mixed human-autonomous traffic. The long-term goal of this project is to design, test, and deploy the first connected and autonomous vehicle (CAV) enabled system to actively reduce stop-and-go phantom traffic jams on freeways and thus significantly reduce the energy consumption of transportation.

Prior work on closed-course testing demonstrated that phantom jams could be reduced using autonomous vehicle technologies and specially-designed algorithms. (See work at phantomjams.github.io/.) The CIRCLES project seeks to extend this technology to real-world traffic, where reducing these adverse traffic effects could provide ≥10% energy savings.

CIRCLES researchers have created four major products, including software libraries, utilities, frameworks, and tools to support the project.

The project is currently in planning mode, and the team is seeking seed grants from various organizations and companies. They will leverage these to write large grant proposals to federal agencies (the National Science Foundation and U.S. Department of Transportation), State Agencies (California Department of Transportation), and the private sector (Amazon, Toyota, Tesla, Uber, and Renault/Nissan in particular).

Berkeley Institute of Transportation Studies (ITS)

ITS addresses challenges in our transportation systems, including safety, energy consumption, an aging infrastructure, and a lack of reliability, resilience, and sustainability. Spanning nine departments and four colleges within UC Berkeley and two divisions at Berkeley Lab, ITS is a unique environment where the entire pipeline from science and technology inception to deployment can be brought to bear on these challenges, working directly with transportation practitioners and the worlds of policy and governance in which they must function.

ITS researchers work in a wide range of fields, including robotics and machine learning, behavioral economics, policy, and urban planning. To effectively harness that expertise, our plan for the future focuses on four growth areas that will allow us to advance the knowledge base in key fields such as self-driving cars, airspace governance for the coming drone revolution, and a clean-energy infrastructure. With our mission of service to the State of California, and with our San Francisco Bay Area location — ground zero for the extraordinary data-rich, technologically advanced era in which we live — ITS aims to be the inventor of the smart cities of tomorrow, contributing to an always-more-efficient and sustainable transportation system. 

Data, Tools, and Facilities

Transportation Library

The Transportation Library located at UC Berkeley is the most innovative transportation library in the nation, focusing on using specialized data and leveraging electronic resources to:

•  Advance success and impact through effective information management
•  Support primary missions of research and graduate education through targeted services designed to teach information literacy and provide efficient, long-term access to relevant, timely information
•  Promote access to information, particularly research results, to the broader transportation research community

National Energy Research Scientific Computing Center (NERSC)

NERSC is a U.S. Department of Energy Office of Science user facility that serves as the primary high-performance computing center for scientific research sponsored by the Office of Science. Located at Berkeley Lab, NERSC serves more than 7,000 scientists at national laboratories and universities researching a wide range of problems in combustion, climate modeling, fusion energy, materials science, physics, chemistry, computational biology, and other disciplines.

NERSC is known as one of the best-run scientific computing facilities in the world. It provides some of the largest computing and storage systems available anywhere, but what distinguishes the center is its success in creating an environment that makes these resources effective for scientific research. NERSC systems are reliable and secure, and provide a state-of-the-art scientific development environment with the tools needed by the diverse community of NERSC users. NERSC offers scientists intellectual services that empower them to be more effective researchers. For example, many of our consultants are themselves domain scientists in areas such as material sciences, physics, chemistry, and astronomy, and are well-equipped to help researchers apply computational resources to specialized science problems.

Team Member
Team Member