Cooperative Adaptive Cruise Control: Taking Cruise Control to the Next Level

Details

• Corporate Creators:
  United States. Federal Highway Administration. Exploratory Advanced Research Program
• Subject/TRT Terms:
  • Autonomous vehicles
  • Autonomous intelligent cruise control
  • Implementation
  • Research projects
  • Traffic flow
  • Vehicle to vehicle communications
  • Mobile communication systems
  • Cruise control
  • Highways
  • Operations and Traffic Management
  More +
• Publication/ Report Number:
  FHWA-HRT-16-044 ; HRTM-30/02-16(WEB)E
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  United States. Federal Highway Administration
• Abstract:
  Using a combination of sensors and vehicle-to-vehicle communication, cooperative adaptive cruise control (CACC) takes cruise control to the next level, enabling vehicles to adjust their speed to the preceding vehicle in their lane. The CACC system can also respond more quickly to speed changes by the preceding vehicle and other vehicles farther ahead that are beyond the line of sight. These advancements improve the stability of traffic flow, increase driver confidence, and make shorter vehicle-following distances possible. Ultimately this results in better use of a highway’s effective capacity and greater fuel efficiency. Overcoming the key remaining technical challenges to implementing CACC is the goal of the Exploratory Advanced Research (EAR) Program project “Using Cooperative ACC to Form High-Performance Vehicle Streams.” The California Partners for Advanced Transportation Technology (PATH) Program at the University of California, Berkeley (UC Berkeley), is conducting this research, which is funded by the Federal Highway Administration (FHWA). The Technical University of Delft in the Netherlands is PATH’s research partner.
• Content Notes:
  Date taken from TRID record. 20190329 CG.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/39739/dot_39739_DS1.pdf
• File Type:
  [PDF - 400.97 KB]
• Collection(s):
  Autonomous Vehicles ; Federal Highway Administration
• Main Document Checksum:
  urn:sha-512:10e3142fc1c605298ba4068ffb4f60c5653510b29f72d73d045a52d2a7d4f5b44b7cfe5d739bd5b03b6d58e8dd81be3749e7e3262b6b525f5fb975a8f25c932a