A First Investigation of Truck Drivers’ On-the-Road Experience Using Cooperative Adaptive Cruise Control

Cooperative Adaptive Cruise Control (CACC) is a driver assist technology that uses vehicle-tovehicle wireless communication to realize faster braking and acceleration responses in following vehicles and shorter headways compared to Adaptive Cruise Control (ACC). This technology not only enhances road safety, but also offers fuel saving benefits as a result of reduced aerodynamic drag. The amount of fuel savings is dictated by the following distances and the driving speeds. So, the overarching goal of this work is to explore truck drivers’ preferences and behaviors when following in “CACC mode,” an area that remains largely unexplored. While in CACC mode, the brake and engine control actions are automated. A human factors study was conducted to investigate truck drivers’ experiences and performance using CACC at shorter-than-normal vehicle following time gaps. The “On-the-road” experiment required commercial fleets drivers to operate the second and third trucks in a three-truck string on the freeways for 160 miles in Northern California. The experiment was in mixed normal traffic without any on-site assistance of authorities, such as state police. All trucks were equipped with CACC systems and unloaded trailers. Five different time gaps between 0.6 and 1.8 seconds were tested. Factors such as cut-ins by other vehicles, road grades, and traffic conditions influenced drivers’ experience using CACC. Other factors like time gap setting, individual differences, and route section affected drivers’ usage of CACC. These findings reveal truck drivers’ acceptance of the deployment of CACC in their truck fleets and provide useful information for decision making to promote CACC usage in the trucking industry

• Record URL:
  • https://escholarship.org/uc/item/92359572
• Corporate Authors:

  University of California, Berkeley

  California PATH Program, Institute of Transportation Studies
  Richmond Field Station, 1357 South 46th Street
  Richmond, CA  United States  94804-4648

  Federal Highway Administration

  Exploratory Advanced Research Program
  6300 Georgetown Pike
  McLean, VA  United States  22101-2296
• Authors:
  • Yang, Shiyan
  • Shladover, Steven E
  • Lu, Xiao-Yun
  • Spring, John
  • Nelson, David
  • Ramezani, Hani
• Publication Date: 2018-6

Language

• English

Media Info

• Media Type: Digital/other
• Features: Appendices; Figures; References; Tables;
• Pagination: 54p

Subject/Index Terms

• TRT Terms: Autonomous intelligent cruise control; Behavior; Connected vehicles; Driver monitoring; Driver support systems; Driver vehicle interfaces; Field tests; Traffic platooning; Truck drivers; Trucks
• Uncontrolled Terms: Cooperative systems
• Subject Areas: Data and Information Technology; Freight Transportation; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01679988
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Contract Numbers: DTFH61-13-H00012
• Files: BTRIS, TRIS, ATRI, USDOT
• Created Date: Sep 4 2018 9:19AM