Connected Vehicle Identification System for Cooperative Control of Connected Automated Vehicles

A field evaluation of a recently developed cooperative platooning algorithm in mixed traffic (a.k.a., cooperative adaptive cruise control with the unconnected vehicle, CACCu), developed by PI Park (including human-driven and connected automated vehicles), has shown significant benefits over adaptive cruise control that does not require connectivity. One of the critical challenges of implementing the CACC algorithm is appropriately identifying connected automated vehicles to form a cooperative adaptive cruise control. This identification is not a trivial task mainly because each connected vehicle does not share its vehicle information due to privacy concerns. In addition, the connectivity opens cybersecurity issues. As shown by PI Park, connected vehicles’ communications are vulnerable. The proposed connected vehicle identification system (CVIS) relies on a few sensors, including radar sensors, vehicle-to-vehicle communication devices (e.g., C-V2X), and a global position system (GPS). The preceding vehicle identification system (PVIS) was developed by PI Park, and is currently being expanded to improve its performance by considering surrounding vehicles (needed for the lane-change recommendation) and the use of GPS velocity (much more accurate than location). A simulation-based study showed significant improvements over the immediately preceding vehicle identification system using only GPS distance.

Language

• English

Project

• Status: Active
• Funding: $100000
• Contract Numbers:

  69A3552348303

• Sponsor Organizations:

  Sustainable Mobility and Accessibility Regional Transportation Equity Research Center

  Morgan State University
  Baltimore, MD  United States 

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Project Managers:

  Niehaus, Joseph

• Performing Organizations:

  University of Virginia, Charlottesville

  Center for Transportation Studies
  P.O. Box 400742, Thornton Hall, D228
  Charlottesville, VA  United States  22903
• Principal Investigators:

  Park, Brian

• Start Date: 20230901
• Expected Completion Date: 20240901
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Connected vehicles; Global Positioning System; Identification systems; Mobile communication systems
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01893882
• Record Type: Research project
• Source Agency: Sustainable Mobility and Accessibility Regional Transportation Equity Research Center
• Contract Numbers: 69A3552348303
• Files: UTC, RIP
• Created Date: Sep 21 2023 3:41PM