Vehicle Sensor Data (VSD) Based Traffic Control in Connected Automated Vehicle (CAV) Environment

Connected Automated Vehicle (CAV) are typically equipped with communication devices (e.g., DSRC) and on-board sensors (e.g., Radar, Lidar, Camera, etc.). Communication devices would enable exchange of real-time information between vehicles and infrastructures via Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) channels. Sensors equipped in vehicles are providing various Vehicle Sensor Data (VSD) such as the CAV’s global positioning system (GPS) location, speed and moving direction, and traffic data of detected regular vehicles. In current applications, collected VSD are commonly used for avoiding collisions only. Therefore, most existing CAV-based traffic control models, which only rely on the trajectory data of CAVs, would fall short of efficiency when CAV penetration rate is low. In this project, the research team aims to fully utilize VSD for traffic operation purpose and develop an innovative traffic control framework that can facilitate the implementation of CAV-based systems. Using on-board sensors, the system can monitor traffic conditions surrounding each CAV. Then through both V2V and V2I channels, all collected information will be integrated and a dynamic Ad-Hoc Sensor Network (ADSN) will be constructed. Under such framework, each CAV can be treated as a moving traffic sensor and detected regular vehicles will be “linked” with the CAVs. The objectives of this project are summarized as follows: 1) develop a macroscopic traffic flow model to estimate freeway traffic state information using VSD; 2) perform real-time speed control of CAVs for traffic efficiency improvement; and 3) prove the effectiveness of the proposed model under low CAV penetration rate condition with experimental tests. This project will demonstrate a proof of low CAV rate control concept which can serve as the foundation of future studies.


  • English


  • Status: Active
  • Contract Numbers:

    NITC 1175

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590

    University of Utah, Salt Lake City

    College of Engineering, Department of Civil Engineering
    Salt Lake City, UT  United States  84112-0561
  • Managing Organizations:

    TREC at Portland State University

    1900 SW Fourth Ave, Suite 175
    P.O. Box 751
    Portland, Oregon  United States  97201
  • Project Managers:

    Hagedorn, Hau

  • Performing Organizations:

    University of Utah, Salt Lake City

    College of Engineering, Department of Civil Engineering
    Salt Lake City, UT  United States  84112-0561
  • Principal Investigators:

    Yang, Xianfeng

  • Start Date: 20171101
  • Expected Completion Date: 20181031
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01651395
  • Record Type: Research project
  • Source Agency: National Institute for Transportation and Communities
  • Contract Numbers: NITC 1175
  • Files: UTC, RiP
  • Created Date: Nov 21 2017 4:11PM