Economical Acquisition of Intersection Data to Facilitate CAV Operations Phase II - Implementation

Cost-effective collection and distribution of intersection data are needed to facilitate traffic operations at intersections in the heavy duty vehicle (HDV) era and particularly, in the prospective era of connected autonomous vehicles (CAVs). Existing methods are time consuming and costly. The first part of this research (executed under CCAT Project Nr. 71), which ended August 2023, developed a cost-effective intersection data collection and distribution device for this purpose (see photo). This device prototype was bench tested in Spring and Summer of 2023 at Lansing and Owosso, respectively, and was found to successfully make SPaT and MAP data easy to collect and dissimulate via to mobile devices. The proposed research (Phase 2) will provide research personnel resources to deploy the device at a number of intersections in the City of Owosso, MI.

Language

  • English

Project

  • Status: Active
  • Funding: $50000
  • Contract Numbers:

    69A3552348305

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    University of Michigan Transportation Research Institute

    2901 Baxter Road
    Ann Arbor, Michigan  United States  48109
  • Project Managers:

    Stearns, Amy

  • Performing Organizations:

    Purdue University, Lyles School of Civil Engineering

    550 Stadium Mall Drive
    West Lafayette, IN  United States  47907
  • Principal Investigators:

    Labi, Samuel

    Krogmeier, James

  • Start Date: 20231201
  • Expected Completion Date: 20241130
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01906128
  • Record Type: Research project
  • Source Agency: Center for Connected and Automated Transportation
  • Contract Numbers: 69A3552348305
  • Files: UTC, RIP
  • Created Date: Jan 26 2024 4:42PM