Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data

In this project, the team will develop a methodological framework for modeling the high-fidelity naturalistic driving environment (NDE) with high-resolution trajectory data. Different from traditional NDE models that mainly match the moments of macroscopic traffic behaviors, the high-fidelity NDE models will match the distributions of microscopic driving behaviors, which are critical for safety-critical applications such as autonomous vehicle testing and training. The large-scale high-resolution data that is being collected by roadside sensors will be leveraged. The developed NDE models will be implemented at the SAFE-TEST toolbox for the safety assessment of autonomous vehicles at the American Center for Mobility, which will significantly expand the toolbox into the complex urban driving environment. Both the high-resolution data collection system and SAFE-TEST toolbox were developed by the PI research team with previous CCAT and Mcity sponsored projects.

• Record URL:
  ccat.umtri.umich.edu

Language

• English

Project

• Status: Active
• Funding: $250000
• Contract Numbers:

  69A3551747105

• 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:

  Bezzina, Debra

  Tucker-Thomas, Dawn

• Performing Organizations:

  University of Michigan Transportation Research Institute

  2901 Baxter Road
  Ann Arbor, Michigan  United States  48109

  University of Michigan, Ann Arbor

  Department of Civil and Environmental Engineering
  2350 Hayward
  Ann Arbor, MI  United States  48109-2125
• Principal Investigators:

  Feng, Shuo

  Liu, Henry

• Start Date: 20220401
• Expected Completion Date: 20230331
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers
• Subprogram: Research

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Autonomous vehicles; Connected vehicles; Macroscopic traffic flow; Vehicle safety; Vehicle tests
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01842625
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3551747105
• Files: UTC, RIP
• Created Date: Apr 18 2022 11:45AM