DeepScenario: City-Scale Scenario Generation for Automated Driving System Testing & Evaluation

In this project, we will build a city-scale scenario generation and simulation platform for ADS testing and evaluation. Under different routes and environmental conditions, the simulation platform can generate testing scenarios dynamically along the route to interact with the CAV and systematically evaluate its performance. Meanwhile, a set of corner cases regarding vulnerable road users (VRUs) will be identified and added to the generated scenario library. We will leverage and extend our existing work in scenario generation and integrate it with VISSIM, CARLA, and Autoware. The platform will also be integrated with the augmented reality testing environment to enable the testing of real CAVs.

Language

• English

Project

• Status: Completed
• Funding: $511,083
• Contract Numbers:

  69A3551747105

• Sponsor Organizations:

  Department of Transportation

  Intelligent Transportation Systems Joint Program Office
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Connected and Automated Transportation

  University of Michigan Transportation Research Institute
  Ann Arbor, MI  United States  48109
• Project Managers:

  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:

  Liu, Henry

  Bao, Shan

  Lin, Brian

• Start Date: 20200301
• Expected Completion Date: 20221231
• Actual Completion Date: 20220228
• USDOT Program: University Transportation Centers Program
• Subprogram: Research

Subject/Index Terms

• TRT Terms: Autonomous land vehicles; Autonomous vehicles; Connected vehicles; Environment; Routes; Simulation; Testing equipment; Virtual reality; Vulnerable road users
• Subject Areas: Data and Information Technology; Policy; Research; Safety and Human Factors; Transportation (General); Vehicles and Equipment;

Filing Info

• Accession Number: 01742714
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3551747105
• Files: UTC, RIP
• Created Date: Jun 18 2020 11:05AM