Development of dynamic network traffic simulator for mixed traffic flow under connected and autonomous vehicles technologies- Phase 1 and 2

Connected and autonomous vehicles (CAVs) will generate a revolution in the transportation system, with great potential to improve traffic safety, efficiency, and environmental sustainability. However, the transition to CAVs will occur over time and, during it, CAVs will coexist with human-driven vehicles (HDVs), connected vehicles (CVs) and autonomous vehicles (AVs) in the traffic flow. While several studies have examined the potential impact of AVs, CVs and CAVs on the driving environment, there is a key need for modeling approaches that can characterize network level evolution of traffic flow dynamics and their impacts on stability under mixed traffic streams. There is the need for a comprehensive traffic flow modeling framework that incorporates different levels of connectivity and automation as well as different market penetration rates.This study will develop a unified car-following modeling framework that models mixed traffic streams under different market penetration rates of CAVs. It will also perform stability analyses to explore implications for safety and mobility.

• Record URL:
  ccat.umtri.umich.edu

Language

• English

Project

• Status: Completed
• Funding: $Total: $109,075 ($43,859 Purdue) ($65,216 CCAT)
• 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:

  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:

  Purdue University, Lyles School of Civil Engineering

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

  Peeta, Srinivas

• Start Date: 20180101
• Expected Completion Date: 20221231
• Actual Completion Date: 20231221
• USDOT Program: University Transportation Centers Program
• Subprogram: Research

Subject/Index Terms

• TRT Terms: Autonomous land vehicles; Connected vehicles; Dynamics; Human factors; Intelligent vehicles; Mobile communication systems; Stability analysis; Traffic flow; Traffic safety; Transportation
• Subject Areas: Data and Information Technology; Planning and Forecasting; Research; Transportation (General); TRAFFIC CONTROL;

Filing Info

• Accession Number: 01666012
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3551747105
• Files: UTC, RIP
• Created Date: Apr 13 2018 2:06PM