Trajectory Based Traffic Control with Low Penetration of Connected and Automated Vehicles

Trajectory Based Traffic Control with Low Penetration of Connected and Automated Vehicles

Yiheng Feng Headshot - link directs to their research page
Yiheng Feng
Headshot of CCAT Director, Henry Liu - link directs to their research page
Henry Liu
University of Michigan Transportation Research Institute Logo - link directs to U-M research page

Principal Investigator(s):

Yiheng Feng, Assistant Research Scientist – The University of Michigan Transportation Research Institute
Henry Liu, Director – Center for Connected and Automated Transportation (CCAT)
Professor of Civil and Environmental Engineering – The University of Michigan
Research Professor – The University of Michigan Transportation Research Institute

Project Abstract:
This project aims at developing new science and technology of vehicle trajectory based traffic control, especially under lower penetration of CAVs. Most of the existing models require at least a moderate penetration rate (e.g., 30%) to be effective. How to estimate real-time traffic condition and perform control under lower penetration rate (e.g., <10%) is still an open question. In addition, when the vehicle control is incorporated into signal control, usually a fully CAV environment is assumed. The interactions between CAVs and regular vehicles in a mixed traffic condition are not thoroughly investigated.

Institution(s): University of Michigan Transportation Research Institute

Award Year: 2018

Research Thrust(s): Control & Operations

Project Form(s):
Project Information Form