Center for Connected and Automated Transportation > Research > Research from the University of Michigan > Trajectory Based Traffic Control with Low Penetration of Connected and Automated Vehicles

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

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

Complete
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)
Director – Mcity
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
Final Report