AI-enabled Transportation Network Analysis, Planning, and Operations
Principal Investigator(s):
Yafeng Yin, Donald Cleveland Collegiate Professor Of Engineering – The University of Michigan
Donald Malloure Department Chair Of Civil And Environmental Engineering – The University of Michigan
Project Abstract:
Vehicle connectivity and automation would make vehicle trajectory data more readily available. The proposed research aims to leverage this dataset and recent advancements in implicit deep learning to develop an end-to-end modeling framework that would transform the way how metropolitan planning organizations (MPO) analyze, plan and manage their transportation networks. The proposed framework can directly take empirical, sampled trajectory data as inputs to learn drivers’ route choice behaviors and estimate traffic flow distribution across an urban traffic network. The proposed framework can further prescribe strategies such as lane direction configuration, parking provision, cordon pricing and perimeter control, to better manage the existing supply of urban traffic networks to reduce congestion.
Institution(s): University of Michigan – Ann Arbor
Award Year: 2022
Research Thrust(s): Control & Operations, Modeling & Implementation, Policy & Planning
Project Form(s):