Case Study
Challenges
How could the city of Chicago find a way to reduce waiting times at traffic signals and help reduce traffic congestion?
Solutions
A team consisting of NISS, North Carolina State University, the University of Illinois at Chicago, and CDOT developed prediction models using CORSIM, one of the most widely used traffic simulation models. One of the most important issues was the dual use of observed data to estimate parameters of CORSIM and evaluate the fidelity of its output to reality. Complicating the situation was the need to tune CORSIM both qualitatively and quantitatively in order to remove anomalous behavior that did not match reality.
Outcomes & Results
Waiting times at several intersections and along one major corridor were reduced significantly using the model predictions.
Research Project
The Chicago Department of Transportation (CDOT) implemented NISS-developed strategies for operation of traffic signals on the near North side of Chicago. A team consisting of NISS, North Carolina State University, the University of Illinois at Chicago, and CDOT developed prediction models using CORSIM, one of the most widely used traffic simulation models. One of the most important issues was the dual use of observed data to estimate parameters of CORSIM and evaluate the fidelity of its output to reality. Complicating the situation was the need to tune CORSIM both qualitatively and quantitatively in order to remove anomalous behavior that did not match reality.
Technical Report(s):
Technical Report 112: Statistically-based Validation of Computer Simulation Models in Traffic Operations and Management
Principal Investigator(s): Jerry Sacks
Senior Investigator(s): Nagui M. Rouphail, NCSU
Post Doctoral Fellow(s): B. Brian Park, Piyushimita (Vonu) Thakuriah