California PATH Task Order 3013
Title:  Evaluating Adaptive Ramp Metering Control
Researchers: Will Recker, Lianyu Chu (UC Irvine),
                      Michael Zhang, Taewan Kim, Xiaojian Nie, Wenlong Jin (UC Davis)
Time:  2000.8 – 2001.9
Project status: Finished 

Project Summary:

This project evaluates a number of off-the-shelf as well as new ramp metering algorithms using PARAMICS simulation. This project has three objectives:

(1) Review existing ramp metering algorithms and choose a few attractive ones for further evaluation,
(2) Develop a ramp metering evaluation framework using microscopic simulation,
(3) Compare the performances of the selected algorithms and make recommendations about future developments and field tests of ramp metering systems.  

Project Description:

There are about 17 existing ramp metering algorithms, ranging from simple local algorithms to complex integrated algorithms. We developed a classification scheme and a set of evaluation criteria to categorize and qualitatively assess these metering algorithms. Based on the qualitative assessment, ALINEA, Bottleneck, SWARM, and Zone algorithms were selected for further evaluation.

PARAMICS was adopted as the simulation platform for further evaluation of the selected metering algorithms. Several PARAMICS plugin modules, including detector data aggregation (on-line data collection), ramp metering control (mimics ramp signal operations), and ramp metering algorithms (metering logic implementations), are developed to build a simulation based ramp metering evaluation framework. The four selected algorithms were coded into this framework for a stretch of southbound Interstate 405 located in Orange County, California. Finally, the performances of these algorithms are compared under different demand patterns.

Papers and reports: