UC Berkeley Research Reports
Title Evaluation of On-ramp Control Algorithms
Permalink https://escholarship.org/uc/item/83n4g2rq
Authors Zhang, Michael Kim, Taewan Nie, Xiaojian et al.
Publication Date 2001-12-01
eScholarship.org Powered by the California Digital Library University of California CALIFORNIA PATH PROGRAM INSTITUTE OF TRANSPORTATION STUDIES UNIVERSITY OF CALIFORNIA, BERKELEY
Evaluation of On-ramp Control Algorithms Michael Zhang, Taewan Kim, Xiaojian Nie, Wenlong Jin University of California, Davis Lianyu Chu, Will Recker University of California, Irvine
California PATH Research Report UCB-ITS-PRR-2001-36
This work was performed as part of the California PATH Program of the University of California, in cooperation with the State of California Business, Transportation, and Housing Agency, Department of Transportation; and the United States Department of Transportation, Federal Highway Administration.
The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the State of California. This report does not constitute a standard, specification, or regulation.
Final Report for MOU 3013
December 2001 ISSN 1055-1425
CALIFORNIA PARTNERS FOR ADVANCED TRANSIT AND HIGHWAYS Evaluation of On-ramp Control Algorithms
September 2001
Michael Zhang, Taewan Kim, Xiaojian Nie, Wenlong Jin University of California at Davis
Lianyu Chu, Will Recker PATH Center for ATMS Research University of California, Irvine
Institute of Transportation Studies One Shields Avenue University of California, Davis Davis, CA 95616 ACKNOWLEDGEMENTS
Technical assistance on Paramics simulation from the Quadstone Technical Support sta is also gratefully acknowledged.
ii EXECUTIVE SUMMARY
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, and 3) compare the performances of the selected algorithms and make recommendations about future developments and eld tests of ramp metering systems.
About 17 ramp metering algorithms, ranging from simple local algorithms to complex in- tegrated algorithms, are rst categorized and assessed qualitatively. Prior to our review, we developed a classi cation scheme and a set of evaluation criteria to aid the categorization and qualitative assessment of the selected 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 me- tering algorithms. Several API (Application Programming Interface) modules, including Loop aggregation API (on-line data collection), Ramp API (mimics ramp signal operations), and Ramp Algorithm APIs (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 south bound Interstate 405 located in Orange County, California. To compare the performance of these algorithms, multiple simulation runs were made under di erent demand patterns. Using the total vehicle travel time (TVTT) as the measurement of e ectiveness (MOE), our evaluation study nds that: