Technical Papers
Nov 30, 2021

Mobility Impacts of Ramp Metering Operations on Freeways

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 2

Abstract

Transportation agencies are implementing traffic management strategies to improve mobility and safety on freeways. Ramp metering is a traffic management strategy deployed to mitigate congestion on freeways by using traffic signals installed at on-ramps to control and regulate vehicle entry onto the freeway mainline. Estimating the mobility benefits of ramp metering is critical not only to determine the strategy’s effectiveness but also to inform the decision-making process regarding its deployment. The before-and-after approach and ramp metering shutdown experiments are conventional methods for estimating the benefits of ramp metering. These methods could overestimate or underestimate the benefits. This study aimed to estimate the expected mobility benefits of ramp metering by leveraging ramp metering downtime due to system breakdowns. Buffer index (BI), a travel time reliability measure, was selected as the performance measure. The study was based on data collected from 2016 to 2018 on a corridor with ramp metering signals (RMSs) along I-95 in Miami-Dade County, Florida. Penalized regression methods were used to identify factors that could predict the buffer indices of the freeway segment with RMSs. Factors evaluated include ramp metering operations (on/off), freeway traffic congestion levels, freeway mainline traffic speed, ramp traffic volume, and density of on-ramps and off-ramps. Results showed a 23% reduction in BIs during moderate congestion and a 28% reduction in BIs during severe congestion. Transportation agencies could use the results when evaluating RMSs operational performance and comparing their mobility impact with other alternatives.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The available information is the analysis code.

Acknowledgments

The authors would like to acknowledge the financial support of the Florida International University Dissertation Year Fellowship. This research was sponsored by the Florida Department of Transportation (FDOT) and conducted as a cooperative effort by Florida International University (FIU) and the University of North Florida (UNF). The opinions, findings, and conclusions expressed in this publication are those of the author(s) and not necessarily those of the Florida Department of Transportation.

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 148Issue 2February 2022

History

Received: Jan 14, 2021
Accepted: Oct 14, 2021
Published online: Nov 30, 2021
Published in print: Feb 1, 2022
Discussion open until: Apr 30, 2022

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Authors

Affiliations

Henrick J. Haule, S.M.ASCE [email protected]
Graduate Student, Dept. of Civil and Environmental Engineering, Florida International Univ., 10555 West Flagler St., Miami, FL 33174 (corresponding author). Email: [email protected]
Priyanka Alluri, Ph.D., M.ASCE [email protected]
P.E.
Associate Professor, Dept. of Civil and Environmental Engineering, Florida International Univ., 10555 West Flagler St., Miami, FL 33174. Email: [email protected]
Thobias Sando, Ph.D., M.ASCE [email protected]
P.E.
Professor, School of Engineering, Univ. of North Florida, 1 UNF Dr., Jacksonville, FL 32224. Email: [email protected]

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  • Uncovering the Spatiotemporal Patterns of Regional and Local Driver Sources in a Freeway Network, Sustainability, 10.3390/su16083344, 16, 8, (3344), (2024).

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