Adoption of FasTrak on San Francisco Bay Area Bridges: Impact of Operations Research Models in Relieving Congestion

Ramesh Bollapragada (), Venoo Kakar, John Goodwin () and Andrew Fremier ()
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Ramesh Bollapragada: College of Business, San Francisco State University, San Francisco, California 94132
John Goodwin: Metropolitan Transportation Commission, Metro Center, Oakland, California 94607
Andrew Fremier: Metropolitan Transportation Commission, Metro Center, Oakland, California 94607

Interfaces, 2023, vol. 53, issue 2, 97-110

Abstract: Bay Area toll bridges are the main transportation link across the nine-county San Francisco Bay Area. These bridges experience extreme congestion and become bottlenecks during peak hours with long backups at the toll plazas. A solution to ensure smooth vehicle throughput at toll plazas is the widespread adoption of the electronic toll collection system called FasTrak. However, the FasTrak system has experienced low usage rates since its inception relative to other toll collection systems in the country. Forecasting, marketing, and operations research models were utilized to make recommendations and collaborate with transportation authorities to increase FasTrak usage during peak hours (5–10 a.m. and 3–7 p.m.) to address traffic congestion. After these recommendations were implemented, FasTrak usage increased from 40% in 2006 to the long-term target of 70% by 2016. This paper presents a synthesis of the challenges and the implementation of the FasTrak Strategic Plan. Furthermore, econometric models are presented that capture the effect on traffic volumes of increased FasTrak usage achieved through congestion pricing. Saved travel time resulted in productivity gains of approximately $569 million per year. This study contributes to an understanding of the role of effective transportation policies in reducing congestion and improving productivity.

Keywords: congestion pricing; FasTrak; electronic toll collection; transportation; forecasting (search for similar items in EconPapers)
Date: 2023
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