Exploration of Corridor-Based Tolling Strategies for Virginia’s Express Toll Lanes

Report No: 22-R5

Published in 2021

About the report:

Virginia has invested significant resources in the development of express toll lanes (ETLs), which adjust toll rates dynamically based on the level of toll lane usage. A tool is needed to investigate the potential impact of the I-66 Outside-the-Beltway (OTB) ETLs on regional traffic patterns. This study developed a microscopic traffic simulation model in TransModeler to evaluate a set of corridor-based tolling strategies for the I-66 ETLs in NOVA. This model also considered the changes in vehicle occupancy, mode split, and departure time among travelers because of tolls based on locally collected data. An interactive map-based analyzer based on the simulation results was created to support quick scenario analysis and decision-making.

I-66 OTB ETLs are estimated to bring tangible travel time improvements to the entire corridor. The simulation model showed that, compared to traffic conditions before the opening of theI-66 OTB ETLs, eastbound travel time along the general purpose lanes improved during the morning peak period by as much as 36.1% for the segment between Gainesville and Rt. 28, and 13.2% for the segment between Rt. 28 and I-495, respectively. During the afternoon peak period, Westbound travel time improved by as much as17% for the segment between I-495 and Rt. 28, and 7.4% between Rt. 28 and Gainesville, respectively.

The simulation model showed that the I-66 OTB ETLs would serve about 6,645 and 8,774 vehicles at a point right before the interchange with I-495, during the morning peak and the afternoon peak periods, respectively. When combined with the traffic on the general purpose lanes, the total throughputs increased to 30,783 (+6.8%) and 35,914(+5.1%) vehicles, compared to the current throughputs of about 28,813 and34,160 vehicles respectively during each peak period. The simulation model also showed that US 29 and US 50 do not serve as good alternatives for trips along I-66 OTB. The introduction of the ETLs created less than a 5% impact on the overall traffic volumes along the arterial roads.

The choice of a dynamic pricing algorithm affected the number of ETL users and played a critical role in maintaining sufficient levels of service for the ETLs. Other factors, such as the value of time distribution, the vehicle occupancy requirement for free access, and the overall travel demand also have a significant impact on ETL usage and corridor traffic patterns. Among all the single factor scenarios, the policy of tolling only single occupant vehicles (HOT2+) instead of vehicles with one or two occupants (HOT3+) has the most significant impact on the performance of the corridor.

The models developed in this study also have some limitations, such as the limited quantity of data for model calibration, the small number of scenarios tested, and uncertainties that may not be fully considered at this point (e.g., COVID-19). Users should use these results with an appropriate understanding of the caveats. With these constraints considered, this study does provide a proactive assessment of the potential impact of the I-66 OTB ETLs under different scenarios, which can provide information to VDOT stakeholders for future decisions. The value of time, the vehicle occupancy, and the mode switch models estimated in this study can be applied in other studies in the region when no better data sources are available.

Disclaimer Statement:The contents of this report reflect the views of the author(s), who is 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 Virginia Department of Transportation, the Commonwealth Transportation Board, or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. Any inclusion of manufacturer names, trade names, or trademarks is for identification purposes only and is not to be considered an endorsement.


  • Shanjiang Zhu, Ph.D., Mecit Cetin, Ph.D., Hong Yang, Ph.D., Olcay Sahin, Atabak Mardan

Last updated: November 7, 2023

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