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A Dynamic Congestion Pricing Strategy for High-Occupancy Toll Lanes

Abstract

High Occupancy Toll (HOT) lanes are emerging as a solution to address the underutilization of High Occupancy Vehicle (HOV) lanes and also means of generating revenue for state department of transportation. This paper proposes a method for dynamically determining the HOT toll price in response to the changes in traffic condition and documents procedures for estimating parameters needed for the proposed pricing strategies: revenue maximization and delay minimization. The proposed strategies have been applied to 14-miles of freeway segment in the San Francisco Bay Area, and the findings show that utilizing all the available HOV lane capacity (i.e. difference between HOV lane capacity and HOV demand) to serve the HOT demand does not result in maximizing the total revenue. There exists optimal level of HOV lane capacity that can be allowed for the use of HOT vehicle to maximize the revenue.

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