A BI-LEVEL FRAMEWORK FOR PRICING OF HIGH-OCCUPANCY TOLL LANES

Abstract

As a freeway operational management strategy, High-Occupancy Toll (HOT) lanes have been deployed to manage the demand for High-Occupancy Vehicle (HOV) lanes by adjusting the tolls. By doing so, the capacity of freeways with such lanes can be used more efficiently. Periodically, setting the right amount of toll in accordance with the time-varying demand is a key to successful operation of HOT lanes; however, this is often difficult because travellers have heterogeneous willingness to pay for the toll and traffic conditions vary as the demand changes due to the imposition of tolls. This paper proposed an algorithm to determine the optimal level of toll for minimizing the total delay collectively spent by both HOVs and low-occupancy vehicles. Based on real-world traffic and survey data obtained from Gyungbu expressway in South Korea, a case study is presented to verify the applicability of the developed algorithm. The results from the case study show that the proactive dynamic pricing scheme can use the underutilized capacity of HOT lane efficiently and, thereby, shorten total travel time by 22% and generate revenue of more than $8600. Some limitations and future research agendas are also discussed.