What Drives Single Occupant Traveler Decisions in HOT Lanes? An Investigation Using Archived Traffic and Tolling Data from the MnPASS Express Lanes

High-occupancy toll (HOT) lanes are in operation, under construction, and planned for in several major metropolitan areas. The premise behind HOT lanes is to allow single occupant vehicles (SOVs) to access high occupancy vehicle (HOV) lanes (and, a higher level of service) if they are willing to pay a toll. To maintain a high level of service in the HOT lanes, the toll rate is set dynamically to restrict the number of SOVs which access the facility as it nears capacity. Thus, HOT facilities provide operators of transportation systems with a new operations tool: pricing. In order to effectively use pricing, it is critical to understand driver behavior when faced with a set of traffic conditions and toll levels. This paper presents the results of an empirical investigation into the relationship between toll rate, traffic conditions, and SOV driver behavior, based on data from the dynamically-tolled I-394 HOT facility in Minneapolis, Minnesota. Analysis of the empirical data indicated that a large percentage of SOV drivers use the HOT lanes at different, yet predictable rates throughout the AM peak period, even when there is no clear travel time advantage. After accounting for these “regular” users, the remaining SOV drivers utilize the HOT lanes at greater rates when the cost per hour of commute time saved is lowest. A model was developed that incorporates both of these findings, predicting HOT lane usage rates based on time savings, time of day, and toll rates with an R2 value of 0.684.

Choice of High Occupancy/Toll Lanes under Alternative Pricing Strategies

High occupancy/toll (HOT) lanes typically vary tolls charged to single occupant vehicles, with the toll increasing during congested periods. The toll is usually tied to time of day or to the density of vehicles in the HOT lane. The purpose of raising the toll with congestion is to discourage demand sufficiently to maintain travel speeds in the HOT lane. However, it has been demonstrated that the HOT toll may act as a signal of downstream congestion (in both general purpose (GP) and HOT lanes), causing an increase in demand for the HOT lane, at least at lower prices. This paper develops a model of lane choice to evaluate alternative HOT lane pricing strategies, including the use of GP density, to more accurately reflect the value of the HOT lane. In addition, the paper explores the potential effect these strategies would have on the HOT lane vehicle share through a partial equilibrium analysis. This analysis demonstrates the change in demand elasticity with price, showing the point at which drivers switch from a positive to negative elasticity.

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

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.