The determination of the feasibility of an Express Lanes project and evaluation of alternatives for the Express Lanes requires a travel demand forecasting tool that is capable of assessing the impact of tolling on traffic volumes and patterns. Depending on the complexity of the project or the phases in the project development process, a simple spreadsheet application may suffice. However, in most cases, a comprehensive travel demand model is needed to forecast the level of demand for the Express Lanes facility, the impacts of pricing on corridor and regional travel, and the impacts of tolling on different groups of travelers.
Desirable Features for Travel Demand Models
The demand to use Express Lanes is affected by a number of factors. Traveler’s sociodemographic characteristics, the trip origin and destination and associated highway network configurations, trip length, actual and perceived travel time savings, travel time reliability, and most importantly, the travelers’ Value of Travel Time Savings (VTTS) for the benefits of using the Express Lanes all affect the existing and future travel demand for Express Lanes. How well a travel forecasting model predicts demand for an Express Lanes facility depends on whether the model is structured to capture these factors that influence the travel demand, how well it is calibrated and validated to reflect existing conditions if an Express Lanes facility already exists in the region, and how it is applied to quantify the uncertainty in the future. When evaluating a travel demand model for Express Lanes, the following features are desirable:
- Time-of-Day – the model produces travel demand by different times of a day and allows changing the time of travel in response to variable toll amounts.
- Route Choice – model assigns traffic to general use lanes and the Express Lanes explicitly based on varying toll amounts.
- Mode Choice – mode choice structure allows formation or dissolution of carpools in response to toll policies or switching to or from competitive transit modes.
- Travel Cost – accurate representation of the cost of using Express Lanes.
- Value of Travel Time Savings (VTTS) – VTTS is the implied toll value that travelers would be willing to pay for a given savings in travel time.
- Value of Reliability (VOR) – VOR is the implied toll a traveler would pay to reduce the variability of a trip’s travel time.
Many of the advanced travel demand models in Florida already include some or all of these features. However, having these features alone is not sufficient to use the model for an Express Lanes project. The underlying assumptions used in the model should be identified, and sensitivity analyses may be needed to examine how changes in key assumptions would affect the results of traffic modeling.
Data Used in Express Lanes Modeling
Travel demand models used for Express Lanes also use data from regional household travel surveys, Census population estimates and employment projections, origin-destination surveys, and traffic counts. A critical parameter for forecasting Express Lanes demand is the VTTS for the travel population. If Express Lanes facilities already exist in an area, the VTTS can be obtained by collecting traffic volumes, travel times, toll rates, and travel behavior data from travelers using the Express Lanes facilities. However, in areas where such facilities do not exist, stated preference surveys can be conducted to gather information about potential users of the new facility. Stated preference surveys attempt to elicit VTTS information by asking travelers to state the travel choices they would make when given a set of hypothetical scenarios. Under carefully constructed experimental designs and data analysis techniques, these surveys provide information on VTTS that can be used in a travel demand model. If a stated preference survey cannot be conducted for the study area, similar surveys from other areas could also be considered after a careful evaluation of the socioeconomic and travel characteristics determines substantial similarities with the project area.