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Innovative Methods for Pricing Studies Arun R. Kuppam, Cambridge Systematics, Inc. Maren L. Outwater, Cambridge Systematics, Inc. Rob C. Hranac, Cambridge Systematics, Inc. I n a recent forum on road pricing (1), attendees dis- number of issues that present challenges, including how cussed limitations with current travel demand fore- to distribute values of time: casting approaches for pricing studies. In addition, Cambridge Systematics, Inc. (CS) recently completed a Across individual travelers (i.e., with different paper on the limitations of studies used to advance toll income levels); projects (2) and on the opinions of Washington State's Across different trips (i.e., with different purposes community leaders (3). Based on these sources and and modes); recent experience in developing forecasting models for Across different destinations (i.e., trips to the air- toll projects, the authors have identified the following port); issues as important to improving existing travel models Across different vehicle types (i.e., with different for pricing studies: inaccurate values of time for specific vehicle classes); travelers, trip purposes, modes, and time periods; and Based on the types of goods being carried for truck lack of temporal detail and behavioral choice for time- trips; and of-day models. For different types of congestion (i.e., recurring and CS's approach to advance travel models for pricing nonrecurring congestion, such as accidents). studies focuses on these issues as the most critical to be addressed in existing models. The authors have been In a disaggregate travel demand forecasting system, involved in the development and application of these these values of time could be set based on the traveler, the methods for trip-based models in Minnesota and Wash- trip, the vehicle type, and the goods being carried and ington, as well as for activity-based models in San Fran- could remain consistent throughout the forecasting cisco. The remainder of this paper describes innovative process, eliminating the application-related issues sur- methods to incorporate advances to address these issues. rounding the values of time. At this time, most travel In addition, the authors describe strategies to optimize demand forecasting models are aggregate trip-based mod- tolls for pricing studies. Finally, more research is proposed els, which makes the distribution of values of time for indi- to address additional limitations of existing models. vidual travelers, trips, and vehicles impossible. For these models, the only solution is to identify specific categories of travelers, trips, and vehicles and apply values of time VALUES OF TIME for these categories. This is an effective means of distrib- uting values of time within the forecasting system. The estimation and application of the value of time in However, these trip-based modeling systems do not travel demand forecasting models is the most often cited necessarily contain the same market segmentation problem for evaluating pricing projects. There are a throughout the system (i.e., to assess values of time by 142