This research examines a new methodology for prospectively estimating the willingness of travelers to use a toll road by combining travel time saved with the income of the prospective customer base. The purpose of the research is to facilitate network level planning by allowing some reasonable predictions of acceptable toll rates using readily available data and estimation techniques. Methods of estimating user benefit resulted in simulated distributions of value of user time. Values of time are linked to census tract income data for the user population to produce value of time as a percent of income as an indicator, which is hypothesized to be a more useful indicator of the travel market than conventional indicators. Techniques for estimating the travelshed of a toll road are examined. Results show that considering value of time as a percentage of census tract median income provides an improved portrayal of the toll road market, as usage of the toll road increases with increasing income. Using census tract median income as the income parameter has shortcomings, in that it produces anomalous results at very low population levels. Of the two methods of estimating the travelshed, the visual estimation approach was not satisfactory, leaving the analyst to use select link analyses instead.

High Occupancy Toll (HOT) lanes that use dynamic pricing to manage congestion and generate revenue are increasingly popular. In this paper, we estimate the behavioral response of drivers to dynamic pricing in an HOT lane. The challenge in estimation lies in the simultaneity of price and demand: the structure of dynamic tolling ensures that prices increase as more drivers enter the HOT lane. Prior research has found that higher prices in HOT lanes increase usage. We find that after controlling for simultaneity HOT drivers instead respond to tolls in a manner consistent with economic theory. The average response to a 10 percent increase in the toll is a 1.6 percent reduction in usage. Drivers primarily value travel reliability over time savings, although there is heterogeneity in the relative values of time and reliability based on time of day and destination to or from work. The results highlight the importance of both controlling for simultaneity when estimating demand for dynamically priced toll roads and treating HOT lanes with dynamic prices as a differentiated product with bundled attributes.

This monograph presents a simple, innovative approach for the measurement and short-term prediction of highway travel times based on the fusion of inductive loop detector and toll ticket data. The methodology is generic and not technologically captive, allowing it to be easily generalized for other equivalent types of data. The book shows how Bayesian analysis can be used to obtain fused estimates that are more reliable than the original inputs, overcoming some of the drawbacks of travel-time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) from the available data, without recurrent and costly requirements for additional data. The application of the algorithms to empirical testing in the AP-7 toll highway in Barcelona proves that it is possible to develop an accurate real-time, travel-time information system on closed-toll highways with the existing surveillance equipment, suggesting that highway operators might provide their customers with such an added value with little additional investment in technology.

This research examines a new methodology for prospectively estimating the willingness of travelers to use a toll road by combining travel time saved with the income of the prospective customer base. The purpose of the research is to facilitate network level planning by allowing some reasonable predictions of acceptable toll rates from readily available data and estimation techniques. Methods of estimating user benefit resulted in simulated distributions of value of user time. Values of time are linked to census tract income data for the user population to produce value of time as a percentage of income as an indicator. As relevant literature acknowledges the tendency toward increased toll road usage at higher income levels, it is hypothesized that linking estimates of value of time directly to household income would produce a more useful indicator of the travel market than do conventional indicators. Techniques for prospectively estimating the travelshed of a toll road are compared with the actual travelshed, as reflected in user home census tracts, as a means of evaluating the efficacy of those techniques in estimating the market area of a prospective toll road. Results show that considering value of time as a percentage of census tract median income provides an improved portrayal of the toll road market, as usage of the toll road increases with increasing income. Using census tract median income as the income parameter has shortcomings, in that it produces anomalous results at very low population levels. Of the two methods of estimating the travelshed, the visual estimation approach was not satisfactory, leaving the analyst to use select link analyses instead.

Road pricing (tolls, etc.) as a means of generating revenue for infrastructure investment has become a major policy option in both Europe and North America. It can also be used as a policy in the management of traffic demand and flow, environmental objectives, and optimal resource allocation as regards the size of investments. Road pricing is assumed to be able to solve many problems simultaneously -- congestion control, pollution reduction, and investment financing. This volume assembles and assesses theoretical knowledge, empirical results and experiences of actual road pricing. In addition, the impact of new information technology on future policy formulation is considered.