Now Available: SHRP 2 C04 Improving Our Understanding of How Highway Congestion and Pricing Affect Travel Demand

SHRP 2 C04 Improving Our Understanding of How Highway Congestion and Pricing Affect Travel Demand

Prepared by: Parsons Brinckerhoff for SHRP-2

SHRP-2 C04
SHRP-2 C04 Improving Our Understanding of How Highway Congestion and Price Affect Travel Demand

American motorists experience more hours of congested conditions every year, but planning models rely on relatively thin behavioral information to take congestion into account. Highway operations and road pricing strategies are being employed to address congestion, but the planning process is not well equipped to describe the effective capacity available when roads are congested or to describe the relief obtained by improvement strategies. Variable tolls are being considered to encourage motorists to shift travel time out of congested periods, to use less congested roads, or to change mode. Current travel models are not capable of simulating all of the factors needed to calculate the effect of tolls on congestion because they do not include disaggregated models of choice behavior for a range of users under various choice conditions. A disaggregate approach is required that deals directly with the decisions faced by individuals rather than large groups of people.

The objective of this project was to develop mathematical descriptions of the full range of highway user behavioral responses to congestion, travel time reliability, and pricing. This included formatting the mathematical descriptions of behavior so that they could be incorporated into various travel demand modeling systems in use or being developed. Another objective was to examine network assignment practices needed to support models that simulate behavioral responses to congestion, travel time reliability, and pricing.

Over the past 30 years, research has advanced the understanding and prediction of travelers’ behavior choices in response to changes in traffic congestion and changes in the price of travel. This project synthesized that research to select the important and well-founded behavioral hypotheses, and it tested those hypotheses statistically on the most suitable data sets available in the United States. The project identified the most important contextual influences on behavioral sensitivity to highway congestion and pricing, and it provided guidance on the relative magnitude of those influences. Travel demand modeling studies are typically limited in scope and time frame, and they are usually tied to a single survey data set. This project had the unique opportunity to carry out a comprehensive series of hypotheses tests on data sets that were available from multiple areas across the United States.

The Final Report can be accessed here.


Now Available: NCHRP 08-57 Assessing Highway Tolling and Pricing Options and Impacts

NCHRP 08-57 Assessing Highway Tolling and Pricing Options and Impacts

Prepared by: Parsons Brinckerhoff for NCHRP

NCHRP 08-57
NCHRP 08-57 Assessing Highway Tolling and Pricing Options and Impacts

With continuing growth in travel demand, worsening congestion, and shortages of funding available for increasing highway capacity, state departments of transportation (DOTs), metropolitan planning organizations (MPOs), and other transportation agencies are considering pricing strategies such as user-based fees or tolling as options for generating transportation revenue and for managing transportation system performance. Although a number of DOTs have initiated projects that rely on pricing as an alternative to traditional funding sources, policy makers and planners need a framework for better decisions on pricing: When to price? What to price? How to price? They also need a framework for fully understanding the potential impacts of these major projects on the performance of the entire transportation system. While pricing strategies can provide new sources of revenue to fund expanded transportation capacity, they clearly will also have impacts on travel demand and congestion. As such, there are questions to be answered regarding who pays for such improvements, who will use these facilities, and how these facilities will be operated to improve the overall performance of the transportation system. Pricing decisions must be based on accurate, reliable, and credible forecasts of their impacts on travel behavior and the revenue to be generated from the tolled facilities. Additionally, of equal importance, planners and decision makers need a broad framework that can effectively inform their consideration of pricing options in terms of their policy implications, performance expectations, and financial impacts.

Decision makers in both the public and private sectors of the transportation industry need a better understanding of pricing. The public’s knowledge and awareness of pricing issues are limited, and this places a greater burden on policy makers and planners to provide reliable and credible information. Traditional methods and analytical tools for transportation decision making, such as risk analysis, benefit-cost and other economic analysis, financial analysis, market research, and travel-demand forecasting fall short in addressing the complexities associated with pricing decision making. In order for pricing proposals to be fully and accurately evaluated and planned, these methods and analytical tools need to be applied consistently within a rational decision-making framework. In addition, there is a need for improvements to existing methods and analytical tools to resolve issues such as public acceptance, unique private sector involvement, and economic and social issues while supporting current and future pricing decisions.

This research project developed a decision-making framework that includes descriptions and evaluation of methods and analytical tools for establishing pricing policies and practices and for predicting their impacts on travel behavior and congestion. Gaps are identified, and improved methods and analytical tools are developed to fill those gaps. Improvements for travel-demand forecasting methods employed to support pricing decisions for new capacity and congestion management are provided. The results are presented two volumes: the first containing the decision-making framework and the second focusing on improvements to travel-demand forecasting methods and analytical tools.

Volume 1, Decision-Making Framework, is available HERE.

Volume 2, Travel Demand and Forecasting Tools, is available HERE