Market-Based Framework for Forecasting Parking Cost in Traditional and Microsimulation Modeling Applications

Abstract

Parking cost is an important variable in determining mode choice, yet it receives little attention in most travel forecasting models. This paper presents a framework for modeling parking supply and cost that has three advantages over most parking cost models: a market-based approach is used to equilibrate parking demand with parking supply; actual parking costs paid by groups of travelers rather than average parking costs are estimated for each transportation analysis zone; and estimates are made from longitudinal data. This framework has been applied successfully in a traditional four-step travel model and is being used in practice. It also provides additional opportunities for application in a segmented manner or in concert with a microsimulation modeling approach. Mode choice results based on aggregate and segmented applications of the framework are substantially different. Improved forecasting of parking costs should be an important consideration in any new model development. In recent years, substantial efforts have been focused on household interactions and activity modeling. Although the understanding of travel behavior has improved substantially, the improved techniques still depend on good input data for credible forecasts.