Developing a Mode Choice Model for Small and MediumMPOs

This project developed a process and framework for generating the inputs needed for estimating a travel mode choice model that includes the transit mode, and developing a framework for implementing the results of an estimated travel mode choice model to project mode shares in response to demographic changes and improvements in transit service. In generating inputs for estimating a mode choice model, an important component is network skims (travel times and costs) by alternative modes. Most metropolitan planning organizations (MPOs) have good geographic information systems (GIS)-based representations of the highway network, which can be used to generate drive-alone and shared-ride skims. However, this is not the case with transit skims due to the lack of a good GIS-based representation of the transit network, especially for bus stops. The project manually geo-coded bus stop information onto the highway network, and used assumptions to generate transit paths and corresponding zone-to-zone transit skims. A guidebook provides a step-by-step procedure for developing skims. The database for estimation was developed using household survey data (2004) on trip characteristics. Two demographic variables were used in the mode choice model: household size and income. The models have been embedded into a software forecasting platform to predict modal share shifts between each pair of traffic analysis zones (TAZs) (and the region as a whole) due to changes in income levels and/or household size over time. The models can also be used to assess the impacts of transit improvements for in-vehicle and out-of-vehicle transit times. Further data collection from transit surveys is recommended to enhance the model’s capacity to estimate the time and cost effects based on preferences. A georeferenced coordinate system for bus stop locations would also improve the transit skim generation process.