This study pools household travel and built environment data from 15 diverse US regions to produce travel models with more external validity than any to date. It uses a large number of consistently defined built environmental variables to predict five household travel outcomes – car trips, walk trips, bike trips, transit trips and vehicle miles travelled (VMT). It employs multilevel modelling to account for the dependence of households in the same region on shared regional characteristics and estimates ‘hurdle’ models to account for the excess number of zero values in the distributions of dependent variables such as household transit trips. It tests built environment variables for three different buffer widths around household locations to see which scale best explains travel behaviour. The resulting models are appropriate for post-processing outputs of conventional travel demand models, and for sketch planning applications in traffic impact analysis, climate action planning and health impact assessment.

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The mixed-use development (MXD) trip generation model provides a mechanism for estimating vehicle, walking, and transit trips for an MXD. The model applies trip modifications to standard single-use trip generation estimates developed by ITE. MXDs with diverse internal activities have been shown to capture internal trips at a rate higher than conventional suburban developments; therefore, the MXD trip generation model accounts for the internal capture of MXD sites by reducing the external trips produced and estimating the number of walking and transit trips that would typically be conducted by automobile. In addition, MXDs in central areas have been shown to generate shorter vehicle trips, and this factor has been taken into account in the model, as internal and external vehicle miles traveled (VMT) are estimated on the basis of published travel characteristics of MXDs. The MXD trip generation model provides a straightforward method of testing transportation-related metrics of MXDs. The model uses ratios from a leading research-based MXD model to reduce ITE vehicle trip estimates and presents a summary of results that show the effects on VMT, internal capture, and mode split as a result of enhanced activity density and diversity of land uses within the MXD. The MXD trip reductions are based on a methodology that analyzed data sets for 239 MXDs in six large and diverse metropolitan regions. Benefits of locally calibrated characteristics on vehicle ownership are also included in the mode split of the trip estimates of the MXD trip generation model.

Current methods of traffic impact analysis, which rely on rates and adjustments from ITE, are believed to understate the traffic benefits of mixed-use developments (MXDs) and therefore to lead to higher exactions and development fees than necessary and to discourage otherwise desirable developments. The purpose of this study was to improve methodology for predicting the traffic impacts of MXDs. Standard protocols were used to identify and generate data sets for MXDs in 13 large and diverse metropolitan regions. Data from household travel surveys and geographic information system databases were pooled for these MXDs, and travel and built-environment variables were consistently defined across regions. Hierarchical modeling was used to estimate models for internal capture of trips within MXDs and for walking, biking, and transit use on external trips. MXDs with diverse activities on site were shown to capture a large share of trips internally, so that the traffic impacts of the MXDs were reduced relative to conventional suburban developments. Smaller MXDs in walkable areas with good transit access generated significant shares of walk, bike, and transit trips and thus also mitigated traffic impacts.