Although considerable research has been done on the well-established relationship between smart growth and daily travel demand, research on travel effects by trip purpose or by time of day is much more limited. This creates a challenge for estimating the effects of smart growth development patterns and transportation management on peak period traffic conditions and congestion. For smart growth to be a component of regional congestion relief, transportation planners need to understand what types of smart growth development work and in what types of environments, as well as how best to link the development strategies to specific transportation solutions. Under SHRP 2 Project C16, a research team led by Maren Outwater of Resource Systems Group conducted an extensive review of existing research to understand the dynamics and interrelationships of smart growth policies with the performance of transportation investment. The research focused on five topics: (1) the built environment impact on peak automobile demand, (2) mobility by mode and purpose, (3) induced traffic and induced growth, (4) the relationship between smart growth and congestion, and (5) smart growth and freight. This synthesis of existing research documented well-established relationships and identified gaps in the research. During the next phase of the research, the research team developed a software tool to help decision makers of transportation and land use policies conduct scenario planning of smart growth policies and determine their impact on regional travel demand. The scenario-planning tool, initially called Smart Growth Area Planning (SmartGAP) and recently renamed the Rapid Policy Assessment Tool (RPAT), estimates smart growth’s effect on both peak and nonpeak travel, as well as its effects on sprawl, energy reduction, active travel, and carbon footprints. The SmartGAP tool measures the travel demand impacts of smart growth policies through robust modelling of individual households and firms in a metropolitan region. All of the input data can be developed from nationally available data sets that are provided with the application. Users also have the option of replacing these data with local data sources. The tool is easier and faster to use than traditional planning models and is therefore useful for quickly evaluating scenarios of growth, pricing, and other demand management strategies. SmartGAP is free and open sourced. To test the usefulness and reasonableness of the SmartGAP tool, three planning agencies conducted test implementations of the software. The agencies included a small metropolitan planning organization, a large metropolitan planning organization, and a state department of transportation. The pilot tests provided valuable feedback to improve the software and the accompanying user’s guide. (Author/publisher)
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