Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
1The Smart Growth Network, a partnership of the U.S. Environmental Protection Agency and other government and business and environmental organizations, defines smart growth in terms of 10 basic principles: 1. Provide mixed land uses. 2. Take advantage of compact building design. 3. Create a range of housing opportunities and choices. 4. Create walkable neighborhoods. 5. Foster distinctive, attractive communities with a strong sense of place. 6. Preserve open space, farmland, natural beauty, and critical environmental areas. 7. Strengthen and direct development toward existing communities. 8. Provide a variety of transportation choices. 9. Make development decisions predictable, fair, and cost-effective. 10. Encourage community and stakeholder collaboration in development decisions. These characteristics of the urban form and built environment are generally associated with a variety of benefits to environmental protection, public health, and quality of life and economic and social benefits. One of the better-established benefits of smart growth is the reduction in unnecessary travel, the resulting reductions in impacts on congestion and delay and their costs to business and households, and reduced infrastructure expansion, energy consumption, and greenhouse gas and other emissions. Comparisons of travel data among regions of different urban forms, among communities within those regions, and among development areas within those communities all demonstrate that smart growth development vehicle travel rates are lower than rates in conventional suburban forms. The comparisons show that the extent of reduction is proportional to the degree to which the development is compact, diverse, location-efficient, served with a variety of transportation choices, and endowed with a sense of place. Overview of the Project The second Strategic Highway Research Program (SHRP 2) was authorized by Congress to address some of the most pressing needs related to the nationâs highway system. SHRP 2 addresses four strategic focus areas: the role of human behavior in highway safety (Safety); rapid highway renewal (Renewal); congestion reduction through improved travel time reliability (Reliability); and transportation planning that better integrates community, economic, and environmental considerations into new highway capacity (Capacity). The goal of SHRP 2 Capacity Project C16 was to understand and evaluate the effect of smart growth policies on travel demand. Executive Summary
2While there is an abundance of literature on the connection between transportation and land use and the impact of various smart growth strategies on travel demand, there is a lack of practi- cal guidance and tools for translating these insights at key decision points in planning and proj- ect development. Project C16 will help practitioners to understand how smart growth impacts travel demand in two ways: first, through a synthesis of the research, and, second, through a user-friendly software tool that can be used to evaluate the impact of smart growth policies on travel demand. The products of this research relied on existing information and resources. These products will be available through the Transportation for CommunitiesâAdvancing Projects through Partnerships (TCAPP) website, which is the online delivery source for most Capacity research in SHRP 2. (TCAPP was recently renamed PlanWorks.) It provides a systematic approach for reaching collaborative decisions and identifies key decision points in transportation decision making. Background Research The background research sought to identify direct experience by practitioners and academics in the area of how smart growth policies affect travel demand. The work by practitioners was obtained through a series of interviews with directors, administrators, principal and senior transportation planners and engineers, and technical specialists and by reviewing published work by both practitioners and academics. The interviews provided an indication of informa- tion needs for metropolitan planning organizations (MPOs) and state departments of transpor- tation agencies. Most agencies were interested in scenario planning as a strategy for evaluating smart growth, to allow for the testing of many higher-level scenarios across a broad range of issues with a quick turnaround. Many agencies also identified the need for coordination, coop- eration, and communication between regional and state transportation agencies and local land use agencies on land use policy, since land use regulations are controlled by local governments. The synthesis of existing research covered five topics, as shown in Table ES.1. This research allowed for the summarization of the well-established relationships and the gaps in research. The well-established relationships are drawn primarily from studies where these impacts were observed, and the gaps in the research are found in impacts that are reflected in other parts of the system (such as regional effects of congestion) or in other aspects of travel (such as peak demand or work trips) that are not directly observable. Background research also included a synthesis of performance metrics and analytical tools that are used to evaluate the impact of smart growth policies on travel demand. Performance Table ES.1. Summary of Background Research Topic Well-Established Relationships Gaps in Research Built environment impact on peak auto demand Impact on daily travel Impact by time of day Mobility by mode and purpose Impact on daily travel Impact by trip purpose Induced traffic and induced growth Capacity expansion on an expanded facility Route shifts, time-of-day shifts, mode shifts, induced trips, new destinations, growth shifts on the network; effects of operational improve- ments, land use plans Relationship between smart growth and congestion Localized effects Macro-level or regional effects Relationship between smart growth and freight Freight is necessary for population centers Impacts of loading docks, truck routing, full-cost pricing, freight facilities and crossings, interfirm cooperation, stakeholder communication
3 metrics were summarized at three levels: transportation-specific metrics, metrics that indicate the effectiveness of the regional and local integration of transportation and land use, and higher- level metrics that capture the effects of land use and transportation decisions on a âtriple bottom lineâ of economic, environmental, and societal impact. These metrics provided a starting point for the development of performance metrics to be included in this work. Three types of analytical tools were evaluated in this research phase: 1. Simple spreadsheets to address a subset of planning factors and performance measures; 2. Sophisticated geographic information system (GIS) tools that allow scenario planning at the land use parcel level and produce a large variety of performance indicators; and 3. Travel demand and land use forecasting models developed by MPOs that are sometimes supplemented with a visual interface dashboard for presenting smart growth results. These tools vary by the level of detail, level of sophistication, scale (micro/project level, meso/ corridor level, and macro/regional), and performance metrics they can produce. Smart Growth Area Planning (SmartGAP) The Smart Growth Area Planning (SmartGAP) tool was developed for regional decision makers of transportation and land use policies to conduct scenario planning of smart growth policies and determine their impact on travel demand. This tool was designed to address as many of the limitations identified in the research as possible and to provide a tool that filled a gap in the set of available tools. SmartGAP evaluates regional scenarios based on changes in the built environ- ment, travel demand, transportation supply, and transportation policies being considered. SmartGAP is a robust statistical package that tracks the characteristics of individual households and firms in a region and determines the travel demand from these characteristics. The relation- ships in the SmartGAP tool were based on the background research conducted for the project. The built environment is defined as a set of 13 place types, as shown in Figure ES.1. SmartGAP evaluates a series of performance metrics resulting from smart growth scenarios: community impacts, travel impacts, environmental and energy impacts, financial and eco- nomic impacts, and location impacts. These metrics provide a rich assessment of each scenario at a regional scale. SmartGAP is designed to operate at a regional scale and is flexible in how the place types are applied in each region. All of the input data can be developed from available Figure ES.1. Place types for households and firms in SmartGAP.
4data sources, and these are provided with the application. If a regional agency has local data, these data can be used in place of the available data in the system. The software was developed by using R, an open source statistical package to allow for wide distribution. SmartGAP has a graphical user interface (GUI) with a user-friendly set of menus and tabs as shown in Figure ES.2. Pilot Tests To test the usefulness and reasonableness of the SmartGAP tool, three planning agencies and the Resource Systems Group, Inc. (RSG), conducted test implementations of the software: ⢠Atlanta, Georgia, Regional Commission (ARC) conducted a large MPO test. ⢠Thurston Regional Planning Council (TRPC) in Washington State conducted a small MPO test. ⢠The Maryland Department of Transportation (the Maryland DOT) conducted a larger urban/ suburban county and a smaller rural county test. ⢠RSG conducted a test in the Portland, Oregon, metropolitan region. Each test consisted of eight standard scenarios so that it was possible to compare across regions and to understand the usability of the software, the complexity of developing input data, the usefulness of the performance metrics, and the reasonableness of the results. There are many Figure ES.2. SmartGAP graphical user interface.
5 other scenarios that can be tested, by adjusting any of the data or policy inputs. The planning agencies provided valuable feedback to improve the software and userâs guide: ⢠Performance metrics were consistent with expectations. ⢠Installation and input file preparation were easy. ⢠Regional policy scenario testing is useful for smaller MPOs without advanced travel demand models and for prescreening policy scenarios in larger MPOs with advanced travel demand models. ⢠Run times were reasonable. The research and software developed in this project offers a useful and effective means to better understand the impact of smart growth policies on travel demand. During the course of the project, there were some suggestions for longer-term enhancements to SmartGAP that may be considered to provide additional capabilities and sensitivities but were not possible within the time and resources of the current work. These suggestions provide a road map for future versions of SmartGAP. Products In summary, the major results of the project offer two products to facilitate improved communica- tion, interaction, and partnerships between decision makers and planners in both the transportation and land use arenas: ⢠A decision support software tool for regional and local planners to use for testing smart growth scenarios and evaluating their impact on travel demand. ⢠Online resources to help people understand the dynamics and interrelationships of smart growth strategies, with the performance of a transportation investment as background and as a supplement to the software tool. These resources can bridge the gap between regional planning visioning exercises and trans- portation plans in relation to the evaluation of smart growth strategies. This bridging will help allow state, regional, and local agencies to engage in the evaluation of smart growth strategies quickly and easily so that promising smart growth strategies can be identified and pursued in the land use and transportation planning processes. It can also supplement more sophisticated mod- eling efforts, which can be used to evaluate specific smart growth projects. SmartGAP is designed to be accessible to land use and transportation planners with no modeling experience.
