Effect of Smart Growth Policies on Travel Demand (2013)

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6Project Objectives The overall goal of Project C16 was to provide transportation planning agencies with improved tools and methods for more accurately and comprehensively integrating transportation investment decision making with land development and growth management. To achieve this goal, there were several objectives: • Understanding the critical decision points in the transpor- tation planning process for highway capacity and assessing whether, how, and to what extent smart growth approaches to land use policies and planning may affect demand for such capacity. • Reporting on existing research to understand the dynamics and interrelationships of smart growth strategies with the performance of a transportation investment. • Building on existing applications to identify the range of features and capabilities that these tools and methods need to represent, including the performance metrics needed to assess smart growth alternatives. • Facilitating improved communication, interaction, and partnerships between decision makers and planners in both the transportation and land use arenas. There were two primary products that were developed to meet these objectives. First, a synthesis of smart growth research and existing applications designed to evaluate smart growth policies was developed. Second, a software tool that filled the planning agency needs for evaluating smart growth scenarios and was easy to use was built, thus allowing deci- sion makers and planners in the transportation and land use fields to use the same package. In addition, the software was tested by three planning agencies in a series of pilot tests. Research Approach The project provided tools, methods, and resources for trans- portation planning agencies in the United States to evaluate the effects of smart growth policies on travel demand. The project built on existing work in this field, while recognizing that this is a relatively new arena of study in transportation planning. The development of tools and online resources relied on research, performance metrics, and application tools already in use. All recommended tools and resources were reviewed by the Technical Expert Task Group (TETG) and by select MPOs and state DOTs who engaged in the project’s pilot studies. Figure 1.1 presents the overall approach to the project. The TETG is a peer review panel for this study that reviewed and guided the overall technical direction of the work. The approach involves collaboration with SHRP 2 Capacity Project C01 (A Framework for Collaborative Deci- sion Making on Additions to Highway Capacity) and integrat- ing SHRP 2 Capacity Project C07 (Products in the Collaborative Decision-making Process) teams at two points in the process, as shown in Figure 1.1. Presentations of deliverables were made to the TETG after the initial research was conducted, after the tools and online resources were developed, and after the final report was complete. Presentations were made to the SHRP 2 Technical Coordinating Committee for Capacity Research along with the C01 and C07 teams during Task 10 to present this solution for highway capacity research. In addi- tion, the C01 team was consulted to put the SmartGAP prod- ucts on the Transportation for Communities—Advancing Projects through Partnerships (TCAPP) website (soon to be the PlanWorks website). The research focused on a framework for how smart growth influences travel demand, as illustrated in Figure 1.2. This framework provides an understanding of these areas: • The built environment’s impacts on peak auto demand. Focuses on how smart growth influences peak-period demand (A→ C→D for variable-based analysis and B→C→D for case-based analysis) as shown in Figure 1.2. • Mobility by mode and purpose. Addresses the built envi- ronment’s impacts on peak auto demand for these market segments. C h A P T e R 1 Introduction

Figure 1.2. Smart growth and travel demand conceptual framework. TOD  transit-oriented development; ITS  intelligent transportation system; TDM  transportation demand management. A. Variables/Metrics Density Diversity Design Distance to Transit Destination Accessibility Development Site Demand Management Demographic • • • • • • • • s B. Cases/Project Examples Street/Neighborhood: Complete Streets Community: TOD, Neo- traditional Regional: • • • Jobs-housing balance Smart Growth C. Travel Demand Impacts Trip Rates (purpose, time of day) Modal Splits Vehicle Miles Traveled Vehicle Hours Travele • • • • d D. Outcomes Delay: Congestion Emissions (CO2, air quality) Energy Consumption • • • E. Responses Supply-side: Road expansion, Transit investments, ITS, Bicycle and pedestrian enhancements Demand-side: • • TDM, pricing 7 Figure 1.1. Overview of approach.

8• Smart Growth Area Planning Tool (SmartGAP) (Chapter 3), including background and intended users, model structure, household and firm models, urban form models, vehicle models, accessibility, travel demand, congestion and induced demand, policies and performance metrics, additional resources, and recommendations for enhancements. • Pilot tests (Chapter 4), including the Maryland DOT, ARC, TRPC, and lessons learned. • Summary (Chapter 5) of the research findings, the use of SmartGAP, and future enhancements for the software that have been identified during the process. The report also includes an extensive list of references identi- fied throughout the project and two technical appendices: • Performance Metrics and Tools (Appendix A) provides more detail from the background research. • SmartGAP Documentation (Appendix B) provides more detail on the individual models in SmartGAP to support Chapter 3. In addition, a user’s guide has been developed for SmartGAP as a separate document to provide users with information on installation and use of the software. It is available at www.trb .org/main/blurbs/168842.aspx. • Induced traffic and induced growth. Can less traffic from smart growth be offset by the traffic-inducing impact of better flowing traffic, shown as E→C and E→B in Figure 1.2? • Relationship between smart growth and congestion. Denser development may cause spot congestion, even though trip generation rates and vehicle miles traveled (VMT) per per- son or per household may decrease, shown as C→D in Fig- ure 1.2. • Smart growth and freight traffic. This relationship is not shown explicitly in the framework. Organization of this Report This is the draft final report for the project and covers the three primary products of this research: • Background research (Chapter 2) on key decision points for smart growth in the planning process, the built envi- ronment’s impacts on peak auto demand, mobility by mode and purpose, induced traffic and induced growth, relationships between smart growth and congestion, and smart growth and freight traffic. This also includes a sum- mary of the key findings from the research and the gaps in researchers’ knowledge.