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.
7 1.1 Purpose This guidebook is designed to help transportation and com- munity planners account more effectively for pedestrian and bicycle activity (demand) in plans and projects. As interest in promoting walking and bicycling has increased, so too has the awareness that the tools and data to support good planning and decision-making for these modes are very limiting. This guidebook is the product of NCHRP Project 08-78, which was specifically undertaken to address these deficiencies with more robust tools and methods so as to meet the needs of a growing and diversified body of practitioners and planning applications. Non-motorized travel has garnered increased attention from the planning profession for various reasons: â¢ Continued growth in demand for highway travel unmet by expansions in capacity due to persistent funding limitations. â¢ Efforts to provide a greater number of meaningful trans- portation choices for more people. â¢ Concerns about the environmental implications of large- scale personal vehicle use, including greenhouse gas emis- sions and stormwater runoff from highway facilities. â¢ Growing interest in building sustainable, livable commu- nities that rely heavily on walkable design. â¢ Value of walking and biking as âactiveâ transportation modes in combating obesity and related health problems. â¢ Need for assistance in designing and prioritizing non- motorized transportation facilities. â¢ Direct relevance of walking and biking as key elements in supporting transit use and development concepts such as smart growth and transit-oriented development. The tools and data available to address most of these issues have been very limited, both in number and sophisticationâ this makes it hard to identify the most cost- and demand- effective projects or to compete for funds with other modes. Perhaps more urgent, however, is the need to demonstrate the benefit potential of compact mixed-use development designs, including transit-oriented development, where higher densi- ties require increased walking and biking for both access and circulationâand in effect, allowing these designs to function efficiently by reducing auto demand for travel to, from or within them. The need for good analytic tools occurs at all geographic scalesâfrom comprehensive state and regional plans and cap- ital programs, to designing effective multimodal corridors, to evaluating alternative community and activity center designs, to evaluating individual bicycle and pedestrian projects. This guidebook offers tools and accompanying guidelines to address these key planning and decision-making concerns, with methods that range from very sophisticated and detailed models to very simple sketch-planning and elasticity tech- niques. The sections below give more information on what the guidebook contains, how it is structured, and how to use it. 1.2 Overview of Analytic Tools and Gaps The tools and data available for bicycle and pedestrian plan- ning are less detailed and sophisticated than those developed for motorized travel. Possible reasons for this include â¢ Highway and transit modes receive more attention because of (1) the scale of public investment involved in their con- struction and operation and (2) the many associated impacts that must be addressed as a result of the scale of such projects. â¢ Walking and bicycling are more difficult to model because they are at a different scale and have a much closer relation- ship with the nuances of land use than motorized modes. The analytic tools available for bicycle or pedestrian plan- ning fall into one of two broad categories: â¢ Comprehensive four-step trip-based travel forecasting models, such as have long been used for regional transportation C H A P T E R 1 Introduction
8planning. Because of their spatial aggregation into TAZs, these models lack the fine granularity necessary to capture the essence of non-motorized travel choice factors. In most cases, these models are used to estimate the total number of non-motorized trips that would be generated for each TAZ (bicycle and pedestrian are often combined), based on population and employment measures. These trips are then assumed to remain within the TAZ in which they originated, and so are effectively removed from further analysis in the destination and mode-choice steps. Hence, the non-motorized modes are never able to compete with motorized modes as travel choices (thereby allowing for modal substitution if there are attractive opportunities within walking or biking distance), which also limits the degree to which changes in land use or walk/bike network accessibility can influence non-motorized travel demand given that the relevant design characteristics would be lost within the aggregation of the zonal geography. â¢ Facility demand type models, which differ from the com- prehensive models in being âcountâ based as opposed to âchoiceâ based. A choice-based model attempts to estimate trip volumes through a series of steps meant to replicate the process of deliberately deciding among travel alterna- tives, whereas a count-based approach sidesteps that com- plexity by trying to directly explain the level of activity at a given location through an association with various mea- sures of the local environment. Multiple regression is used to quantify the association, and both respectable R2 values and good parameter statistics suggest that these models are effective in explaining levels of activity. However, because the models are created with highly aggregated data to represent both the dependent (counts) and independent (explanatory) variables, and the explanatory variables often have little direct âcausalâ relationship with the activ- ity level, their reliability for forecasting often carries some doubt. Hence, their applicability is limited to the specific area for which they were developed and to the variables included in their structure. Neither type of model was judged by the NCHRP Proj- ect 08-78 review as having the desired capability to link non-motorized travel behavior to the key underlying factors identified in research studies. These factors included the characteristics of the traveler, the shape of the travel environ- ment in terms of the number and types of opportunities that would compel someone to walk or bike, and the degree to which the respective transportation networks provided access to those opportunities. Given the relatively short travel dis- tance range associated with walkingâand to a lesser extent, bikingâthe relationship between environment and behavior is much more elemental than it is with auto travel. Small dif- ferences in the composition of the built environment and how non-motorized travelers must interact with motor vehicle traf- fic have an important impact on the desirability of walking or biking. Designing effective environments or determining the most cost-beneficial facility improvements require the ability to quantify the interrelationship between the two. The most effective way to quantify this set of relation- ships is through the measure of âaccessibility.â The concept of accessibilityâthe measure of the number and variety of opportunities made available in the given pattern of land use, coupled with the efficiency of the transportation network in reaching these opportunitiesâis fundamental to any travel decision, but it is particularly central to non-motorized travel. Any effort to improve the capability of bicycle and pedestrian planning tools would need to address the issue of accessibility directly. How this concept manifests itself in non-motorized travel is presented in Figures 1-1 and 1-2. Figure 1-1 shows the diversity and distribution of land use/employment activities for Arlington County, Virginiaâone of the project research test sitesâwhile Figure 1-2 shows the network of travel facilities available to access those opportunities. The task is to merge the information in the two sources into measures that reflect the joint opportunity. If such a conjunction can be made for any point in the travel environmentâa household, a work placeâit is possible to evaluate each locationâs modal competitiveness in terms of its comparative accessibilities. In terms of the relevance for planning tools, the ability to make this simultaneous connection allows planners to work with both halves of the planning equation. As shown in Fig- ure 1-3, planners can affect accessibility by either modifying the location or mix of opportunities in the land use through the numerator (as in Figure 1-1), or enhancing the ability to access those opportunities by reducing travel time to reach them through enhancements to the travel network (as in Figure 1-2). Steady advances in GIS methods have created new oppor- tunities for building and working with these accessibility relationships. It is now possible to portray the environment in which travel occurs in much greater detail and with more realism. Rather than generalizing land use and travel at the level of TAZs, one can discern activities at a parcel-level of detail. Given that most of the data prepared for GIS manipu- lation is in the form of layers (represented as polygons, lines, or points), it is possible to share information between these layers through geospatial overlay methods and create rela- tionships. Perhaps just as valuable, tools have been developed for GIS to perform unique analysis with this information (e.g., building a travel network and quantifying the access it provides to activities by building connecting paths). Research on the relationship between land use and trans- portation has shown that built environments that feature shorter distances as a result of higher density, more attrac- tive assortment of co-mingled land uses, safe and convenient
9 Figure 1-1. Location of employment activity in Arlington County. Figure 1-2. Bicycle and pedestrian networks in Arlington County.
10 facilities for non-motorized travel, and good regional accessi- bility afforded by transit have much more efficient travel pat- terns. Households of similar size and similar economic status in such compact, mixed-use areas own fewer cars and make fewer and shorter trips by car than households in suburban, auto-dependent subdivisions. This difference is because more of these trips are made internally, to local destinations, or because access to transit is very convenient. Similar results are seen in employment and activity centers, where employees or visitors are more likely to shop or conduct business internally if they can walk to nearby activities; people are also much more likely to take transit to these areas if they can function without an auto once at the site. Another capability absent in available tools is user inter- action. Historically, transportation models have been highly technical and complex, with little user-friendliness in set up, inserting assumptions, or interpreting output. These models have required unique expertise to set up and run, are par- ticular about the strategies they can analyze, and take long computational periods to return answers. Although better software interfaces have made most models more approach- able, increased application of GIS technology has resulted in greater visualization and, in the process, greater accessibil- ity for both modeler and user audiences. It is now possible to visualize the planning environment through aerial maps, 3-D imagery, shadings, or graphics. This allows the user to âseeâ the planning environment and take part in the design of alternatives. The exercise facilitates better communication of results to stakeholders. This guidebook presents methods that take maximum advantage of accessibility, visualization, and stakeholder participation. 1.3 Overview of the Research behind the Guidebook Prior to preparing this guidebook, the NCHRP Project 08-78 research team performed an extensive review of the state of the practice in bicycle and pedestrian planning and demand forecasting methods. This review covered more than 20 years of research studies and reports, both domestic and interna- tional. The goal was to learn as much as possible about the factors influencing bicycle and pedestrian travel, including the following: â¢ Transportation infrastructure characteristics â¢ Land use and built-environment factors â¢ Topography â¢ Weather and climate â¢ Sociodemographic characteristics As part of this review, planning tools and research models used to quantify these relationships were evaluated in terms of planning applications they were being used for, their data requirements, and their accuracy and realism. This review made it possible to isolate the factors of importance associ- ated with bicycle and pedestrian travel and provide insights into their relative importance. Many of the studies were lim- ited in important ways, most commonly by focusing on one particular aspect of the demand equation (e.g., bicycle route choice). Although each of these bodies of research helped sharpen the research teamâs understanding of particular fac- tor relationships, no overarching effort to connect these pieces into a comprehensive framework for modeling non-motorized travel behavior was uncovered. Summaries of this background research and major findings are provided in Chapters 2 and 3 of the guidebook. Readers wishing to benefit more fully from this earlier research are encouraged to consult Appendices 4 through 8 of the Contractorâs Final Report, which are avail- able as part of CRP-CD-148. Given the absence of a template connecting the identified key relationships, the research team sought to capture these relationships. This research was conducted in two different venuesâSeattle and Washington, DCâtaking advantage of what were judged the best combinations of available travel survey data, the ability to relate this information to walkable/ bikeable environments, and excellent GIS tools and geospa- tial databases. Although the two research efforts used differ- ent methods, both were directly tied to the importance of accessibility, for both motorized and non-motorized modes. The Tour-based Bicycle and Pedestrian Model developed in Seattle and the GIS-based Walk-Accessibility Model developed in the Arlington County, Virginia, portion of the Washington DC metro area, are new tools that should create opportunities for planning practitionersâboth tools focused primarily on bicycle/pedestrian issues, as well as those more involved with comprehensive planning, land use, and multimodal transpor- tation analysis. Both models use a choice-based structure to estimate trip generation and modal choice, but they do so in different ways. The Seattle approach uses the highly dis- Number & Variety of Opportuni es Travel Time & Distance ACCESSIBILITY = Land Use & Urban Design Network Coverage and Connec vity Figure 1-3. Relating land use and network capability through accessibility.
11 aggregate methods employed in activity/tour-based model- ing, which brings the choice to the level of the individual and articulates land use and network relationships at the parcel level of detail. Accessibilities are computed using the actual networks. The Arlington approach also uses the actual net- works to compute accessibility to activities, but relies on GIS tools to create the paths and make the connections with the land use opportunities. A cumulative walk-accessibility scoreâ similar to Walk Scoreâis used to estimate the likelihood of walking for a particular trip purpose from (or to) any potential location. Both methods produce walk trip tables, which can be assigned to a transportation network, although neither tool currently includes an assignment procedure. It is expected that these routines can be found in the conventional trans- portation planning models or software available and in use at most MPOs and local planning agencies. Because these models are the major new tools coming out of NCHRP Project 08-78, the guidebook presents them in greater detail than some of the other tools included as options. Moreover, to encourage maximum accessibility to these two new tools, special spreadsheet versions have been developed and included with the guidebook. These spreadsheet models are intended to build familiarity with the tools and a better understanding of the key relationships and their sensitivi- ties. Sample data are provided with each model, along with detailed instructions on how to set up, use, and interpret the findings. Both spreadsheet tools can serve as sketch-planning models or in factoring estimates (in lieu of elasticities) from other models that do not have the same sensitivities. Other tools deemed to have merit for use in bicycle and pedestrian planning have been included, along with guide- lines on their use. These tools include the following: â¢ A comprehensive set of enhancement procedures for use in modifying an existing four-step trip-based model to improve its sensitivity to land use, accessibility, and non-motorized travel. These enhancements were developed as part of the Seattle-based research. â¢ Pre-existing pedestrian planning toolsâPedContext and MoPeDâthat offer special capabilities for estimating pedestrian travel in relation to land use and accessibility, at a pedestrian scale of spatial resolution. These tools also can assign walk trips to travel networks and estimate usage levels on facilities. â¢ Bicycle route choice models that quantify the relative value of the characteristics of a bicycle travel network in guiding choice of route; while these models do not predict mode or destination choice, they provide important insights that aid in effective network design and in gauging the acces- sibility of a path or network in reaching desired opportuni- ties for choice modeling. â¢ An introduction to direct demand models used for directly estimating bike or pedestrian facility demand, with exam- ples taken from applications in Santa Monica and San Diego. 1.4 Content of the Guidebook The guidebook is organized as follows: â¢ Chapter 2, Fast Facts About Walking and Bicycling: This chapter provides basic parameters on walking and bicycling, such as trip rates, trip distance and travel time distributions, comparative average distances and travel times across trip purposes, and correspondence of bike and walk trip rates with user characteristics (e.g., gender, income, auto owner- ship, education, and race/ethnicity). Most of this informa- tion is from a single source, the 2009 National Household Travel Survey, to ensure consistency among the various relationships. â¢ Chapter 3, Factors Affecting Walking and Biking: This chapter summarizes key factors that affect bicycle and pedestrian trip-making, including relationships with land use, facilities, natural environment, sociodemographic fac- tors, and attitudes and perceptions. These factors are pre- sented separately for walking and bicycling. â¢ Chapter 4, Best-Practice Methods for Estimating Bicycle and Pedestrian Demand: This chapter discusses each model or approach included in the recommended tools. This chap- ter familiarizes the reader with each method, the purpose behind its development, and special features or capabili- ties that may interest the reader. Full detail on the tools is provided in the appendices to the Contractorâs Final Report (project-developed methods) or links to key source docu- ments for other recommended methods. â¢ Chapter 5, Application of Methods: This chapter provides users with various tips, displays, and organizational strate- gies aimed at selecting and using the assembled tools. Tables comparing the key characteristics and features of each tool are provided; these are accompanied by individual model fact sheets to collect information in a single place when focusing on the given tool. Advantages and disadvantages associated with each tool are presented so as to help in the selection process. This descriptive and comparison information is fol- lowed by guidelines on ways to adapt and use each tool, along with caveats to be aware of. The level of detail in this section is greatest for the two new tools, the Tour-Based (Seattle) and the walk-accessibility (Arlington) model because they are new and different and are the major offerings from the NCHRP Project 08-78 research project. The custom spread- sheets developed for both of these tools are presented in detail. â¢ Appendixes: Individual appendixes contain the full model results and related discussion and elasticities (where avail- able) for each of the recommended tools.
12 1.5 How to Use the Guidebook Users will benefit most from this guidebook if they take time to become familiar with the overall content and organi- zation, beginning with the accessibility concepts highlighted in this chapter. The guidebook is more than a set of tools and instructions on how to use them: it provides an understanding of the key relationships, how they affect non-motorized travel behavior, and how these tools can be used to do a better job of including such information in the analysis. The guide- book demonstrates (1) how land use and transportation network shape and coverage combine to define accessibility, (2) that accessibility is the key factor in understanding walk/ bike travel, and (3) effective land use and network strategies improve accessibility. This guidebook summarizes the information compiled on the tools, explanation of their development, and the findings of the earlier research. For many users, the guidebookâs level of information will be more than sufficient; those wish- ing to deepen their understanding are encouraged to consult the Contractorâs Final Report and its appendices. In addition to providing an overview of the preliminary (Phase I) research, the Contractorâs Final Report provides an overview and assessment of data sources and offers recommendations for future research. Ideally, users will review Chapters 2 and 3 for Fast Facts and Key Factors. This will provide a good overview of bicycle and pedestrian travel and serve as a basis for understand- ing the reasons behind the development or structure of the various tools and recommendations for their use. Again, the background research on these issues is documented in much greater detail in the Contractorâs Final Report. The key operative sections of the guidebook are Chapters 4 and 5. Chapter 4 provides an overview of each of the tools, in enough depth to communicate purpose, construction, and level of complexity. Review of Chapter 4 is recommended before using the guide in Chapter 5. Chapter 4 will be of con- tinuing value as reference when using Chapter 5, when more information will be wanted on specific attributes of models. Chapter 5 contains aids to help understand the tools and compare them on various criteria, including intended geo- graphic scale, type of application, data requirements, and key output metrics. This information, along with the accompany- ing narrative, should help users select the most appropriate tool or tools for their applications. The remainder of Chapter 5 details how to apply the various tools. Equations, elasticities, and key details of models (to the extent of availability) are packaged into separate referenced technical appendices, by model. A special supplement to this guidebook may be found in the customized spreadsheet versions of the two new models created by the NCHRP projectâthe Seattle-derived tour- based model and the Arlington-based walk-accessibility model. The user will find these tools useful, particularly for sensitivity testing and creative application to individual planning tasks. Users who want to replicate or emulate a given technique have access to detailed model development reports on each of the tools. For the Seattle tour-based, Arlington Walk-Accessi- bility, and trip-based model enhancements, documentation is provided as Appendices 1 through 3, respectively, of the Contractorâs Final Report. For all other models, web citations are provided.