Making Effective Fixed-Guideway Transit Investments: Indicators of Success (2014)

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V O L U M E 1 Handbook

Contents OVERVIEW What you need to know first Section 1: Overview page 1.1 Introduction 1-1 1.2 What s Transit Project Success? 1-3 1.3 TCRP Project H-42 Research Summary 1-5 METHOD Using indicator- based methods to predict success Section 2: The Indicator-Based Method 2.1 Goals of the Indicator-Based Method 1-6 2.2 Previous Applications of Indicator-Based Methods 1-6 2.3 Ridership as a Proxy for Project Benefits 1-14 2.4 Research Findings: Indicators of Potential Ridership 1-16 2.5 Ridership Indicators Database 1-20 2.6 Spreadsheet Tool 1-20 SPREADSHEET How to use this tool Section 3: Using the Spreadsheet Tool 3.1 Quick-Start Guide 1-23 3.2 Inputs: Line-by-Line Instructions and Tips on Data Sources 1-25 3.3 Outputs: Results and What They Mean 1-33 3.4 Using the Tool to Compare Scenarios 1-37 FACTORS Have you considered... Section 4: Other Factors 4.1 Other Factors Affecting Ridership 1-38 4.2 Other Goals Beyond Ridership and Capital Cost 1-39 NEXT What to do next Section 5: What Next? 5.1 Examining Expectations in Light of Fixed-Guideway Success Indicators 1-40 5.2 Conducting a More Detailed Study 1-40 5.3 Overview of Funding Options for Fixed-Guideway Transit 1-43 References 1-44 Abbreviations and Acronyms 1-45 Appendix: Summary of the TCRP Project H-42 Database 1-46

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-1 SECTION 1 Overview 1.1 Introduction Fixed-guideway transit projects, such as urban rail and bus rapid transit (BRT) with dedicated lanes, can be among the largest infrastructure investments that cities and metropolitan areas face. The capital costs of these projects can range from tens of millions of dollars to several billion dollars. The operat- ing and maintenance costs over many years can be substantial as well. Thus, decisions on whether to build a fixed-guideway transit system and what type of system to build are not taken lightly by local officials or their funding part- ners. Such decisions may follow many years of planning and analysis at the system, corridor, and project levels. Developing and applying the analysis tools that are typically used to evaluate alternative investments can cost mil- lions of dollars. This handbook is a product of Transit Cooperative Research Program (TCRP) Project H-42, which sought to • Identify conditions and characteristics typically associated with suc- cessful fixed-guideway transit system investments, and • Provide guidance on evaluating proposed investments based on these conditions and characteristics. This handbook offers an analytical framework and a set of tools to determine whether a corridor may be suitable for investment in a fixed-guideway transit system. This handbook • Offers examples of indicator-based methods applied in transit plan- ning studies; • Identifies those factors that, when present in a corridor, seem to be the strongest indicators of a project’s potential success; and • Introduces and provides guidance on a spreadsheet tool to apply the indicator method. Is your proposed transit project likely to be successful? Can you know before investing time and money into detailed studies? This handbook and accompanying spreadsheet tool will help you evaluate whether the conditions in your corridor are right for a successful fixed-guideway project.

Transit Cooperative Research Program1-2 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS This handbook is intended to be useful to city, county, and regional decision- makers as well as transportation planning practitioners who are interested in conducting an initial assessment to determine whether a proposed transit project has potential, to evaluate a range of alternative fixed-guideway tran- sit investments, or to compare different alignments for a proposed invest- ment. It will help provide answers, at a conceptual planning level, to such questions as: • Which corridors in our region offer the best opportunity for develop- ing fixed-guideway transit? • What alternative modes and alignments appear to be the most promising in a particular corridor? • How might changes to local land use and other policies affect a corri- dor’s potential for fixed-guideway transit? This handbook and the TCRP Project H-42 Report (see Volume 2) serve to up- date and extend research by Boris Pushkarev, Jeffrey Zupan, and R.S. Cumella in the late 1970s (1). Their 1982 book, Urban Rail in America, has been widely used as a guide for identifying the type of transit investment that might be appropriate in a corridor based on development density and other condi- tions (2). In the 30 years since Urban Rail in America was published, there have been dramatic changes in metropolitan area development patterns, the work force, economic conditions, and gasoline prices, as well as a renaissance in transit. The American Public Transportation Association (APTA) reports that there are now 27 commuter rail transit systems, 15 heavy rail transit (subway) and 35 light rail transit systems in the United States. In addition, bus rapid transit (BRT) has been adopted in several municipalities as a new alternative to traditional transit modes, allowing communities historically priced out of rail technology to develop cost-effective transit networks. As of 2013, APTA counts five fixed-guideway BRT systems in the United States. Since 1980, rid- ership on U.S. commuter rail, heavy rail, and light rail systems has grown from 2.52 million to 4.47 million trips per year, while passenger miles on these modes have grown from 17.5 million to 29.5 million (3). These systems offer considerable data that enable a more complete analysis of the determinants of project success, which can be instructive for the analysis and development of future transit investments. In addition, developments in research methods, more readily available land use and transportation data, and ubiquitous computing and geographical information system (GIS) technology have advanced our ability to analyze the effects of a host of different factors on transit performance. This research benefits from these advances. The methods offered in this handbook will not provide final answers on whether or not a community should invest in transit, or what type of transit to build. However, these tools can help local governments decide whether a proposed project merits investment in more detailed planning analyses. Transit systems built over the past several decades offer considerable data that can be used to evaluate a proposed project’s potential to be successful. The tools in this handbook will help you decide whether to invest in more detailed studies.

NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS 1.2 What Is Transit Project Success? A challenge in predicting the success of a fixed-guideway project is defining what “success” means. Project goals vary by region, by city, and by corridor, and can be broad and multi-faceted. Standards that might be used to clas- sify completed projects as highly successful, moderately successful, or unsuc- cessful simply do not exist. As a part of the research, a focus group and several interviewees—comprising transportation practitioners and academics—were asked to help define success, yielding a range of responses (see sidebar) but no definitive answer to the question, “What is success?” From an economics standpoint, a successful project is one whose benefits exceed its costs. Yet a full accounting of a transit project’s direct and indi- rect costs and benefits is analytically challenging. Many of the benefits and externalities—such as a transit project’s contribution to making a city more livable—are difficult to quantify or value in dollar terms. During the planning process, proposed fixed-guideway transit projects are often evaluated by comparing their costs and transportation benefits with those of lower-cost alternatives. Relative comparisons in terms of cost effec- tiveness can be more manageable because they do not depend on a full ac- counting of all costs and all benefits. For example, if the same level and qual- ity of transit service can be provided less expensively by bus than by rail, then Figure 1: Phoenix LRT Voters in Maricopa County showed their support for building a total transit network by approving regional transportation funding in 2004. As a result, in 2008 METRO began operation of the $1.4 billion, 20-mile light rail line in Phoenix, Tempe, and Mesa. In September 2012, there were 50,000 boardings per weekday, exceeding the system’s 20-year ridership projection in less than 4 years. When asked how to determine the success of a fixed-guideway transit project, members of a focus group and other interviewees responded: “Corridors and projects are different. I suggest you look at a typology of corridors first, then look at measures of success.” “Circulators and line haul facilities, for example, have very different pur- poses.” “Success metrics ought to depend on the market and what you’re trying to do—not just the mode.” “Elected officials seem to care most about the number of riders.” “My agency would say they didn’t have any failures—our rail projects have all been successful.” I-3 Photo courtesy of METRO Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook

Transit Cooperative Research Program the rail alternative may not be the most cost-effective way to achieve these transportation benefits. The success of a completed project might also be assessed by considering how fully it meets the ridership forecasts and other goals it was intended to achieve. Our focus groups, interviews, and case studies confirmed that the goals of fixed-guideway projects are many and varied. For example, the motivations for building an urban circulator system within a central business district (CBD) might be to enhance access, or to help make the area more attractive for development, while the reasons for building a rail line extending far from downtown might be to offer people an alternative to driving on congested roadways, or to improve transit speed and reliability. A person’s view of a project’s success may also depend on his or her perspec- tive. A transit agency general manager or board of directors may define suc- cess differently than a transit rider, a taxpayer, or a funding partner. Some suggest that a project is successful if it results in widespread support for ex- panding the system. Identifying a comprehensive and widely acceptable definition of success proved to be elusive. Thus, as further discussed in Section 2.3, this research focused on measures of success that can be quantified and that generally correspond with a range of project goals: project-level ridership, changes in system-wide transit use, and project-level cost. Though incomplete as a measure of success, the expected ridership on the project and the expected 1-4 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 2: Cleveland HealthLine BRT The Greater Cleveland Regional Transportation Authority (GCRTA) considers its $200 million HealthLine Bus Rapid Transit (BRT) to be a success because: • It has led to a 75 percent ridership increase in the corridor. • After six months, the HealthLine had a customer approval rating of more than 90 percent. • More than $4 billion in development has occurred near the project. • The project has received numerous awards. Transit projects are undertaken for a range of reasons. Success comes in many forms and is inherently difficult to define. Photo courtesy of GCRTA

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-5 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS effect on the system’s usage as a whole, in combination with the expected cost of the project, provide valuable information to help establish a corridor’s potential for fixed-guideway transit. Users of this handbook will be able to determine, relatively quickly and eas- ily, whether the conditions that are typically associated with transit ridership exist or do not exist within their region or corridor. Users can develop a range of potential ridership forecasts without the use of complex travel demand forecasting models, and then balance the ridership benefits against the costs of achieving them. Proposed projects can be compared with similar fixed- guideway projects built across the United States in terms of ridership and cost per rider. For projects driven by land use and economic development goals, TCRP Re- port 16: Transit and Urban Form (4), provides additional insight into measuring project success. 1.3 TCRP Project H-42 Research Summary The research upon which this handbook is based was sponsored by the Tran- sit Cooperative Research Program (TCRP) and performed by a team at the University of California at Berkeley, with assistance from Parsons Brinckerhoff. As part of the research, the team completed the following tasks: • Reviewed prior research and available data to identify ways that transit system success is measured. • Conducted two rounds of focus groups and interviews with transit professionals in the public and private sectors and in academia. • Prepared a preliminary list of transit investment success measures and possible indicators of that success. • Compiled and assembled a dataset of fixed-guideway transit stations and networks in the United States, covering 3,244 transit stations in 27 metropolitan areas. Data collected at the station, investment, and metropolitan area levels included system and station ridership, agency operating costs, project capital costs, regional and local demographics, employment, gross metropolitan product, gas prices, parking availabil- ity and pricing in downtowns and in private lots, restrictiveness of land use regulations, rail and highway networks, and transit service charac- teristics. • Conducted regression analyses to identify corridor, network, and met- ropolitan area factors that are most significantly correlated with project- level ridership and system-level passenger-miles traveled (PMT). • Conducted case studies of transit projects in six different U.S. metro- politan areas, reviewing public reports and other materials, conducting site visits, and interviewing transit planners, metropolitan planning organization (MPO) officials, and consultants who worked on the projects. • Developed a spreadsheet tool, using coefficients produced by the regression analyses, which can provide initial predictions of ridership, PMT, and capital cost. Details on the research are provided in the Research Report, which is included as Volume 2 in TCRP Report 167 (5). This handbook is based on analysis of data from 27 U.S. metropolitan areas and the input of transit professionals from the public and private sectors and academia.

Transit Cooperative Research Program1-6 This approach is useful for conducting initial assessments of potential projects and corridors. Indicators are characteristics of the corridor and the proposed transit service. SECTION 2 The Indicator-Based Method 2.1 Goals of the Indicator-Based Method Indicators are characteristics of a corridor and a proposed project that may affect the project’s success. As discussed in Section 1 and in more detail in Section 2.3, for the purposes of this handbook, success is defined primarily in terms of producing sufficient project-level and system-level ridership to justify the cost of the project. The indicator-based method offers a simplified way to analyze the potential success of a proposed fixed-guideway transit project in a particular corridor, given a certain set of corridor conditions and assumptions about the proj- ect. While not meant as a substitute for more detailed planning methods and analysis, the indicator-based method can be useful for conducting an initial evaluation of corridors and fixed-guideway transit alternatives. For example, local agencies might use this method to • Assess whether it is worthwhile to expend funds on detailed project planning studies, • Compare various corridors within a region to see which offers the greatest potential for a transit investment, • Test various project and land use scenarios within a particular cor- ridor to identify those that deserve more detailed study, or • Advocate for changes in transit service and land use policies that would enhance transit ridership. 2.2 Previous Applications of Indicator-Based Methods Planners have used indicator-based methods to evaluate transit opportuni- ties for many years. A few such methods are described in this section, fol- lowed by a description of the method developed in this study. The method developed in TCRP Project H-42 differs from other indicator-based methods

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-7 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Pushkarev and Zupan found that the density of residents along a corridor and the amount of non-residential development in the CBD were significant indicators of ridership, while noting that other factors also contribute to transit project success. in that it generates estimates of project ridership and change in system-level patronage based on statistical analysis, using data from fixed-guideway sys- tems built over the last 40 years. It is more quantitative than other indicator- based methods that use a limited number of somewhat subjective factors, yet it produces a ridership forecast without relying on complex regional trav- el demand forecasting models. In 1976, New York’s Regional Plan Association suggested certain transit mode suitability criteria based on density (Table 1) (6). Table 1: Transit Mode Suitability Criteria by Regional Plan Association Transit Vehicle Mode Minimum Downtown Size, Square Feet of Contiguous Non-Residential Floor Space (millions) Minimum Residential Density, Dwelling Units per Acre Local Bus 2.5 4 to 15* Express Bus 7 3 to 15* Light Rail 21 9 Heavy Rail 50 12 Commuter Rail 70 1 to 2* *Varies with type of access and frequency of service Source: Regional Plan Association, Where Transit Works: Urban Densities for Public Transportation. New York, 1976. The Regional Plan Association’s recommendations were followed by Push- karev and Zupan’s research, leading to Urban Rail in America several years later. Pushkarev and Zupan recommended a set of minimum threshold resi- dential densities that would support various levels of service across differ- ent modes. Larger CBDs and higher residential densities along corridors were found to support higher levels of transit service. Pushkarev and Zupan found that the success of a transit system depends on other factors as well, includ- ing, “its service and its price, [and] the availability, convenience, and price of the competing mode—the automobile.” (1)(2)

Transit Cooperative Research Program1-8 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Mode: Service Minimum Units-per-Acre Thresholds CBD Size Local Bus: Minimum (20 buses/day) 4 10 million non-residential CBD s.f. Local Bus: Frequent (120 buses/day) 15 35 million non-residential CBD s.f. Light Rail: 5-minute peak-hour headways 9 (corridor of 25 to 100 square miles) 20 to 50 million non-residential CBD s.f. Heavy Rail Rapid Transit: 5-minute peak-hour headways 12 (corridor of 50 to 100 square miles) 50+ million non-residential CBD s.f. Commuter Rail: 20 trains/day 1 to 2 Only to largest downtowns Today, transit planners rely on guidelines such as these when they develop system plans, identify potential new transit corridors and routes, and decide how to allocate available funds. One example is A Toolbox for Alleviating Traffic Congestion, published by the Institute for Transportation Engineers (ITE) in 1989. The report offers general guidelines as follows: • Light rail transit is most suitable for service to non-resi- dential concentrations of 35 to 50 million square feet. If rights-of-way can be obtained at grade, thereby lower- ing capital costs, this threshold can be lowered to the 20 million square foot range. Average residential densi- ties of about 9 dwelling units per acre over the line’s catchment area are most suitable. For longer travel dis- tances where higher speeds are needed, rapid transit is most suitable for non-residential concentrations beyond 50 million square feet and in corridors averaging 12 dwelling units per acre or more. • Commuter rail service, with its high speed, relatively infrequent service (based on a printed schedule rather than regular headways) and greater station spacing is suitable for low density residential areas—1 to 2 dwell- ing units per acre. However, the volumes required are only likely in corridors leading to non-residential con- centrations of 100 million square feet or more, found only in the nation’s largest cities. (7) Table 2: Transit-Supportive Density Levels adapted from Pushkarev and Zupan (1)

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-9 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS As shown in Table 3, the San Francisco Bay Area’s Metropolitan Transporta- tion Commission (MTC) has adopted a set of housing density thresholds by transit mode that projects are expected to meet before the MTC programs funds (8). According to the MTC’s Resolution 3434, “Each proposed physi- cal transit extension project seeking funding through Resolution 3434 must demonstrate that the thresholds for the corridor are met through existing development and adopted station area plans that commit local jurisdictions to a level of housing that meets the threshold.” BART Heavy Rail Transit Light Rail Transit Bus Rapid Transit Commuter Rail Ferry Housing Threshold (Average Housing Units per Station Area) 3,850 3,300 2,750 2,200 750 Source: MTC Resolution 3434, Attachment D-2, as revised July 27, 2005 The Utah Transit Authority calculates a Transit Preparedness Index to identify those parts of its service area that have the characteristics to support a suc- cessful transit investment. The index relies on five criteria to identify the best places in the region for improving transit service: 1. Transit-oriented development (TOD) or mixed use zoning (up to 40 points), 2. TOD or mixed use in general plan (up to 10 points), 3. Bike/pedestrian plan (up to 10 points), 4. Amenity Proximity Score based on walkscore.com (up to 10 points), and 5. Intersection Density based on walkscore.com (up to 30 points). Indicators are generally evaluated in combination to provide a more complete picture of an area’s readiness for fixed- guideway transit. Table 3: Housing Density Thresholds, MTC, San Francisco Bay Area

Transit Cooperative Research Program1-10 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Consulting firms have developed proprietary indicator-based tools such as the Transit Competitiveness Index (TCI) (9). This tool, depicted in Figure 3, of- fers a way to score different travel markets in terms of how well transit is likely to compete with the automobile. The TCI accounts for various transportation and land use characteristics—trip volumes, land use density, parking cost, and congestion—along with trip purpose and household characteristics to produce a numeric score. Depending on the score, individual markets are characterized as strongly competitive, marginally competitive, marginally uncompetitive, and uncompetitive. Further information is available at: http://www.mtc.ca.gov/planning/tsp/TCI-DRAFT-PRIMER.pdf Figure 3: Use of the Transit Competitiveness Index by MTC Analysis of Individual Market Work Trips From Walnut Creek to Downtown Oakland TCI TCI = 693 Contribution from… Attraction density Production density - Auto ownership -1 Congestion Household income 0% Origin diversity CBD characteristics Access from parkingParking costs Destination diversity Topology Toll Source: San Francisco MTC and Cambridge Systematics, Inc.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-11 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS CREATE Canby HS Aloha HS Putnam HS Tigard HS Wilson HS Jesuit HS Sunset HS Liberty HS Gresham HS Century HS Madison HS Glencoe HS Estacada HS Sherwood HS Tualatin HS La Salle HS Marshall HS Franklin HS Reynolds HS Parkrose HS Westview HS Riverdale HS Clackamas HS West Linn HS Gladstone HS Lakeridge HS Milwaukie HS Reed College Beaverton HS Cleveland HS Hillsboro HS Jefferson HS Roosevelt HS Southridge HS Sam Barlow HS Centennial HS PCC - Cascade Wilsonville HS Oregon City HS Lake Oswego HS PCC - Sylvania Capital Center PCC - Southeast Catlin Gabel HS Cascade College Forest Grove HS Merlo Station HS David Douglas HS PCC - Rock Creek Concordia College Pathfinder Academy Valley Catholic HS Pacific University Sylvan Learning Ctr Oregon Outreach Inc Springwater Trail HS SERP Enterprises Inc. New Urban High School Marylhurst University Damascus Christian HS Westside Christian HS Lewis & Clark College Serendipity Center HS Portland Christian HS Warner Pacific College University of Portland Arts & Communication HS Mt Hood Community College Oregon Graduate Institute Mt Hood CC Maywood Campus Tualatin Valley Jr Academy Portland Adventist Academy De La Salle North Catholic HS Oregon Institute of Technology Oregon Health & Science University 13D,13 10 16 13D 8 28 28 28 9 29 10 11 11T 29 29 29 28 28 28 34 34 34 34 34 38S 11 11 11 17D 1712 17 32 Hillsboro Gateway PDX Int’l Airport GreshamBeaverton Vancouver Clackamas Oregon City Lents Aloha Tigard Washington Square Camas Orenco Cornelius Tualatin Bethany Fairview Hillsdale King City St. Johns Troutdale Wood VillageCedar Mill Sherwood Gladstone Hollywood Rockwood Wilsonville Damascus Murray Hill Washougal West Linn Lake Grove Tanasbourne Raleigh Hills Milwaukie Happy Valley Forest Grove West Portland Pleasant Valley Lake Oswego Sunset Transit Center Portland Central City: To be determined through Central City Plan update Bi-state HCT corridors to be considered in conjunction with RTC 26 30 5 84 205 205 26 84 5 5 217 224 212 99 E 99 W 10 8 43 219 L E G E N D TransitPriority HCT Corridors* High Capacity Transit (2009) High Capacity Transit Corridors under advancement 2035 Conceptual Bus Network Railroad Major Arterials School 0 2 4 Miles Near-Term Regional Priority Corridors Next Phase Regional Priority Corridors Developing Regional Priority Corridors Regional Vision Corridors Parks/Open Space RTC HCT Corridors County Boundary Adopted by: JPACT, June 23, 2009 Metro Council, July 9, 2009 Resolution No. 09-4052 ID ID ID Urban Growth Boundary *Lines are representative of general HCT corridors, buffers are 1 mile ID Near-Term Regional Priority Corridors Next Phase Regional Priority Corridors Developing Regional Priority Corridors Regional Vision Corridors ID ID ID ID • 10 Portland city center to Gresham (in the vicinity of Powell Boulevard corridor) • 11 Portland city center to Sherwood (in the vicinity of Barbur Boulevard/Hwy 99W corridor) • 34 Beaverton to Wilsonville (in the vicinity of WES commuter rail corridor) • 8 Clackamas Town Center to Oregon City Transit Center • 9 Milwaukie to Oregon City Transit Center • 17 Sunset Transit Center to Hillsboro • 17D Red Line extension to Tanasbourne • 28 Washington Square Transit Center to Clackamas Town Center • 29 Washington Square Transit Center to Clackamas Town Center • 32 Hillsboro to Beaverton • 55 Gateway to Salmon Creek • 12 Hillsboro to Forest Grove • 13 Gresham to Troutdale extension • 13D Troutdale to Damascus• 16 Clackamas Transit Center to Damascus • 38S Tualatin to Sherwood Figure 4: Setting Transit Corridor Priorities in Portland When developing the Regional High Capacity Transit System Plan for metropolitan Portland, the region’s MPO (known as Metro) used an online “build-a-system” questionnaire to solicit public input. The results told decision-makers that residents wanted ridership potential to be the main factor in deciding corridor priority. Source: Metro, used by permission Metro, the MPO for the Portland, Oregon, region, applied an interactive web- based “build-a-system tool” as part of the public involvement process for its High Capacity Transit System Plan (Figure 4). According to the plan, [The] tool allowed community members to explore trade-offs between corridors and build their own high capacity transit sys- tem. With the build-a-system tool, community members learned about centers that could be served by high capacity transit and to compare corridors based on ridership, travel time, operations cost, capital cost, and environmental benefits. (10) Metro’s tool is more fully described at: http://www.oregonmetro.gov/index.cfm/go/by.web/id=26680

Transit Cooperative Research Program1-12 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS The six case studies documented in the TCRP Project H-42 final report identi- fied a number of other rules of thumb used to evaluate fixed-guideway tran- sit projects (Table 4). Several of these relate to ridership, and some are specifi- cally meant to consider either choice or dependent ridership. Others relate to the potential for economic development and real estate impacts, and to the potential to complete projects within a finite budget. Though not technically complex, the rule of thumb methods helped transit planners address the immense complexity of designing and building a tran- sit project. The case studies, summarized in Volume 2 of TCRP Report 167 (5), illustrate several balancing acts among various interest groups, among con- flicting objectives, and between technical analysis and heuristic evaluations. In addition to analyzing quantifiable indicators, transit agencies consider various rules of thumb in developing transit systems.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-13 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Table 4: Success Indicators from TCRP Project H-42 Case Studies Criterion (Rule of Thumb) Measure of Project Success Ch ar lo tt e D al la s Eu ge ne Po rt la nd Sa lt La ke C ity D .C ./M D Provide fixed-guideway transit where bus ridership is already high Ridership / Consolidated bus operations Select high-visibility corridors where patrons will feel safe Ridership Connect CBD with suburban park-and-rides near a congested belt loop Ridership / Sustainability / Congestion relief / Consolidated bus operations Minimize stations to maximize speed Ridership / Sustainability / Congestion relief Minimize grade crossings and in-street operations to maximize speed Ridership / Sustainability / Congestion relief Provide fixed-guideway transit in corridors where parallel highway infra- structure is heavily congested Ridership / Sustainability / Congestion relief Connect multiple employment centers Ridership / Sustainability / Congestion relief Connect major regional destinations Ridership / Economic development Place alignment in close proximity to commercial property Ridership / Economic development Place stations in busy locations where “eyes on the street” provide sense of safety Ridership Provide service that has average travel speeds greater than existing bus routes Ridership / Consolidated bus operations Provide transit in high-demand travel corridors where alternative capacity is prohibitively expensive Economic development Maximize the number of stations Economic development / Real estate values Place alignment along corridors with ample development potential to fa- cilitate urban growth as described by local land use plans or regional plans Real estate values Provide fixed-guideway transit in corridors where inexpensive right-of-way can be easily accessed Construction completion / Minimized impacts Maximize distance between alignment and single family neighborhoods; Minimize taking of residential property Minimized impacts / Public support Identify corridors that can help garner local political support for further transit system investment Public support Select corridors that garner congressional support Public support Locate stations in low income areas or in communities of color Dependent riders / Economic development Provide substantial bus layover facilities at stations Consolidated bus operations

Transit Cooperative Research Program1-14 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS 2.3 Ridership as a Proxy for Project Benefits Ridership was chosen as the primary measure of project benefit in the TCRP Project H-42 research. When a new transit project is proposed, one of the first questions people ask is how many people will use it. Once a project opens for service, often the first question asked is whether the forecast levels of rider- ship were achieved. Transit projects are often deemed to be successful when their forecast ridership level is met. Ridership is a useful proxy for a wide range of transit project benefits. Those who ride on a new transit line are likely to directly benefit in one way or an- other. Existing transit riders—such as people who previously took the bus but who now ride the new fixed-guideway system—may benefit from faster travel time, improved reliability, or greater comfort. New riders—those who started using transit only when the project opened—offer another measure of the project’s mobility/accessibility benefits. New riders might be people who previously commuted by car but who switched to the new transit line upon realizing that it offered them travel time or other benefits. Changes in ridership can also serve as a measure of reductions in congestion, air pollut- ant emissions, and energy consumption. To some degree, ridership can also be viewed as a proxy for land use and economic development benefits. A project that attracts few riders is unlikely to stimulate much development, while projects that do stimulate development are likely to attract additional ridership. For this research, ridership proved to be a convenient indicator of success because transit ridership data are readily available and can be statis- tically correlated with corridor conditions. When comparing the transit potential of different corridors, or the potential of different alternatives within a corridor, there are two complementary mea- sures of ridership: 1. Project-level ridership is the number of trips that would be made on a proposed project on a daily basis. Project-level ridership includes both existing riders and new riders attracted to transit. 2. System-wide patronage change is the expected change in system- wide daily passenger-miles traveled (PMT) on transit once the proposed project is in service. System-wide PMT takes into account the greater regional mobility that may occur when a single guideway project links riders into a regional system. System-wide PMT captures the number of new riders and the length of their trips. It does not include existing riders whose trip length on transit does not change, even if these riders benefit from faster travel time. Compared with project-level ridership, the change in system-level PMT offers a better indicator of a project’s likely impact on overall highway congestion, emissions, and energy consumption, but it does not indicate how a guideway investment would benefit existing users. Ridership is a useful proxy for a wide range of transit project benefits.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-15 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Project-level ridership and system-level PMT are complementary and offer different perspectives on a project’s benefits. An urban circulator, for exam- ple, may attract a significant number of new riders, many of whom may have walked before. Since circulator trips are typically short, circulators may have little impact on PMT unless they also provide the “last mile” connection that makes longer-distance transit travel more attractive. A commuter rail project with the same project-level ridership as the circulator could have a larger im- pact on PMT, because commuter rail trips tend to be much longer. The PMT estimate includes all transit travel in the region, including miles trav- eled on the bus network. A bus rider who simply switches a routine trip to a new, parallel rail line of the same length would not produce any change in PMT. A trip attracted from auto to transit, however, would add to PMT on the transit system. If the new rail line is more direct than the pre-existing bus route, or if it leads to bus service reductions or forced transfers, the PMT increase from new riders could be muted or even offset as riders defect from the transit system. Figure 5: WMATA Orange Line In 2008, WMATA’s Orange Line carried 79,000 riders per day in Virginia. The line connects con- centrated development near the subway stations in Arlington with the District of Columbia, just across the Potomac River. Relatively high residential and commercial densities in Arlington and the District, together with good transit access, contribute to Orange Line ridership and PMT on the Metrorail system. The Orange Line has also played a key role in shaping development in Arlington. Photo courtesy of Arlington County (markings by Kaid Benfield) Evaluating both project- level ridership and changes in system-wide passenger miles provides a more complete picture of a project’s benefits than one of these measures alone.

Transit Cooperative Research Program1-16 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS 2.4 Research Findings: Indicators of Potential Ridership The analysis conducted for TCRP Project H-42 considered more than 140 dif- ferent factors that could possibly influence project-level or system-level rid- ership. To identify those factors that correlate most strongly with ridership, the researchers conducted regression analyses using data from 55 heavy rail transit (HRT), light rail transit (LRT), and fixed-guideway bus rapid transit (BRT) projects in more than 20 metropolitan areas. The analysis found several strong and significant predictors of transit rider- ship, and some surprising results. Table 5 summarizes the indicators of greatest statistical significance in ex- plaining project ridership and PMT. A full list of the indicators considered in the research, and their value as predictors of success, is presented in the Appendix. Researchers analyzed 55 completed transit projects to find correlations between ridership and more than 140 factors. Table 5: Most Significant Indicators of Project Ridership and System-Wide PMT Indicators of Project Ridership Indicators of Change in PMT on System • Employment within one-half-mile of project stations • Population within one-half-mile of project stations • Combination of employment and population within one-half- mile of stations and daily parking rate in the CBD • Percent of the project alignment at grade • Metropolitan area population • Employment density within one-half-mile of fixed-guideway stations in the metropolitan area • Population density within one-half-mile of fixed-guideway stations in the metropolitan area • Higher wage jobs within one-half-mile of fixed-guideway stations in the metropolitan area • Average congestion in the metropolitan area (daily vehicle- miles traveled (VMT) per freeway lane-mile) • Retail, entertainment, and food jobs within one-half-mile of fixed-guideway stations in the metropolitan area • Interaction of jobs and population within one-half-mile of fixed-guideway stations in the metropolitan area

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-17 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Like Pushkarev and Zupan, the researchers for this study found that the amount of population near stations is highly predictive of a proposed transit project’s success in attracting ridership. Unlike that previous work, this analy- sis showed that employment near stations was at least as important as popu- lation. More importantly, perhaps, the analysis demonstrated that those proj- ects with the highest ridership have a combination of dense population near stations, dense employment near stations, and relatively high CBD parking costs. The percentage of the project’s alignment that is at grade proved to be a negative indicator of project-level ridership. At-grade projects may be more prevalent in places that are lower in density, while transit is more likely to be grade-separated in places with higher density or land value. Thus, this indica- tor may be reflective of density. It may also be true that at-grade systems are slower than grade-separated systems. At-grade status may reflect a bundle of operational characteristics such as speed, frequency, and reliability, although the analysis did not find that these factors individually had a statistically sig- nificant effect on ridership. Transit travel speed and frequency were less significant predictors of a transit project’s ridership compared to other variables such as density and parking costs downtown. Another surprise related to central business district (CBD) employment. While the number of jobs near stations was an important indi- cator of ridership, there was no significant difference between jobs within a CBD and other jobs near stations. Figure 6 illustrates the goodness-of-fit plot for the ridership model in the spreadsheet tool and shows the high predictiveness of the model. The black line represents a perfect match between predicted and actual values; the ac- tual values are tightly clustered around the line. Transit travel speed and frequency were not found to be the most significant predictors of ridership.

Transit Cooperative Research Program1-18 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS In contrast to the ridership model’s focus on characteristics of individual proj- ects, the PMT model widens the scope to forecast overall ridership on the full transit system of a metropolitan statistical area (MSA), including all modes and lines. Each MSA is represented by a different data point for each year data was available, for a total of 1,390 observations. The indicators for system-wide PMT change relate to how the proposed proj- ect can affect metropolitan area transit use. Projects in larger metropolitan areas, with a fixed-guideway system in place serving relatively dense popu- lations and employment, tend to see the greatest benefit from incremental additions to the system. The number of retail, entertainment, and food jobs near transit stations is a positive indicator of regional PMT. A high number of jobs in these categories means that the system serves a significant number of non-work activities, such as shopping and restaurants, that attract riders to the system. The number of higher-wage jobs near transit stations is an- other positive indicator. The goodness o fit for the PMT model is clear, as shown in Figure 7. Figure 6: Ridership Model Goodness-of-Fit Plot Pr ed ic te d Ri de rs hi p Actual Ridership

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-19 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 7: PMT Model Goodness-of-Fit Plot The capital cost model used by the spreadsheet tool was developed by Guer- ra and Cervero. We recommend that users curious about the theoretical un- derpinnings of that model read its documentation (11). Pr ed ic te d Ri de rs hi p M ill io ns Actual Ridership Millions

Transit Cooperative Research Program1-20 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS The spreadsheet tool applies the indicator-based method as it compares your proposed project with the completed projects studied as part of this research. 2.5 Ridership Indicators Database The database developed as part of TCRP Project H-42 is summarized in the appendix to this handbook (Volume 1) and further described in the Research Report (Volume 2). For each of the projects in the database, the Appendix provides values for the most significant indicators identified in Table 5. Plan- ners can use this database to identify projects that are similar to their own. If one or more similar projects can be identified in a corridor with similar densi- ties and other characteristics, an initial estimate of the project-level ridership and PMT change can be inferred or interpolated. Although a perfect match is unlikely, a reasonably close match can be informative. If none of the database projects comes reasonably close to the one proposed, however, that finding may caution that the proposed project may not be a suitable match for the corridor. To illustrate, all of the initial LRT projects in the database serve corridors that have at least 65,000 employees and a population density of more than 13,000 people per square mile. If a proposed LRT project would serve a corridor with fewer jobs and less density than these projects, it may not attract as many riders. The database may also offer a useful tool for checking the reasonableness of travel demand model forecasts. If the regional model predicts that a proj- ect will attract 50,000 riders per day but the database shows that all projects attracting 50,000 daily riders serve more densely populated corridors, there may be reason to question the reasonableness of the model results. Similarly, caution should be used if model results are outside of or far from the data points used to determine goodness-of-fit. 2.6 Spreadsheet Tool The Microsoft Excel-based spreadsheet tool developed as part of this re- search provides a simple way to apply the indicator method to compare dif- ferent corridors and alignments in terms of their potential to attract ridership. The user enters corridor data for indicators with the strongest correlation to ridership. The tool runs calculations using coefficients derived from the statis- tical analysis of fixed-guideway transit projects built in the United States be- tween 1974 and 2008. The output of the tool is a preliminary estimate of how many riders could be expected on a new fixed guideway in a given corridor. It also offers an estimate of the change in PMT on the entire system. When a capital cost estimate is entered into the tool, the spreadsheet calculates the cost per rider and cost per new PMT. Users can compare the ridership forecast for their corridor with the ridership on similar completed projects elsewhere in the United States. They can also compare their project with others in terms of cost per rider and cost per new PMT.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-21 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 8: Spreadsheet Tool Opening Screen One strength of the spreadsheet tool is that rather than producing a single ridership answer, it provides a range of forecasts. The range allows the user to more meaningfully interpret the results and understand the uncertainty associated with any forecast. Transit ridership and cost are influenced by myriad factors, many of which cannot be captured in a statistical model such as this one. In fact, the database includes a number of outliers—completed projects with actual ridership outside the range that would be predicted by this model—perhaps reflecting special markets or conditions unique to a particular area. The tool has several limitations. It only estimates three success factors: proj- ect-level ridership, system-level change in PMT, and capital cost. As has been noted, these are not the only factors important in evaluating the likely suc- cess of a fixed-guideway transit project. Also, at this time, the method should only be applied to predict ridership for HRT, LRT, and fixed-guideway BRT lines. The spreadsheet tool provides a range of ridership forecasts, recognizing the many uncertainties that come into play.

Transit Cooperative Research Program1-22 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS The PMT model finds incremental changes due to the studied investment by comparing total PMT values across the system with and without the proj- ect. Because the model was built using PMT values much larger than the in- crements which are its outputs, the increments are on the same order of mag- nitude as the error in the model. This issue is an unavoidable consequence of the data and the methodology, but increments of smaller magnitude should be viewed with a critical eye. This relatively simple tool is not meant to be a substitute for a well-calibrated local travel forecasting model that reflects the corridor’s travel markets and patterns, that more fully represents the attributes of the project and com- peting services, and that offers useful insights into the reasons for ridership changes. TCRP Project H-42 was carried out concurrently with efforts by FTA to develop a simplified travel forecasting model for predicting transit ridership on fixed- guideway projects. The FTA model is the Simplified Trips-on-Project Software (STOPS). Compared with traditional four-step models, STOPS is simplified for the user in terms of the level of effort needed to develop and test a useful model, prepare inputs, and make forecasts. Internally, STOPS is quite detailed and uses transit components that are similar to those found in conventional models. Some users may want to use both STOPS and the TCRP Project H-42 spread- sheet tool to see if they produce similar ridership forecasts. Using both might offer greater confidence in the result, or might provide useful insights about proposed projects. For those interested in using only one of the models, the choice may depend on how one intends to use the results, how quickly one wants the results, and the availability of necessary input data. Some users may prefer to use the faster spreadsheet tool for an initial “quick response” screening of alternatives, then turn to STOPS to prepare forecasts that will support an FTA New Starts or Small Starts rating. The spreadsheet tool differs from the FTA’s ‘STOPS’ model.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-23 SECTION 3 Using the Spreadsheet Tool 3.1 Quick-Start Guide To use the spreadsheet tool, users input data on the corridor being studied as well as data on the fixed-guideway transit system to which it would con- nect. Thus, it is necessary to assume a general alignment for the proposed transit project, a mode, potential station locations, and the percent of the line that would be at grade. Also needed are reliable estimates of population and employment near stations. A GIS system containing population and employ- ment data by job classification and income at the traffic analysis zone level or census tract level can be instrumental in assembling these data. Other data necessary for analysis are provided automatically when the user selects the metropolitan area from the drop-down menu. Open the spreadsheet tool in Microsoft Excel. To access data entry instruc- tions at any time, click the Instructions tab along the bottom of the screen. Line-by-line instructions and tips are also provided in Section 3.2 of this quick-start guide. The data entry screen, shown in Figure 9, has three parts: 1. The Input Panel (Ridership and PMT) at the top of the input screen (inputs 1 through 12) is for data used by the model to predict aver- age weekday ridership for the proposed project, as well as changes in passenger miles. 2. The Input Panel (Cost) (inputs 13 through 20) is for entering informa- tion related to a project’s capital cost. Users may enter a total cost for the project or a cost per directional route mile. If this information is not available, the default cost calculator that is part of the tool may be used, although specific local data are likely to yield more accurate results. 3. The Reference Panel contains values that are automatically gener- ated based on user inputs in the above panels. Users input information on the proposed project and corridor; certain other cost and demographic information is automatically populated when the metropolitan area is selected.

Transit Cooperative Research Program1-24 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Data input here is used to predict ridership. These numbers are automatically calculated. Data input here is used to estimate costs. Figure 9: Data Entry Screen Once these data are supplied, the spreadsheet tool will calculate the expect- ed daily ridership on the project, the likely change in daily PMT, the estimated capital cost, the capital cost per rider, and the capital cost per new PMT. The tool will show how the proposed project compares with other U.S. fixed- guideway transit projects in the database. By benchmarking against similar projects, users can assess the likelihood that the project will be successful. The tool can also be used to run “what-if” scenarios by testing the ridership impact of different input assumptions, such as higher population and em- ployment concentrations. To get the most value from the tool, it is essential to enable macros within Excel. Users can search the Excel help reference for how to enable macros in their version of Microsoft Excel.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-25 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 10: Calculations Involving Partial Census Blocks 3.2 Inputs: Line-by-Line Instructions and Tips on Data Sources This section offers line-by-line instructions on what data to enter into the spreadsheet tool to produce an estimate of ridership and PMT change for a project. The first six inputs provide information about the proposed transit project and the corridor it would serve. Characteristics of the population and employment need to be calculated for the area within one-half-mile of the proposed stations. U.S. Census data is provided by census block. As depicted in Figure 10, each station area typically encompasses portions of multiple census blocks. Population and employment data collected by census block needs to be adjusted proportionately to estimate the values within each sta- tion area. For all figures involving U.S. Census data: Download data for the census blocks located all or partially within the area to be analyzed (the area within one-half-mile of a proposed transit station). If a block does not fall completely within the half-mile buffer, adjust the number of jobs, residents, etc., counted within the block appropriately. If a census block falls within one- half-mile of more than one station, count the jobs within that block only once. TIP 1 2 9 10 1211 5 87 6 43 Census Block ½-mile Station Station Area River Source: Adapted from Federal Transit Administration’s Sample Methodology for Estimating Station Area Socio-Economic Statistics in Reporting Instructions for the Section 5309 New Starts Criteria.

Transit Cooperative Research Program1-26 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Line 1: Select Metropolitan Statistical Area (MSA) Select the MSA from the drop-down list as shown in Figure 11. Based on this selection, the tool draws on its internal database for relevant in- formation from the U.S. Census Bureau, as of 2008, such as the number of people in the MSA and the number of existing jobs in the CBD. These data cannot be changed. Line 2: Jobs within ½-mile of project stations Insert current employment data on Line 2 to estimate ridership if the project were in place today. Block-level employment data for years be- tween 2000 and 2010 are available through the following process: 1. Use the U.S. Census Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statistics (LODES) download site at: http://lehd.ces.census.gov/data/#lodes 2. Version = LODES7 for 2010 census blocks, LODES5 for 2000 Census Blocks 3. Select state 4. Type = Workplace Area Characteristics 5. The file name structure is: [STATE]_wac_[SEGMENT]_JT00_[YEAR] a. [SEGMENT] = S000 for totals, SE03 for high-wage Figure 12 shows the LODES interface with representative selections. Figure 11: Ridership and PMT Input Panel

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-27 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 12: LODES Interface To convert the block-level LEHD data to a value that can be entered on Line 2 (or any other line using catchment-area employment), it is neces- sary to select only those blocks that lie inside the one-half-mile catch- ment area around stations. When this process was performed in creating the model, the catchments were clipped to exclude water and to ensure that no two catchments overlapped. This eliminated double-counting while ensuring that all of the jobs lying within one-half-mile of any proj- ect station were counted once (see Figure 10). The process of selecting the proper blocks is easiest using GIS software, though it can be performed manually using printed maps. To estimate ridership in some future year, it is necessary to enter job fig- ures estimated for that year. These may be derived from forecasts the region’s MPO or local jurisdictions maintain for transportation planning. Entering different employment forecasts will enable users to test “what- if” scenarios. The spreadsheet model will still assume regional conditions based on 2008 Census data, but it can show how sensitive ridership would be to changes in employment near stations. Use the spreadsheet to test what-if scenarios. For example, users can enter a higher number of jobs in the vicinity of stations to see how ridership might change if employment were more concentrated. TIP

Transit Cooperative Research Program1-28 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS The higher the percentage of alignment at grade, the lower the ridership typically will be. Corridors with at-grade systems tend to have less density than corridors with grade-separated systems, and thus attract fewer riders. The at-grade mileage may also be indicative of slower transit speeds. TIP Line 3: Population within ½-mile of project stations Similar to Line 2, enter the number of people residing within one-half- mile of the planned stations. Existing population can be obtained from the U.S. Census or another reliable source. Again, forecasts of future population can be obtained from the MPO or local jurisdictions. “What-if” scenarios can be tested to see how changes in population near stations would affect ridership on the project and PMT on the system. Line 4: Retail, entertainment, and food jobs within ½-mile of project stations On Line 4, enter the number of “attraction-based” jobs—that is, jobs in- cluded in North American Industry Classification System (NAICS) codes 44-45 (Retail Trade), 71 (Arts, Entertainment, and Recreation), and 72 (Ac- commodation and Food Services). Using the U.S. Census LEHD or another reliable source, calculate the number of jobs in these categories within one-half-mile of the proposed stations. Line 5: Higher wage jobs within ½-mile of project stations “Higher wage jobs” refers to jobs in the Earn3 category of the U.S. Census LEHD data; that is, jobs earning greater than $3,333 per month. Using LEHD or another reliable source, calculate the number of jobs in this cat- egory within one-half-mile of the proposed stations. Line 6: Percent of project alignment at grade Users enter the percent of the alignment that is at grade. For example, if 50 percent of the proposed alignment is going to be at grade within a highway median and 26 percent will be at grade within a street, users would enter “76” on Line 6. The spreadsheet tool uses Lines 7 through 12 and general MSA-level data based on the entry on Line 1 to estimate the PMT on the entire fixed-guide- way transit network with and without the proposed transit project. The dif- ference between these values is the incremental change in PMT attributable to the project.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-29 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Line 7: Daily parking rate in the CBD Enter the average daily (6- to 24-hour) cost of market-rate parking in the CBD on Line 7. This should be the daily rate posted at surface lots and garages within one-half-mile of stations in the CBD. It is not necessary to take subsidized parking into account; simply enter the posted rate. the system Lines 8-11 presume that your proposed project connects to an existing fixed-guideway transit system, meaning a rail system or a BRT system with dedicated lanes. If it is the initial leg of a new fixed-guideway system, the entries for 8-11 will be zero. Using the U.S. Census LEHD or another reliable source, calculate the number of jobs within one-half-mile of all existing fixed-guideway stations on the system. This calculation should not include new stations proposed as part of the investment. stations in the system Using the U.S. Census or another reliable source, calculate the number of people residing within one-half-mile of all existing stations on the fixed-guideway transit system. This calculation should not include new stations proposed as part of the project. Line 10: Retail, entertainment, and food jobs within ½-mile of Line 8: Jobs within ½-mile of all fixed-guideway stations in Line 9: Population within ½-mile of all fixed-guideway all fixed-guideway stations in the system This jobs category is an aggregate of NAICS codes 41-42 (Retail Trade), 71 (Arts, Entertainment, and Recreation), and 72 (Accommodation and Food Services). Using the U.S. Census LEHD or another reliable source, calcu- late the number of jobs in these categories within a half-mile of all exist- ing stations. This calculation should not include new stations proposed as part of the project. User-supplied values are preferred. However, if the user is unable to cal- culate this input for all station catchments in the system, the line can be left blank. In this case, the tool uses the user-supplied value for total The parkTIP ing price may serve as a proxy for other factors in addition to the cost of parking a car during the work day. For example, parking price is also indicative of the size of the CBD and its density. Therefore, using the tool for sensitivity analyses to test the impact of changing the parking price is not advised. For this analysis, “fixed- guideway transit system” means that part of the regional transit system that operates within a dedicated, exclusive right- of-way. It may include HRT, LRT, commuter rail, or BRT that operates in exclusive lanes. TIP

Transit Cooperative Research Program1-30 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS number of catchment jobs in the system and the fraction of jobs that fall into this category to estimate the number of retail, entertainment, food, and accommodation jobs near stations. For many metropolitan areas, a local value for the fraction is provided by the tool based on values for the principal city. For the remaining metropolitan areas, the median value from existing systems is used. stations in the system Line 11: Higher wage jobs within ½-mile of all fixed-guideway As in Line 5, “higher wage jobs” refers to jobs in the Earn3 category of the U.S. Census LEHD data; that is, jobs earning greater than $3,333 per month. Using LEHD or another reliable source, calculate the number of jobs in this category within one-half-mile of all existing stations. This cal- culation should not include new stations proposed as part of the invest- ment. User-supplied values are preferred. However, if the user is unable to calcu- late this input for all station catchments in the system, the line can be left blank. In this case, the tool uses the user-supplied value for total number of catchment jobs in the system and the fraction of jobs that have wages over $3,333 per month to estimate the number of high-wage jobs near stations. For many metropolitan areas, a local value for the fraction is pro- vided by the tool based on values for the principal city. For the remaining metropolitan areas, the median value from existing systems is used. Line 12: Average daily VMT per freeway lane mile from FHWA The VMT per highway lane gives an indication of congestion on the MSA’s freeway system (the competing mode). To get inputs for this line, refer to Table HM-72 (2008) from the Federal Highway Administration (FHWA), which is available at: http://www.wa.dot.gov/policyinformation/statistics/2008/ hm72.cfm The right-hand column in Table HM-72 (Average Daily Traffic per Free- way Lane) gives the total VMT on freeways divided by freeway lane miles for each MSA. This information is also included in the spread- sheet tool under the FHWA REFERENCE tab.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-31 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Line 13: Select cost method Using the drop-down menu, select the approach to capital costing. A user-supplied total cost or user-supplied cost per mile estimate is pre- ferred because it is likely to be more accurate than the costing routine within the spreadsheet tool. Where these are not available, however, the tool can provide a rough order of magnitude estimate based on the variables in the cost input panel and the other projects in the database. Complete Lines 14 through 17 only if the tool is to provide the cost esti- mate. Line 14: Number of stations Enter the number of new stations on the proposed transit investment. Inputs 13 through 20, shown in Figure 13, provide the basis for a capital cost estimate. Figure 13: Cost Input Panel

Transit Cooperative Research Program1-32 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Line 15: % alignment below grade Enter the percent of the alignment that is below grade in a trench or sub- way. For example: If 5 percent of the proposed alignment would be in a subway and 3.5 percent would be in an open trench, the user would enter “8.5.” Line 16: Type of project Select the type of project from the drop-down list. One of four project types can be selected: 1. New projects are those that add the first fixed-guideway transit line in the region. 2. Extensions are projects that extend an existing fixed-guideway line by adding new track and stations beyond the current terminus. 3. Expansions add a new fixed-guideway line to an existing system. The new line could be of a different mode, such as adding a fixed- guideway BRT line to a system that currently operates urban rail. 4. Enhancements improve the service of a line by adding new stations on existing rights-of-way without adding route miles to the system. Line 17: Mode Select the mode: HRT (heavy rail), LRT (light rail transit), or BRT (bus rapid transit). Line 18: Route Miles of the Project Enter the length of the proposed transit investment in miles.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-33 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Line 19: User-estimated capital cost per mile Enter the capital cost per mile for the proposed investment in 2009 dol- lars. Line 20: User-estimated total capital cost Enter the total capital costs for the proposed investment in 2009 dollars. If the user has an estimate for capital costs, use it rather than the estimate produced by the Cost Calculator. When all of the yellow fields are complete, press the “Update the Results” button at the bottom of the screen. The inputs from the first pages are mul- tiplied by coefficients determined through statistical analysis of existing sys- tems and summed to produce estimates for average weekday riders on the project, the change in system-wide annual passenger-miles traveled (PMT), average weekday riders, and capital cost. Click the OUTPUTS tab to view the results. 3.3 Outputs: Results and What They Mean The spreadsheet tool offers three different output screens: 1. Project Ridership Output, showing estimated weekday project rider- ship and capital cost per rider, with confidence intervals. 2. Capital Costs Output, showing estimated total capital cost and capi- tal cost per directional route mile in 2009 dollars. 3. System-wide PMT Output, showing expected new PMT on the sys- tem and capital cost per new PMT. To arrive at these outputs, the spreadsheet tool relies on coefficients derived from the regression analysis. The tool calculates the project-level ridership and cost by multiplying each input by its relevant coefficient and then sum- ming the results. The incremental PMT is calculated by subtracting an esti- mate of PMT on the committed network from the PMT on a network that includes both the proposed project and the committed network. The model outputs are based on a fit to data which shows natural variation, or scatter. To take this into account, the output panel presents not only the ridership estimate for Your Project but also a range of uncertainty. The Upper Limit and Lower Limit forecasts are derived from a variance-covariance matrix gener- ated during the modeling process. The uncertainty in the ridership estimates is on the order of 20 percent. If the input data is for a recent year—e.g., if 2010 census data was the source of the population and employment inputs—then the ridership estimate TIP TIP Although it is possible to navigate to the OUTPUTS tab using the worksheet tabs at the bottom of the screen, users should use the “Update the Results” button when they want to see their results. The button initiates a macro that updates the column chart on the OUTPUTS tab. The spreadsheet tool may not reflect the user’s most recent inputs if the Update button is not used. For the most reliable results, the user’s cost estimate should be used if at all possible. Enter it either at Line 19 or Line 20, depending on whether an estimated cost per mile or total capital cost is being used.

Transit Cooperative Research Program1-34 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS The output screen in Figure 14 compares the average weekday riders esti- mated for a hypothetical project (Your Project) with the ridership on similar projects in the database. The estimated number of riders predicted for Your Project on an average weekday is shown in the bar chart alongside the actual ridership on projects of the same type (new projects, extensions, expansions, and enhancements as described in the Line 16 instructions above). An Upper Limit and Lower Limit are also provided to illustrate the range of uncertainty in the forecast. Users can compare ridership on Your Project with all projects in the database by referring either to Table A-1 in the appendix to this hand- book or to the REFERENCE VALUES tab in the spreadsheet tool. Since the database includes a wide variety of projects in different modes and city sizes, users may choose to focus on a subset of projects that are similar to the one being evaluated. For example, if the user is considering an LRT project in a medium-sized regional city, the forecast ridership would best be compared with the Portland Interstate MAX and Minneapolis Hiawatha Cor- ridor projects as opposed to the Miami Metrorail or the Chicago Orange Line. Figure 14: Output Panel on Project Ridership would be for that year, as if the project were already in place. If the corridor- level input data is a forecast for a future year, then the project-level rider- ship estimate would be for that future year. The spreadsheet tool does not account for regional growth, however, so an estimate of future year ridership reflecting anticipated growth in station-area jobs and population will tend to be conservative.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-35 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 15: Output Panel on Capital Costs The output panel in Figure 15 shows the proposed project’s estimated capital cost per average weekday rider along with other projects in the database with a similar capital cost per rider. Your Project appears likely to have a capi- tal cost per rider similar to other projects, giving users confidence in their project’s potential for success. Users can compare Your Project’s capital cost per rider with that of all projects in the database using Table A-1 in the ap- pendix. Capital cost per rider can be useful in a multi-criteria evaluation, but as has been noted previously, this one metric should not be considered to be the ultimate determinant of a project’s success. The Bay Area Rapid Transit (BART) extension to San Francisco Airport has the second-highest capital cost per rider of the projects in the database. Nevertheless, many consider the proj- ect to be successful because its operating costs are covered by fares and the project saves users from paying the much higher cost of airport parking or taxi service. The capital cost per rider computed by the spreadsheet is not directly com- parable with FTA’s cost effectiveness metric and breakpoints. The FTA’s cost per rider metric for cost effectiveness annualizes both the capital cost and the ridership projection, and includes annual operating and maintenance costs as well. The spreadsheet tool simply divides the total estimated capital cost by the anticipated average weekday ridership.

Transit Cooperative Research Program1-36 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 16: Output Panel on System-wide PMT Figure 16 compares Your Project with projects in metropolitan areas of simi- lar size in terms of its potential to change PMT. The estimate for Your Project shows that it will have a positive effect on ridership system-wide, and that the impact on PMT is comparable to other projects in similar sized areas, offering further evidence that the project can be a success. In a similar fashion to Figure 11, Figure 16 compares the project being con- sidered with the database projects in terms of its potential to change PMT. It should be noted that in cases where the forecast PMT increment is less than zero, the output panel will display Negligible in place of the estimate. All other values on the panel will be displayed as NA and the plot will show the incremental PMT as being equal to zero. As the cost and ridership are projected by entirely different models, none of the other outputs are affected and those values are still entirely legitimate even if the PMT model fails to produce a valid result. The negligible assumption was made because it is possible that negative pre- dictions fall within the error of the model and therefore are in actuality zero. Alternatively, it is possible to explain legitimate negative increments through diversion of service or increased efficiency of the overall system. For a com- plete discussion of how TCRP Project H-42 investigated negative PMT incre- ments, see the full report in Volume 2.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-37 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS 3.4 Using the Tool to Compare Scenarios Although the initial outputs resulting from a single scenario of project and corridor characteristics can be of interest as a starting point for analysis, the spreadsheet offers additional value as a tool for comparing different What-if? scenarios. By changing the inputs, the user can test how project-level rider- ship and the amount of new PMT might change under a different set of as- sumptions. New scenarios might include: • Changes to the project characteristics, such as adding more stations or moving the stations to locations with different densities. • Changes to the corridor characteristics, such as the assumed popula- tion and employment density. In such a way, the ridership outcome from different forecast years and public policy options can be as- sessed. • Comparing the ridership potential of different corridors within the same region. The results might help prioritize corridors. The spreadsheet tool does not currently include a save function, nor does it allow the user to compare the results of different scenarios side-by-side. Thus, users will need to record the results of each scenario and compare them outside the tool, perhaps in a Microsoft Word or Excel file. To enter a new scenario, click on the Adjust the Inputs button. This button will take users back to the USER DATA ENTRY tab. After making any necessary adjustments, navigate back to the OUTPUTS tab using the Update the Results button.

Transit Cooperative Research Program1-38 Understanding the qualitative factors that can enhance or hinder ridership can help you interpret the spreadsheet’s output for your project. SECTION 4 Other Factors 4.1 Other Factors Affecting Ridership The quantitative factors included in the spreadsheet tool capture many, but not all, of the factors that can lead to the success of a transit project. The liter- ature search and case studies conducted as part of TCRP Project H-42 identi- fied other and somewhat less quantifiable factors that can also contribute to the ridership on a fixed-guideway transit project. These factors may explain some of the outliers in Figure 14, and would be expected to increase (or de- crease) ridership in comparison to levels estimated by the spreadsheet tool. • Transit service and pricing – Transit ridership tends to be particularly sensitive to service levels and the cost paid by riders. The typical demand forecasting model is highly sensitive to such variables as transit travel time, peak and off-peak headways, average fares, and parking fees, reflecting research on travel behavior. Section 2.4 not- ed that one of the unexpected results of this research was that the regression analysis did not show transit service levels or pricing to be significant indicators of ridership. It is assumed that this is because service levels and fares are implicit to some of the other indicators, such as density, highway congestion levels, and percent of the line that is at grade. If your project would have higher (or lower) service than is typical for projects in the database, or lower (or higher) cost paid by the user, it may attract higher (or lower) ridership. • “Transit First” policies – Those places that give transit priority for funding and street capacity, that impose tolls on automobiles, and that limit the supply of parking or raise the price of parking, can attract higher ridership by reducing the relative cost of transit, or increasing its relative speed, compared to automobiles. • Special generators – Sporting venues, universities and colleges, and other special generators can increase ridership. Forecasts produced by the spreadsheet tool assume that a corridor has about the same number of special generators as the projects in the database. Where there are more (or fewer) special generators than average for the other projects, ridership is likely to be higher (or lower).

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-39 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS • Walkability near stations – Transit ridership tends to be higher where stations are easily accessible on foot, including access that is direct, safe, and interesting. • Preference for rail – The spreadsheet tool predicts ridership based on the input variables described in Section 3.2, and is agnostic with re- gard to the transit technology (e.g., LRT, HRT, or fixed-guideway BRT). However, FTA has found that fixed-guideway projects in general and rail in particular can attract riders based on certain attributes—such as a rider’s perception of comfort and reliability—that are not well represented in traditional travel forecasting models. When these unincluded attributes are taken into account, ridership forecasts for a rail alternative and a BRT alternative may differ even if they are iden- tical in terms of frequency, travel time, station locations, and fares. 4.2 Other Goals Beyond Ridership and Capital Cost As noted throughout this handbook, ridership and capital cost per rider are not the only measures of success for a fixed-guideway transit project. Other motivations for considering a fixed-guideway transit project, or for selecting one alternative over another, can include: • Shaping future growth and development – Transit success is often defined in terms of its ability to shape settlement patterns and increase land values. An important consideration can thus be the development potential around existing and proposed stations. This potential can be greatly affected by land availability, land use regula- tions, and the real estate market. • Reducing operating costs – A project that increases transit vehicle speed can mean that fewer vehicles are needed to provide the same frequency of service. BRT with such features as skip stop service, lev- el boarding, signal priority, and off-board fare collection can reduce run time, meaning that fewer buses are needed to provide the same passenger-carrying capacity. Fewer buses might be needed to offer the same number of bus runs in a day, thus offering greater service while lowering operating costs. • Promoting social and geographic equity – This can include mobility improvement for disadvantaged individuals, populations, or regions, as well as an equitable allocation of benefits and resources. Some transit agencies, such as Sound Transit in the Seattle metropolitan area, are required to spend funds in the jurisdiction where they are collected. Although project-level ridership and PMT change can be related to these goals, they may not be the best indicators of potential success in achieving them. The reasons for undertaking a transit project extend beyond achieving a certain ridership target.

Transit Cooperative Research Program1-40 If spreadsheet analysis shows promise, it may be appropriate to invest in a more detailed corridor-level planning study. If ridership results do not appear to be favorable at this time, an incremental approach to transit system development could be valuable. SECTION 5 What Next? 5.1 Examining Expectations in Light of Fixed- Guideway Success Indicators The indicators of success presented in this handbook are only the begin- ning. If a corridor or project is shown to have good potential for attracting ridership commensurate with its cost, the next step may be more detailed corridor-level planning studies of transit needs and alternative solutions. These studies would typically include the use of travel demand forecasting models, conceptual engineering, environmental studies, and stakeholder in- volvement. Potential funding sources might be identified. Transit visioning at the regional scale may help put the project in context and facilitate funding support. If the spreadsheet analysis yields less-favorable results, the story may not be over either. Consider the goals of the proposed transit project, and what suc- cess would look like. Consider whether or not those expectations are realistic. It may be that a different type of transit project—perhaps with a lower cost— would be a better fit for the travel markets and available funding. Success can often be achieved by starting with a smaller initial transit investment, building up ridership over time as the corridor grows and as transit support- ive policies take effect, and incrementally adding to the system’s service and infrastructure. 5.2 Conducting a More Detailed Study In the United States, the MAP-21 (Moving Ahead for Progress in the 21st Cen- tury Act) legislation enacted in 2012 lays out a new procedural structure for the planning and development of fixed-guideway transit projects that utilize federal funds under the FTA’s New Starts and Small Starts program. Specific guidance from the FTA is not available at this writing, but Figure 17 illustrates the major steps.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-41 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 17: New Starts Planning and Development Process under MAP-21 Source: Adapted from Federal Transit Administration, Capital Investment Program Listening Session, September 2012 Planning Project Development Engineering Full Funding Grant Agreement Complete environmental review process, including developing and reviewing alternatives, selecting locally preferred alternative, and adopting it into the fiscally constrained long-range transportation plan Gain commitments of all non-New Starts funding Complete sufficient engineering and design Construction = FTA approval = FTA evaluation, rating, approval Transit planning typically involves both regional system-level studies and corridor-level studies. Regional visioning and system planning can play an important role in understanding travel markets, understanding needs, and setting policies and priorities. Corridor studies offer the focus needed to develop service strategies and to examine alternative modes, alignments, station locations, termini, etc., at an appropriate scale for decision-making. Conventional wisdom among transit planners is that there are usually too many options—too many potential combinations and permutations of ser- vice levels, mode, and alignment—to reach mode and alignment decisions in a considered fashion at a regional scale. While MAP-21 removes the federal requirement for stand-alone corridor- level alternatives analysis studies, FTA’s alternatives analysis framework still offers one model for conducting corridor-level planning studies to reach decisions on the mode, general alignment, and termini for a transit project. Corridor-level transit planning following similar approaches is widely prac- ticed around the world. The alternatives analysis framework for corridor-level planning studies includes the steps shown in Figure 18, with agency and stakeholder involvement continuing throughout. Depending on the complexity of the corridor, corridor planning can precede or be folded in with more detailed project development, which considers design options (e.g., the precise alignment, station locations, yard and shop, etc.). Under MAP-21, the National Environmental Policy Act (NEPA) process is completed during the project development phase, along with the engi- neering necessary to support NEPA. FTA’s approval of a project into the sub- sequent engineering phase hinges on how well the project meets statutory criteria for project justification and local financial commitment.

Transit Cooperative Research Program1-42 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS Figure 18: Technical Framework for Corridor-Level Planning Study Operations planning Travel forecasting Conceptual engineering Cost estimating Social, economic, and environmental impact assessment Financial planning Mode, general alignment, termini Financial plan Project management plan Problem Definition and Scoping Development of Alternatives and Methodologies Documentation and Presentation of Results Selection of Locally Preferred Alternative Analysis and Refinement of Alternatives Source: Parsons Brinckerhoff, based on FTA’s Procedures and Technical Methods for Transit Project Planning (12)

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-43 NEXTOVERVIEW METHOD SPREADSHEET OTHER FACTORS 5.3 Overview of Funding Options for Fixed-Guideway Transit Next steps include identifying and securing funds to build the project, as well as to operate and maintain it. In the United States, the primary federal fund- ing source for fixed-guideway transit is the New Starts and Small Starts pro- gram administered by FTA. Funds are awarded on a discretionary basis, and projects must meet certain criteria defined in law and regulation in order to compete successfully for funds. The New Starts share for successful projects tends to be no more than 50 percent of the capital cost, with most of the op- erating and maintenance cost covered by fares and local funds. Nevertheless, the opportunity for discretionary funds makes the program very appealing, and the demand for funds exceeds the money available. Other federal funding sources and financial support mechanisms are avail- able. Flexible funds authorized under Title 23 (Highways) may be used for transit projects. These include funds made available to states and MPOs un- der the Surface Transportation Program (STP) and the Congestion Mitigation and Air Quality (CMAQ) Program. In recent years, federal funds have been available through the discretionary TIGER (Transportation Investment Gener- ating Economic Recovery) grant program. Financing help is available through TIFIA (Transportation Infrastructure Finance and Innovation Act). State and local funding sources for transit are many and varied, ranging from beer taxes in Alabama to video poker in Oregon. Dedicated sales taxes and excise taxes are often used, as they are stable and reliable and provide a ro- bust enough funding stream to support a transit capital program while also supporting operations. Value capture tools such as assessment districts and tax increment financing are of interest in many places. Reports on federal, state, and local funding options for fixed-guideway tran- sit are available online at such websites as: http://www.trb.org/publications/pubstcrppublications.aspx http://apta.com/resources/reportsandpublications/Pages/default.aspx http://t4america.org http://www.cfte.org

Transit Cooperative Research Program1-44 REFERENCES 1. Pushkarev, B., and J. Zupan. Public Transportation and Land Use Policy. Indiana University Press, Bloomington, 1977. 2. Pushkarev, B., J. Zupan, and R.S. Cumella. Urban Rail in America: An Explo- ration of Criteria for Fixed-Guideway Transit. Indiana University Press, Bloomington, 1982. 3. American Public Transportation Association. 2012 Public Transportation Fact Book, Appendix A: Historical Tables. Washington, D.C., 2012. 5. Chatman, D., et al. TCRP Report 167: Making Effective Fixed-Guideway Tran- sit Investments: Indicators of Success, Vol. 2: Research Report. Transpor- tation Research Board of the National Academies, Washington, D.C., 2014. 6. Regional Plan Association. Where Transit Works: Urban Densities for Public Transportation. New York, 1976. 8. Metropolitan Transportation Commission Resolution 3434: Regional T T ransit Expansion Program, 2008. www.mtc.ca.gov/planning/rtep/ Cambridge Systematics, Inc. and Transportation Analytics. Draft Transit Competitive Index Primer. Metropolitan Transportation Commission, ransit Sustainability Project. San Francisco, Calif., 2012. 10. Metro. Regional High Capacity Transit System Plan 2035: Summary Report. Portland, Ore., 2010. .9 11. Cervero, R., and E. Guerra. “To T or Not to T: A Ballpark Assessment of the Costs and Benefits of Urban Rail Transportation," Public Works and Management, April 2011. 12. Federal Transit Administration, U.S. Department of Transportation. Pro- cedures and Technical Methods for Transit Project Planning. www.fta. dot.gov/12304_2396.html, accessed September 2012. 4. Parsons Brinckerhoff. TCRP Report 16: Transit and Urban Form, Volume 2, Part III, A Guidebook for Practitioners. TRB, National Research Council, Washington, D.C., 1996. 7. Institute of Transportation Engineers. A Toolbox for Alleviating Traffic Con- gestion. Washington, D.C.,1989.

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-45 APTA – American Public Transportation Association BART – Bay Area Rapid Transit (San Francisco) BEA – Bureau of Economic Aairs BRT – Bus Rapid Transit CBD – Central Business District CMAQ – Congestion Mitigation and Air Quality CR – Commuter Rail DRM – Directional Route Miles FFGA – Full Funding Grant Agreement FHWA – Federal Highway Administration FTA – Federal Transit Administration GDP – Gross Domestic Product GIS – Geographical Information System HRT – Heavy Rail Transit LEHD – Longitudinal Employer-Household Dynamics LRT – Light Rail Transit MAP-21 – Moving Ahead for Progress in the 21st Century Act MPO – Metropolitan Planning Organization MSA – Metropolitan Statistical Area MTC – San Francisco Bay Area’s Metropolitan Transportation Commission NAICS – North American Industry ClassiŒcation System NEPA – National Environmental Policy Act NCDC – National Climatic Data Center NHTS – National Household Travel Survey NTD – National Transit Database PMT – Passenger-Miles Traveled ROW – Right-of-Way STP – Surface Transportation Program TCRP – Transit Cooperative Research Program TIFIA – Transportation Infrastructure Finance and Innovation Act TIGER – Transportation Investment Generating Economic Recovery (Discretionary Grant Program) TOD – Transit-Oriented Development TRB – Transportation Research Board of the National Academies TTI – Texas Transportation Institute VMT – Vehicle-Miles Traveled ABBREVIATIONS AND ACRONYMS

Transit Cooperative Research Program1-46 City & Project Type Average Weekday Ridership Annual System PMT Capital Cost (millions) Cost per Route Mile (millions) Cost per Rider (millions) Cleveland Healthline Expansion 12,850 276,271 $197 $29 $0.0153 Eugene EMX Initial 6,600 $26 $6 $0.0039 Los Angeles Orange Line Expansion 21,940 3,098,253 $371 $27 $0.0169 Chicago Metra North Central Expansion 2,201 3,880,511 $247 $4 $0.1123 Chicago Metra South Central Extension 4,125 3,880,511 $211 $19 $0.0512 Miami South Florida Tri-Rail Upgrades Enhancement 36,510 822,877 $394 $5 $0.0108 Atlanta North / South Line Expansion 113,948 861,297 $3,194 $144 $0.0280 Atlanta North Line Dunwoody Extension Extension 9,381 861,297 $611 $328 $0.0651 Baltimore Metro Initial 39,023 680,319 $2,040 $170 $0.0523 Chicago Douglas Branch Extension 16,035 3,880,511 $503 $76 $0.0313 Chicago O'Hare Extension (Blue Line) Extension 21,350 3,880,511 $469 $62 $0.0220 Chicago Orange Line Expansion 32,334 3,880,511 $778 $86 $0.0241 Los Angeles Red Line (Segment 1) Expansion 26,073 3,098,253 $2,566 $755 $0.0984 Los Angeles Red Line (Segment 2) Expansion 45,410 3,098,253 $2,891 $445 $0.0637 Los Angeles Red Line (Segment 3) Expansion 30,138 3,098,253 $1,733 $259 $0.0575 Miami Metrorail Initial 58,121 822,877 $2,366 $113 $0.0407 Philadelphia SEPTA Frankford Rehab. Enhancement 45,103 1,588,477 $1,186 $235 $0.0263 San Francisco BART Extension Extension 19,501 2,372,623 $1,598 $184 $0.0820 Baltimore – Three Extensions Extension 4,448 680,319 $140 $21 $0.0314 Baltimore Central Line Expansion 24,541 680,319 $531 $23 $0.0216 Buffalo Metro Rail Initial 24,076 78,709 $951 $149 $0.0395 Dallas North Central Extension 12,304 478,539 $450 $36 $0.0366 Dallas S&W Oak Cliff and Park Lane Extension 46,713 478,539 $1,137 $57 $0.0243 Denver Central Corridor Expansion 36,403 454,082 $161 $30 $0.0044 Denver Southeast (T-REX) Expansion 16,298 454,082 $876 $46 $0.0538 Denver Southwest Corridor Initial 8,728 454,082 $228 $26 $0.0262 Los Angeles Green Line Expansion 30,935 3,098,253 $1,225 $61 $0.0396 APPENDIX: SUMMARY OF THE TCRP PROJECT H-42 DATABASE Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Type: • Initial – first fixed-guideway transit line in the region • Extension – makes an existing line longer • Expansion – adds a new line to an existing system • Enhancement – adds stations (without extending line) Table A-1: Overview of Projects

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-47 City & Project Type Average Weekday Ridership Annual System PMT Capital Cost (millions) Cost per Route Mile (millions) Cost per Rider (millions) Los Angeles Long Beach Blue Line Initial 79,349 3,098,253 $1,658 $37 $0.0209 Minneapolis Hiawatha Corridor Initial 30,518 387,148 $454 $38 $0.0149 New York – Newark Elizabeth MOS-1 Expansion 1,065 $214 $214 $0.2009 New York Hudson-Bergen MOS 1 and 2 Expansion 40,100 $1,809 $117 $0.0451 Pasadena Gold Line Expansion 23,681 3,098,253 $1,022 $73 $0.0432 Phoenix Metro Light Rail Initial 40,772 $1,231 $62 $0.0302 Portland Airport Max Expansion 3,005 460,769 $156 $28 $0.0520 Portland Interstate MAX LRT Expansion 7,992 460,769 $333 $57 $0.0417 Portland MAX Segment I Initial 60,229 460,769 $508 $33 $0.0084 Portland Westside/Hillsboro MAX Expansion 34,223 460,769 $1,320 $74 $0.0386 Sacramento Folsom Corridor Extension 6,587 161,049 $274 $25 $0.0417 Sacramento Mather Field Road Extension Extension 6,711 161,049 $44 $7 $0.0066 Sacramento South Phase 1 Expansion 9,877 161,049 $225 $36 $0.0228 Sacramento Stage I Initial 31,071 161,049 $360 $20 $0.0116 Salt Lake City Medical Center Extension Extension 3,358 241,549 $87 $57 $0.0259 Salt Lake City North South Corridor Initial 31,405 241,549 $412 $27 $0.0131 Salt Lake City University Extension Expansion 7,285 241,549 $111 $44 $0.0152 San Diego Blue Line Initial 41,361 544,326 $986 $39 $0.0238 San Diego Mission Valley East Expansion 4,203 544,326 $521 $88 $0.1241 San Diego Orange Line Expansion 23,113 544,326 $633 $29 $0.0274 San Jose North Corridor Initial 11,272 188,422 $757 $46 $0.0672 San Jose Tasman East Expansion 3,340 188,422 $335 $68 $0.1003 San Jose Tasman West Expansion 1,977 188,422 $416 $55 $0.2106 San Jose VTA Capitol Segment Extension 2,385 188,422 $205 $64 $0.0860 San Jose VTA Vasona Segment Expansion 3,848 188,422 $374 $73 $0.0973 Seattle Central Link Initial 19,719 $2,583 $186 $0.1310 Trenton – Southern New Jersey Light Rail Transit System Expansion 8,150 $1,166 $42 $0.1430 Table A-1: Overview of Projects, cont’d.

Transit Cooperative Research Program1-48 Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Job Categories: • Leisure – all jobs in retail, entertainment, food • Higher-income – more than $3,333 per monthTable counts people and jobs within 1/2-mile radius of proposed stations CBD parking rate is price for 6- to 24-hour stay Table A-2: Project Area Characteristics (within 1/2-mile of proposed stations) City & Project Total Jobs Total Population Leisure Jobs Higher- income Jobs Percent of Project At Grade CBD Parking Rate Cleveland Healthline 114,837 32,797 11,148 58,791 100.00% $11.71 Eugene EMX 27,994 17,128 4,811 11,112 1 4 Los Angeles Orange Line 46,107 83,112 9,642 21,627 100.00% $14.76 Chicago Metra North Central 23,971 34,463 2,189 10,632 $28.80 Chicago Metra South Central 14,978 35,312 1,668 6,544 $28.80 Miami South Florida Tri-Rail Upgrades 74,554 48,714 6,817 31,830 $9.00 Atlanta North / South Line 176,597 47,472 24,577 95,131 38.00% $6.78 Atlanta North Line Dunwoody Extension 16,327 4,253 1,561 10,915 36.00% $6.78 Baltimore Metro 72,145 59,848 7,766 39,443 25.00% $13.86 Chicago Douglas Branch 28,652 115,554 3,319 11,273 11.00% $28.80 Chicago O'Hare Extension (Blue Line) 30,026 10,811 4,556 16,076 93.00% $28.80 Chicago Orange Line 20,176 65,718 6,946 5,635 0.00% $28.80 Los Angeles Red Line (Segment 1) 136,311 48,170 16,566 86,502 15.00% $14.76 Los Angeles Red Line (Segment 2) 70,634 174,905 14,419 27,012 0.00% $14.76 Los Angeles Red Line (Segment 3) 25,292 28,817 6,234 10,461 0.00% $14.76 Miami Metrorail 146,439 109,235 22,758 69,812 2.00% $9.00 Philadelphia SEPTA Frankford Rehab. 21,056 102,181 3,432 8,007 0.00% $24.00 San Francisco BART Extension 20,583 10,727 5,677 9,479 16.00% $30.40 Baltimore – Three Extensions 27,985 5,510 3,009 17,482 99.00% $13.86 Baltimore Central Line 68,690 57,014 12,125 32,949 99.00% $13.86 Buffalo Metro Rail 65,298 45,417 6,249 28,857 18.00% $6.79 Dallas North Central 57,228 20,750 7,738 31,078 81.00% $5.89 Dallas S&W Oak Cliff and Park Lane 145,557 68,864 20,663 80,905 70.50% $5.89 Denver Central Corridor 96,104 25,269 13,039 54,758 91.00% $12.53 Denver Southeast (T-REX) 86,349 26,811 14,152 48,337 100.00% $12.53 Denver Southwest Corridor 16,780 9,893 2,319 6,548 83.00% $12.53 Los Angeles Green Line 66,818 74,088 7,932 45,986 62.00% $14.76

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-49 City & Project Total Jobs Total Population Leisure Jobs Higher- income Jobs Percent of Project At Grade CBD Parking Rate Los Angeles Long Beach Blue Line 185,178 180,511 23,870 81,408 81.00% $14.76 Minneapolis Hiawatha Corridor 167,692 42,224 23,664 102,871 72.00% $10.83 New York – Newark Elizabeth MOS-1 7,742 8,894 789 4,307 85.00% $37.71 New York Hudson-Bergen MOS 1 and 2 88,742 211,414 13,418 54,265 83.00% $37.71 Pasadena Gold Line 80,661 93,893 20,988 35,331 71.00% $14.76 Phoenix Metro Light Rail 187,816 74,135 25,006 91,832 96.00% $5.09 Portland Airport Max 5,319 3,108 1,507 1,672 100.00% $8.75 Portland Interstate MAX LRT 16,343 18,279 3,286 7,122 88.00% $8.75 Portland MAX Segment I 116,225 63,679 21,139 55,390 65.00% $8.75 Portland Westside/Hillsboro MAX 64,900 50,141 16,215 27,163 81.00% $8.75 Sacramento Folsom Corridor 40,202 15,579 7,145 22,082 99.00% $11.83 Sacramento Mather Field Road Extension 7,599 18,996 1,664 3,111 97.00% $11.83 Sacramento South Phase 1 9,559 27,610 1,729 3,703 98.00% $11.83 Sacramento Stage I 63,851 42,573 10,007 32,000 100.00% $11.83 Salt Lake City Medical Center Extension 22,057 1,709 110 10,862 $12.00 Salt Lake City North South Corridor 74,476 27,619 16,805 28,614 99.00% $12.00 Salt Lake City University Extension 17,532 15,945 3,463 7,583 100.00% $12.00 San Diego Blue Line 143,832 88,169 34,071 69,035 85.00% $16.25 San Diego Mission Valley East 10,650 18,710 2,510 3,369 56.00% $16.25 San Diego Orange Line 38,798 81,575 14,465 12,719 97.00% $16.25 San Jose North Corridor 99,786 49,992 13,308 64,700 100.00% $14.17 San Jose Tasman East 17,452 20,494 3,269 11,198 73.00% $14.17 San Jose Tasman West 38,728 15,101 1,367 32,813 95.00% $14.17 San Jose VTA Capitol Segment 4,819 29,645 1,847 1,654 100.00% $14.17 San Jose VTA Vasona Segment 26,618 36,163 6,641 14,572 92.00% $14.17 Seattle Central Link 161,394 61,817 22,591 99,498 41.50% $21.96 Trenton – Southern New Jersey Light Rail Transit System 24,910 64,862 2,233 13,548 100.00% $24.00 Table A-2: Project Area Characteristics, cont’d.

Transit Cooperative Research Program1-50 City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Cleveland Healthline 82,231 101,616 8,489 33,812 Eugene EMX Los Angeles Orange Line 748,613 762,662 117,217 326,956 Chicago Metra North Central 1,588,959 2,177,973 233,255 752,772 Chicago Metra South Central 1,597,952 2,177,124 233,775 756,861 Miami South Florida Tri-Rail Upgrades 128,135 112,926 24,489 48,829 Atlanta North / South Line 136,456 57,930 18,398 51,520 Atlanta North Line Dunwoody Extension 296,727 101,149 41,415 135,736 Baltimore Metro 205,248 116,964 28,730 89,147 Chicago Douglas Branch 1,584,278 2,096,882 232,124 752,131 Chicago O'Hare Extension (Blue Line) 1,582,904 2,201,625 230,887 747,328 Chicago Orange Line 1,592,754 2,146,718 228,497 757,769 Los Angeles Red Line (Segment 1) 658,409 797,604 110,292 262,082 Los Angeles Red Line (Segment 2) 724,086 670,870 112,440 321,572 Los Angeles Red Line (Segment 3) 769,428 816,957 120,625 338,122 Miami Metrorail 56,251 52,405 8,548 10,847 Philadelphia SEPTA Frankford Rehab. 938,729 1,395,396 143,566 427,490 San Francisco BART Extension 671,496 803,545 127,592 357,201 Baltimore – Three Extensions 249,408 171,302 33,487 111,108 Baltimore Central Line 208,703 119,798 24,371 95,641 Buffalo Metro Rail 4,215 0 -259 -1,916 Dallas North Central 222,912 94,852 30,467 107,135 Dallas S&W Oak Cliff and Park Lane 134,584 46,738 17,541 57,308 Denver Central Corridor 70,396 23,181 12,085 30,892 Denver Southeast (T-REX) 80,152 21,639 10,972 37,313 Denver Southwest Corridor 149,720 38,557 22,805 79,102 Los Angeles Green Line 727,902 771,686 118,927 302,598 Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Job Categories: • Leisure – all jobs in retail, entertainment, food • Higher-income – more than $3,333 per monthTable counts people and jobs within 1/2-mile radius of previously existing stations Table A-3: Existing Fixed-Guideway Area Characteristics (within 1/2-mile of existing stations)

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-51 City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Los Angeles Long Beach Blue Line 609,542 665,263 102,989 267,176 Minneapolis Hiawatha Corridor -7,927 52 -1,733 -11,514 New York – Newark Elizabeth MOS-1 -7,742 -8,894 -789 -4,307 New York Hudson-Bergen MOS 1 and 2 -88,742 -211,414 -13,418 -54,265 Pasadena Gold Line 714,059 751,881 105,871 313,252 Phoenix Metro Light Rail -187,816 -74,135 -25,006 -91,832 Portland Airport Max 193,341 143,860 41,236 78,332 Portland Interstate MAX LRT 182,317 128,689 39,456 72,882 Portland MAX Segment I 82,435 83,289 21,603 24,615 Portland Westside/Hillsboro MAX 133,760 96,827 26,528 52,841 Sacramento Folsom Corridor 81,085 81,537 11,959 28,538 Sacramento Mather Field Road Extension 113,689 78,120 17,441 47,509 Sacramento South Phase 1 111,729 69,506 17,375 46,917 Sacramento Stage I 57,437 54,543 9,097 18,621 Salt Lake City Medical Center Extension 92,701 46,178 23,481 29,405 Salt Lake City North South Corridor 40,282 20,268 6,787 11,652 Salt Lake City University Extension 97,225 31,942 20,129 32,683 San Diego Blue Line 119,953 123,686 27,149 43,156 San Diego Mission Valley East 253,134 193,145 58,710 108,823 San Diego Orange Line 224,986 130,280 46,754 99,472 San Jose North Corridor 170,017 179,540 24,113 108,436 San Jose Tasman East 252,350 209,038 34,152 161,938 San Jose Tasman West 231,075 214,431 36,054 140,323 San Jose VTA Capitol Segment 264,984 199,887 35,574 171,482 San Jose VTA Vasona Segment 243,184 193,370 30,780 158,565 Seattle Central Link -161,394 -61,817 -22,591 -99,498 Trenton – Southern New Jersey Light Rail Transit System -24,910 -64,862 -2,233 -13,548 Table A-3: Existing Fixed-Guideway Area Characteristics, cont’d.

Transit Cooperative Research Program1-52 City & Project Number of New Stations Percent of New Alignment Below Grade New Route Miles Cleveland Healthline 30 0.00% 7 Eugene EMX 8 0.00% 4 Los Angeles Orange Line 14 0.00% 14 Chicago Metra North Central 22 55 Chicago Metra South Central 12 11 Miami South Florida Tri-Rail Upgrades 11 72 Atlanta North / South Line 18 32.00% 22 Atlanta North Line Dunwoody Extension 2 43.00% 2 Baltimore Metro 12 50.00% 12 Chicago Douglas Branch 11 0.00% 7 Chicago O'Hare Extension (Blue Line) 4 7.00% 8 Chicago Orange Line 8 0.00% 9 Los Angeles Red Line (Segment 1) 5 85.00% 3 Los Angeles Red Line (Segment 2) 8 100.00% 7 Los Angeles Red Line (Segment 3) 3 100.00% 7 Miami Metrorail 21 0.00% 21 Philadelphia SEPTA Frankford Rehab. 11 0.00% 5 San Francisco BART Extension 5 70.00% 9 Baltimore – Three Extensions 8 0.00% 7 Baltimore Central Line 22 0.00% 23 Buffalo Metro Rail 14 82.00% 6 Dallas North Central 9 0.00% 13 Dallas S&W Oak Cliff and Park Lane 21 18.20% 20 Denver Central Corridor 12 0.00% 5 Denver Southeast (T-REX) 13 0.00% 19 Denver Southwest Corridor 5 4.00% 9 Los Angeles Green Line 14 0.00% 20 Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Table A-4: Project Characteristics

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-53 City & Project Number of New Stations Percent of New Alignment Below Grade New Route Miles Los Angeles Long Beach Blue Line 22 3.00% 45 Minneapolis Hiawatha Corridor 17 28.00% 12 New York – Newark Elizabeth MOS-1 4 15.00% 1 New York Hudson-Bergen MOS 1 and 2 23 6.00% 15 Pasadena Gold Line 13 14.00% 14 Phoenix Metro Light Rail 28 3.00% 20 Portland Airport Max 4 0.00% 6 Portland Interstate MAX LRT 10 12.00% 6 Portland MAX Segment I 25 0.00% 15 Portland Westside/Hillsboro MAX 20 17.00% 18 Sacramento Folsom Corridor 10 0.00% 11 Sacramento Mather Field Road Extension 6 0.00% 6 Sacramento South Phase 1 7 0.00% 6 Sacramento Stage I 24 0.00% 18 Salt Lake City Medical Center Extension 3 2 Salt Lake City North South Corridor 16 0.00% 15 Salt Lake City University Extension 4 0.00% 3 San Diego Blue Line 31 1.00% 25 San Diego Mission Valley East 4 8.00% 6 San Diego Orange Line 24 0.00% 22 San Jose North Corridor 22 0.00% 17 San Jose Tasman East 7 0.00% 5 San Jose Tasman West 11 5.00% 8 San Jose VTA Capitol Segment 4 0.00% 3 San Jose VTA Vasona Segment 8 6.00% 5 Seattle Central Link 11 19.10% 14 Trenton – Southern New Jersey Light Rail Transit System 20 0.00% 28 Table A-4: Project Characteristics, cont’d.

Transit Cooperative Research Program1-54 City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Cleveland Healthline 572,176 163,411 55,547 292,926 Eugene EMX 66,838 40,896 11,486 26,531 Los Angeles Orange Line 63,848 115,092 13,352 29,949 Chicago Metra North Central 30,964 44,517 2,827 13,734 Chicago Metra South Central 19,361 45,647 2,156 8,459 Miami South Florida Tri-Rail Upgrades 95,609 62,472 8,742 40,819 Atlanta North / South Line 273,123 73,419 38,010 147,128 Atlanta North Line Dunwoody Extension 22,034 5,739 2,106 14,730 Baltimore Metro 117,502 97,475 12,649 64,240 Chicago Douglas Branch 55,777 224,947 6,461 21,944 Chicago O'Hare Extension (Blue Line) 38,292 13,788 5,810 20,502 Chicago Orange Line 26,605 86,657 9,159 7,430 Los Angeles Red Line (Segment 1) 242,707 85,769 29,497 154,020 Los Angeles Red Line (Segment 2) 107,117 265,243 21,866 40,964 Los Angeles Red Line (Segment 3) 33,451 38,112 8,245 13,836 Miami Metrorail 229,941 171,523 35,735 109,620 Philadelphia SEPTA Frankford Rehab. 42,122 204,408 6,865 16,017 San Francisco BART Extension 26,250 13,680 7,239 12,088 Baltimore – Three Extensions 51,590 10,157 5,548 32,228 Baltimore Central Line 131,139 108,849 23,149 62,905 Buffalo Metro Rail 144,416 100,446 13,821 63,820 Dallas North Central 74,110 26,871 10,021 40,245 Dallas S&W Oak Cliff and Park Lane 236,706 111,988 33,603 131,569 Denver Central Corridor 271,463 71,377 36,831 154,674 Denver Southeast (T-REX) 110,792 34,401 18,158 62,020 Denver Southwest Corridor 21,551 12,706 2,978 8,410 Los Angeles Green Line 92,609 102,684 10,993 63,735 Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Job Categories: • Leisure – all jobs in retail, entertainment, food • Higher-income – more than $3,333 per month Catchment area is area within 1/2-mile radius of new stations Table A-5: Project Area Characteristics per square mile of catchment area

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-55 Table A-5: Project Area Characteristics per square mile of catchment area, cont’d. City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Los Angeles Long Beach Blue Line 286,109 278,898 36,880 125,778 Minneapolis Hiawatha Corridor 304,704 76,723 42,999 186,922 New York – Newark Elizabeth MOS-1 44,034 50,588 4,490 24,497 New York Hudson-Bergen MOS 1 and 2 163,320 389,086 24,694 99,869 Pasadena Gold Line 116,018 135,050 30,188 50,818 Phoenix Metro Light Rail 337,800 133,337 44,976 165,166 Portland Airport Max 7,483 4,373 2,120 2,352 Portland Interstate MAX LRT 31,059 34,739 6,246 13,535 Portland MAX Segment I 259,272 142,054 47,157 123,562 Portland Westside/Hillsboro MAX 117,276 90,607 29,301 49,085 Sacramento Folsom Corridor 62,138 24,079 11,044 34,131 Sacramento Mather Field Road Extension 11,722 29,303 2,566 4,799 Sacramento South Phase 1 13,391 38,679 2,422 5,188 Sacramento Stage I 139,523 93,027 21,867 69,924 Salt Lake City Medical Center Extension 48,771 3,779 244 24,016 Salt Lake City North South Corridor 131,701 48,840 29,717 50,600 Salt Lake City University Extension 34,733 31,587 6,861 15,023 San Diego Blue Line 252,054 154,510 59,707 120,979 San Diego Mission Valley East 14,029 24,647 3,306 4,437 San Diego Orange Line 60,751 127,733 22,650 19,916 San Jose North Corridor 217,027 108,730 28,945 140,719 San Jose Tasman East 28,352 33,294 5,311 18,191 San Jose Tasman West 74,520 29,058 2,631 63,140 San Jose VTA Capitol Segment 7,114 43,767 2,727 2,442 San Jose VTA Vasona Segment 46,461 63,121 11,592 25,434 Seattle Central Link 258,497 99,010 36,183 159,361 Trenton – Southern New Jersey Light Rail Transit System 40,457 105,343 3,626 22,004

Transit Cooperative Research Program1-56 Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Job Categories: • Leisure – all jobs in retail, entertainment, food • Higher-income – more than $3,333 per month Catchment area is area within 1/2-mile radius of new stations Table A-6: Metropolitan Statistical Area Characteristics per square mile of catchment area City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Cleveland Healthline 9,727 6,634 969 4,571 Eugene EMX Los Angeles Orange Line 9,457 10,065 1,510 4,148 Chicago Metra North Central 6,821 9,357 996 3,229 Chicago Metra South Central 6,821 9,357 996 3,229 Miami South Florida Tri-Rail Upgrades 5,907 4,711 912 2,351 Atlanta North / South Line 12,185 4,102 1,673 5,708 Atlanta North Line Dunwoody Extension 12,185 4,102 1,673 5,708 Baltimore Metro 7,846 5,001 1,032 3,637 Chicago Douglas Branch 6,821 9,357 996 3,229 Chicago O'Hare Extension (Blue Line) 6,821 9,357 996 3,229 Chicago Orange Line 6,821 9,357 996 3,229 Los Angeles Red Line (Segment 1) 9,457 10,065 1,510 4,148 Los Angeles Red Line (Segment 2) 9,457 10,065 1,510 4,148 Los Angeles Red Line (Segment 3) 9,457 10,065 1,510 4,148 Miami Metrorail 5,907 4,711 912 2,351 Philadelphia SEPTA Frankford Rehab. 5,791 9,036 887 2,628 San Francisco BART Extension 9,852 11,592 1,897 5,220 Baltimore – Three Extensions 7,846 5,001 1,032 3,637 Baltimore Central Line 7,846 5,001 1,032 3,637 Buffalo Metro Rail 10,981 7,175 946 4,256 Dallas North Central 9,408 3,882 1,283 4,642 Dallas S&W Oak Cliff and Park Lane 9,408 3,882 1,283 4,642 Denver Central Corridor 8,377 2,438 1,264 4,309 Denver Southeast (T-REX) 8,377 2,438 1,264 4,309 Denver Southwest Corridor 8,377 2,438 1,264 4,309 Los Angeles Green Line 9,457 10,065 1,510 4,148

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-57 Table A-6: Metropolitan Statistical Area Characteristics per square mile of catchment area, cont’d. City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Los Angeles Long Beach Blue Line 9,457 10,065 1,510 4,148 Minneapolis Hiawatha Corridor 11,133 2,946 1,528 6,366 New York – Newark Elizabeth MOS-1 New York Hudson-Bergen MOS 1 and 2 Pasadena Gold Line 9,457 10,065 1,510 4,148 Phoenix Metro Light Rail Portland Airport Max 5,700 4,217 1,226 2,295 Portland Interstate MAX LRT 5,700 4,217 1,226 2,295 Portland MAX Segment I 5,700 4,217 1,226 2,295 Portland Westside/Hillsboro MAX 5,700 4,217 1,226 2,295 Sacramento Folsom Corridor 4,721 3,780 744 1,970 Sacramento Mather Field Road Extension 4,721 3,780 744 1,970 Sacramento South Phase 1 4,721 3,780 744 1,970 Sacramento Stage I 4,721 3,780 744 1,970 Salt Lake City Medical Center Extension 7,955 3,319 1,635 2,791 Salt Lake City North South Corridor 7,955 3,319 1,635 2,791 Salt Lake City University Extension 7,955 3,319 1,635 2,791 San Diego Blue Line 5,420 4,353 1,258 2,305 San Diego Mission Valley East 5,420 4,353 1,258 2,305 San Diego Orange Line 5,420 4,353 1,258 2,305 San Jose North Corridor 5,978 5,086 829 3,836 San Jose Tasman East 5,978 5,086 829 3,836 San Jose Tasman West 5,978 5,086 829 3,836 San Jose VTA Capitol Segment 5,978 5,086 829 3,836 San Jose VTA Vasona Segment 5,978 5,086 829 3,836 Seattle Central Link Trenton – Southern New Jersey Light Rail Transit System

Transit Cooperative Research Program1-58 Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Job Categories: • Leisure – all jobs in retail, entertainment, food • Higher-income – more than $3,333 per month Table shows jobs and population within 1/2-mile radius of proposed stations, divided by number of proposed stations. Table A-7: Project Area Characteristics per station City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Cleveland Healthline 3,378 965 328 1,729 Eugene EMX 3,499 2,141 601 1,389 Los Angeles Orange Line 3,547 6,393 742 1,664 Chicago Metra North Central 1,598 2,298 146 709 Chicago Metra South Central 1,248 2,943 139 545 Miami South Florida Tri-Rail Upgrades 4,142 2,706 379 1,768 Atlanta North / South Line 9,811 2,637 1,365 5,285 Atlanta North Line Dunwoody Extension 8,164 2,126 780 5,457 Baltimore Metro 6,012 4,987 647 3,287 Chicago Douglas Branch 2,605 10,505 302 1,025 Chicago O'Hare Extension (Blue Line) 7,507 2,703 1,139 4,019 Chicago Orange Line 2,522 8,215 868 704 Los Angeles Red Line (Segment 1) 45,437 16,057 5,522 28,834 Los Angeles Red Line (Segment 2) 8,829 21,863 1,802 3,376 Los Angeles Red Line (Segment 3) 8,431 9,606 2,078 3,487 Miami Metrorail 6,973 5,202 1,084 3,324 Philadelphia SEPTA Frankford Rehab. 1,914 9,289 312 728 San Francisco BART Extension 5,146 2,682 1,419 2,370 Baltimore – Three Extensions 3,498 689 376 2,185 Baltimore Central Line 2,748 2,281 485 1,318 Buffalo Metro Rail 4,664 3,244 446 2,061 Dallas North Central 6,359 2,306 860 3,453 Dallas S&W Oak Cliff and Park Lane 6,931 3,279 984 3,853 Denver Central Corridor 8,009 2,106 1,087 4,563 Denver Southeast (T-REX) 6,642 2,062 1,089 3,718 Denver Southwest Corridor 3,356 1,979 464 1,310 Los Angeles Green Line 5,140 5,699 610 3,537

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-59 Table A-7: Project Area Characteristics per station, cont’d. City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Los Angeles Long Beach Blue Line 8,417 8,205 1,085 3,700 Minneapolis Hiawatha Corridor 9,864 2,484 1,392 6,051 New York – Newark Elizabeth MOS-1 1,548 1,779 158 861 New York Hudson-Bergen MOS 1 and 2 3,858 9,192 583 2,359 Pasadena Gold Line 6,205 7,223 1,614 2,718 Phoenix Metro Light Rail 6,708 2,648 893 3,280 Portland Airport Max 1,330 777 377 418 Portland Interstate MAX LRT 1,634 1,828 329 712 Portland MAX Segment I 4,649 2,547 846 2,216 Portland Westside/Hillsboro MAX 3,090 2,388 772 1,293 Sacramento Folsom Corridor 4,467 1,731 794 2,454 Sacramento Mather Field Road Extension 1,266 3,166 277 519 Sacramento South Phase 1 1,366 3,944 247 529 Sacramento Stage I 2,660 1,774 417 1,333 Salt Lake City Medical Center Extension 7,352 570 37 3,621 Salt Lake City North South Corridor 4,381 1,625 989 1,683 Salt Lake City University Extension 4,383 3,986 866 1,896 San Diego Blue Line 4,640 2,844 1,099 2,227 San Diego Mission Valley East 2,662 4,678 627 842 San Diego Orange Line 2,282 4,799 851 748 San Jose North Corridor 4,536 2,272 605 2,941 San Jose Tasman East 2,493 2,928 467 1,600 San Jose Tasman West 3,521 1,373 124 2,983 San Jose VTA Capitol Segment 1,205 7,411 462 414 San Jose VTA Vasona Segment 3,327 4,520 830 1,821 Seattle Central Link 12,415 4,755 1,738 7,654 Trenton – Southern New Jersey Light Rail Transit System 1,245 3,243 112 677

Transit Cooperative Research Program1-60 Key and Notes BRT – Bus Rapid Transit CR – Commuter Rail HRT – Heavy Rail Transit LRT – Light Rail Transit Job Categories: • Leisure – all jobs in retail, entertainment, food • Higher-income – more than $3,333 per month Table shows jobs and population within 1/2-mile radius of existing stations, divided by num- ber of existing stations. Table A-8: Metropolitan Statistical Area Characteristics per existing station City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Cleveland Healthline 2,346 1,600 234 1,102 Eugene EMX Los Angeles Orange Line 6,678 7,107 1,066 2,929 Chicago Metra North Central 4,233 5,807 618 2,004 Chicago Metra South Central 4,233 5,807 618 2,004 Miami South Florida Tri-Rail Upgrades 3,685 2,939 569 1,467 Atlanta North / South Line 8,238 2,774 1,131 3,859 Atlanta North Line Dunwoody Extension 8,238 2,774 1,131 3,859 Baltimore Metro 4,702 2,997 619 2,179 Chicago Douglas Branch 4,233 5,807 618 2,004 Chicago O'Hare Extension (Blue Line) 4,233 5,807 618 2,004 Chicago Orange Line 4,233 5,807 618 2,004 Los Angeles Red Line (Segment 1) 6,678 7,107 1,066 2,929 Los Angeles Red Line (Segment 2) 6,678 7,107 1,066 2,929 Los Angeles Red Line (Segment 3) 6,678 7,107 1,066 2,929 Miami Metrorail 3,685 2,939 569 1,467 Philadelphia SEPTA Frankford Rehab. 2,908 4,538 445 1,320 San Francisco BART Extension 3,549 4,176 683 1,880 Baltimore – Three Extensions 4,702 2,997 619 2,179 Baltimore Central Line 4,702 2,997 619 2,179 Buffalo Metro Rail 4,965 3,244 428 1,924 Dallas North Central 6,515 2,688 888 3,214 Dallas S&W Oak Cliff and Park Lane 6,515 2,688 888 3,214 Denver Central Corridor 4,897 1,425 739 2,519 Denver Southeast (T-REX) 4,897 1,425 739 2,519 Denver Southwest Corridor 4,897 1,425 739 2,519 Los Angeles Green Line 6,678 7,107 1,066 2,929

Making Effective Fixed-Guideway Transit Investments: Indicators of Success Volume 1, Handbook 1-61 Table A-8: Metropolitan Statistical Area Characteristics per existing station, cont’d. City & Project Total Jobs Total Population Leisure Jobs Higher-income Jobs Los Angeles Long Beach Blue Line 6,678 7,107 1,066 2,929 Minneapolis Hiawatha Corridor 6,657 1,761 914 3,807 New York – Newark Elizabeth MOS-1 New York Hudson-Bergen MOS 1 and 2 Pasadena Gold Line 6,678 7,107 1,066 2,929 Phoenix Metro Light Rail Portland Airport Max 2,515 1,860 541 1,013 Portland Interstate MAX LRT 2,515 1,860 541 1,013 Portland MAX Segment I 2,515 1,860 541 1,013 Portland Westside/Hillsboro MAX 2,515 1,860 541 1,013 Sacramento Folsom Corridor 2,637 2,111 415 1,100 Sacramento Mather Field Road Extension 2,637 2,111 415 1,100 Sacramento South Phase 1 2,637 2,111 415 1,100 Sacramento Stage I 2,637 2,111 415 1,100 Salt Lake City Medical Center Extension 4,098 1,710 843 1,438 Salt Lake City North South Corridor 4,098 1,710 843 1,438 Salt Lake City University Extension 4,098 1,710 843 1,438 San Diego Blue Line 3,565 2,863 827 1,516 San Diego Mission Valley East 3,565 2,863 827 1,516 San Diego Orange Line 3,565 2,863 827 1,516 San Jose North Corridor 3,504 2,981 486 2,249 San Jose Tasman East 3,504 2,981 486 2,249 San Jose Tasman West 3,504 2,981 486 2,249 San Jose VTA Capitol Segment 3,504 2,981 486 2,249 San Jose VTA Vasona Segment 3,504 2,981 486 2,249 Seattle Central Link Trenton – Southern New Jersey Light Rail Transit System