Decision-Making Toolbox to Plan and Manage Park-and-Ride Facilities for Public Transportation: Guidebook on Planning and Managing Park-and-Ride (2017)

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

124 This appendix is intended to provide transit professionals with additional information about two demand estimation models from existing national resources. Figure A-1 and Figure A-2 provide illustrations of the following two models: • Figure A-1: The Station Access Model from TCRP Report 153: Guidelines for Providing Access to Public Transportation Stations, developed by Coffel et al. (2012). • Figure A-2: The Indicator-Based Method from TCRP Report 167: Making Effective Fixed- Guideway Transit Investments: Indicators of Success, developed by Chatman et al. (2014). The figures summarize the following aspects of each model: • Description. • Software and hardware requirements. • Data needs and key assumptions. • Estimation process. • Available resources. • Strengths and applications. • Limitations. The two models do not represent all viable modeling techniques used by transit agencies to estimate latent or future demand for park-and-ride. Estimating demand for park-and-ride can be part of a regional travel demand model or a less formal sketch modeling exercise specific to a particular transit agency or potential facility site(s). The following are some examples of transit- agency–specific models developed and used internally by the transit agencies: • The Regional Peer Site Model, developed by the Texas A&M Transportation Institute for Fort Bend County (Texas) Public Transportation in 2012 (Brooks et al. 2014). • Milwaukie (Portland, Oregon) Park-and-Ride Estimates, developed by TriMet in 2011 (Callas 2011). • The Access Policy Methodology, developed by BART in 2005 (Willson 2005). The FTA developed another approach to demand estimation. The FTA’s STOPS is a simpli- fied ridership-forecasting method for local transit agencies to use when planning major transit projects. At their option, local transit agencies can use STOPS to meet all of the forecast-related requirements for transit projects proposed for federal funding. STOPS is a region-wide travel model, similar to traditional trip-based models maintained by MPOs in larger metro areas. STOPS is intended for use by capable travel-forecasting professionals. The FTA provides detailed information on STOPS, as well as downloads of the software and a contact name for technical assistance, on the STOPS webpage, which is accessible from the FTA’s Travel Forecasts page: https://www.transit.dot.gov/funding/grant-programs/capital-investments/ travel-forecasts. Demand Model Briefs A p p e n d i x A

demand Model Briefs 125 TCRP REPORT 153 GUIDELINES FOR PROVIDING ACCESS TO PUBLIC TRANSPORTATION STATIONS DESCRIPTION ESTIMATION PROCESS SOFTWARE, HARDWARE REQUIREMENTS DATA NEEDS, KEY ASSUMPTIONS STRENGTHS, APPLICATIONS WEAKNESSES, LIMITATIONS AVAILABLE RESOURCES Link to TCRP Report 153: www.trb.org/Main/Blurbs/ 166516.aspx Appendix C is documentation for the Station Access Model. The model spreadsheet is in Microsoft Excel format. All files are available at the above hyperlink. MODEL DATA ENTRY SCREEN IN EXCEL TCRP Report 153: Guidelines for Providing Access to Public Transportation Stations provides information to aid in the planning, developing, and improving of access to high-capacity commuter rail, heavy rail, light rail, bus rapid transit, and ferry stations. The report includes guidelines for arranging and integrating various station design elements. The report also features the Station Access Planning Tool, or Station Access Model, which is a spreadsheet-based planning tool that walks the user through the estimation and evaluation of ridership and access mode splits, the testing of alternatives, and a rough evaluation of costs and benefits. The Station Access Model consists of Adobe PDF documentation and a Microsoft Excel spreadsheet. The spreadsheet is in *.xlsx format, compatible with all Office 2003 and later installations. A typical computer capable of operating Excel is sufficient to run the model; no special hardware requirement exists. Model users are responsible for collecting and entering data related to the transit agency, the station itself, and the station area (within a ½-mile radius). Typical data sources are identified in the tool’s instructions. Some data are available from external sources such as the U.S. Census Bureau and the Longitudinal Employment Database. For other data, default values have been developed using data obtained from over 600 high-capacity transit stations throughout the country. Station typologies have been developed to allow the user to select a similar station area based on the surrounding environment and operating characteristics. The Station Access Planning Tool is set up to be a step-wise process. Although each step is part of the process, the model generates interim outputs throughout and does not necessarily provide a clear answer at the end. Rather, the model is designed to provide information with which planners and designers can make decisions. Following are the five key steps in the estimation process: • Step 1— Estimate overall station ridership. • Step 2—Estimate station access mode split. • Step 3—Estimate automobile parking demand. • Step 4—Assess impacts of changes to parking supply. • Step 5—Assess effects of management options (parking pricing, improved feeder bus service, walk access, bicycle access, and transit-oriented development). The Excel spreadsheet contains a separate sheet for each of the five key steps. The Station Access Model is based on a robust set of station access data from transit agencies in the United States and is effective for understanding how well a station is performing in terms of access. Given a set of station-area and regional characteristics, it estimates a reasonable breakdown of access by mode. By comparing this information to actual station access data, planners can understand whether improvements to a given mode are likely to yield greater access numbers by that mode. Like any model, the Station Access Model contains many assumptions and default values that may or may not be appropriate for a specific transit agency or facility location. The model may be acceptable for comparing alternatives but may require significant time and attention to detail to develop specific estimates for a given station or unusual context. Figure A-1. The Station Access Model. Source: Coffel et al. 2012.

126 decision-Making Toolbox to plan and Manage park-and-Ride Facilities TCRP REPORT 167 MAKING EFFECTIVE FIXED-GUIDEWAY TRANSIT INVESTMENTS: INDICATORS OF SUCCESS (VOLUME 1 OF 2) DESCRIPTION ESTIMATION PROCESS SOFTWARE, HARDWARE REQUIREMENTS DATA NEEDS, KEY ASSUMPTIONS STRENGTHS, APPLICATIONS WEAKNESSES, LIMITATIONS AVAILABLE RESOURCES Link to TCRP Report 167: www.trb.org/Main/Blurbs/ 170972.aspx Volume 1 is documentation for the Indicator-Based Method model. The model spreadsheet is in Microsoft Excel format. All files are available at the above hyperlink. The Indicator-Based Method consists of multivariate regression statistics constructed to predict ridership for heavy rail transit (HRT), light rail transit (LRT), and fixed-guideway bus rapid transit (BRT) lines using data from existing park-and-ride facilities in the United States. The model was created by evaluating 55 existing HRT, LRT, and BRT lines in 21 U.S. metropolitan areas, along with supplementary information and guidance from focus groups and interviews with transportation professionals. The model predicts two success metrics: the average weekday ridership and the change in annual passenger-miles traveled (PMT). The Indicator-Based Method model consists of Adobe PDF documentation and a Microsoft Excel spreadsheet. The spreadsheet is in *.xlsm format, compatible with all Office 2007 and later installations (file contains Visual Basic macros). A typical computer capable of operating Excel is sufficient to run the model; no special hardware requirement exists. The model requires entering system-level, project-level, and cost inputs. System-level inputs are information about the overall transit system. Project-level inputs are information about the proposed transit project. Cost inputs consist of information related to the total cost of the project. Examples of some of the required inputs are: • System-level inputs: daily parking rate at the destination activity center/central business district (CBD); jobs within ½ mile of all fixed-guideway stations in the system; population within ½ mile of all fixed-guideway stations in the system; etc. • Project-level inputs: metropolitan statistical area (name, background information); retail, entertainment, and food jobs within ½ mile of project stations; higher-wage jobs within ½ mile of project stations; etc. • Cost inputs: cost method (user can choose among three different options); number of stations; percent alignment below grade; type of project; mode; route miles; user-estimated capital cost per mile; and user-estimated total capital costs. The Indicator-Based Method model seeks to find the best fit between transit ridership and PMT change based on existing conditions and contextual characteristics. Multiple regression analysis was the mathematical tool researchers used to build the model based on projects and cities for which the authors had complete data sets. Appendix E of TCRP Report 167 includes a complete list of the more than 140 indicators that were considered in development of the final model tool. The most powerful predictive variables found were jobs and population within ½ mile of park-and-ride/transit stations, daily parking rate at destination activity centers/CBD, and age of transit facility. The spreadsheet tool helps planners estimate fixed-guideway transit ridership in a fast and easy manner. Planners can divide estimated ridership by access mode-share assumptions to derive park-and-ride lot spaces needed. The model is an easy-to-use methodology to predict transit ridership. Required data are easily accessed, making the model an excellent low-cost, easy-implementation alternative. The model is best suited for predicting fixed-guideway transit ridership: planners may combine modeled ridership with assumed access mode share to determine approximate demand for park-and-ride lot spaces and modal access infrastructure needs in the facility (e.g., pedestrian, bike). The model does not account for existing or future transit service and infrastructure projects affecting the modeled facility. The variable for predicting the total number of park-and-ride lot spaces is not directly available; users derive demand for park-and-ride parking spaces based on total ridership estimated by the Indicator- Based Method divided by assumed access mode shares. MODEL DATA ENTRY SCREEN IN EXCEL Figure A-2. The Indicator-Based Method. Source: Chatman et al. 2014.