TCRP Report 153: Guidelines for Providing Access to Public Transportation Stations. Part 2: Station Typology and Mode of Access Planning Tool

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1 TCRP Report 153: Guidelines for Providing Access to Public Transportation Stations Part 2: Station Typology and Mode of Access Planning Tool Jamie Parks, AICP Kittelson & Associates, Inc. Acknowledgements Kathryn Coffel, Kathryn Coffel Consulting, LLC Jamie Parks & Conor Semler, Kittelson &A Associates, Inc. Herbert Levinson Dave Sampson, AECOM Joseph Schofer Carol Kachadoorian, Toole Design Group 2

2 TCRP Report 153: Three Primary Research Products Guidebook Part I: Rapid Transit Station Planning 8-step idealized process Case-study insights Travel demand characteristics Part II: Rapid Transit Station Access Arrangement and Design General guidelines, and by mode: pedestrian, bicycle, transit, auto, TOD Case studies Successful practices and on-going challenges Agency-wide process (tied to 8-step process) Station-specific examples Station Access Planning Tool 3 Webinar Outline Webinar 1: Planning Process, Case Studies and Design 4 Guidebook Part I, Rapid Transit Station Planning Chapter 2: Station Access Planning Tools and Process Chapter 3: Insights from Case Studies Appendix E: Case Studies Guidebook Part II, Rapid Transit Station Access Arrangement and Design Chapter 6: General Station Access Guidelines Chapter 7-11: Access Guidelines by Mode Pedestrian Access to Transit Bicycle Access to Transit Transit Access Automobile Access and Park-and-Ride TOD and Station Access

3 Webinar Outline Webinar 2: Station Typologies and Mode of Access Planning Tool Guidebook Part 1: Rapid Transit Station Planning Chapter 4: Station Typology and Access Modes Chapter 5: Travel Demand Considerations Appendix C: Station Access Planning Tool Appendix D: Station Access Mode Data Sections not covered: Stakeholder interviews and Literature review: Appendix A and TCRP Web-only Document 44 Appendix B: Overview of existing station access tools 5 Access to High-Capacity Transit: What Is It? High-Capacity Transit Commuter rail Heavy rail Light rail and streetcar Bus rapid transit Ferry Access Modes Walk Bicycle Transit Auto Transit Oriented Development 6

4 Access to High-Capacity Transit: What s the Problem? Many stakeholders Many goals for station ti access improvements Maximize ridership Minimize operating costs Minimize capital costs Enhance active transportation Attract new development Limit spillover effects 7 Chapter 4: Station Typology and Access Modes Provide consistent planning framework for transit access Capture importance of physical factors on transit access Existing or aspirational Serve as a basis to organize data and access planning tool 8 Conceptual impact of density on mode share

5 Station Typology Total of 18 station types covering all line-haul modes Comprehensive typology Few systems will have all 18 station ti types represented May be collapsed for many applications 9 Suburban Freeway Station Suburban TOD/Town Center Typology Factors 8 Key Factors Example Suburban Employment Center Housing density Low Scale 1 3 Surrounding land uses Office with limited retail Distance from CBD 5 15 miles Supporting transit network Some local bus, shuttles Pedestrian/bicycle access Poor connectivity, high traffic volume Parking facilities Park and ride and ride prioritized Access/egress Egress 10

6 Station Typology Matrix Typology summarized in single 2-page matrix 18 station types X 8 factors Example stations provided for each station type Typical line-haul modes associated with each type Refer to hand-out 11 Appendix D: Station Access Mode Data Connect typology to real-world outcomes Station ridership by access mode available from seven U.S. transit agencies: Agency WMATA (Washington, DC) BART (San Francisco) Regional Transit District (RTD) (Denver) TriMet (Portland) Metro North (New York City) MBTA (Boston) Sound Transit (Seattle) Rapid Transit Modes Heavy Rail Heavy Rail Light Rail Light Rail Commuter Rail Heavy Rail and Light Rail Commuter Rail 12

7 Station Access Mode Data Data available for over 450 stations Manually matched to typology using available data Confirm typology Provide dataset for further analysis Wide range of access characteristics captured Example Summary Table from TCRP Report Station Typology Access Data Chapter 4 provides summary data tables Appendix D provides the full access data for all 450 stations Arranged by station type 14

8 Chapter 5: Travel Demand Considerations, and Appendix C: Station Access Ridership Tool Estimate station ridership for each access mode Facilitates analysis of access alternatives Estimate impact of access improvements on: Transit ridership Operating cost Revenue (fare and parking) 15 Development of Spreadsheet Tool Literature review and interviews found few objective station access evaluation tools BART model (Willson and Menotti) to assess trade-offs between parking and TOD Elasticities available for some factors Data collection at over 450 stations and station typology Draft structure approved by panel Released draft version of tool for agency testing and feedback 16

9 Access Decision Factors Auto Park-and-ride and ride requires available and adequate parking Kiss-and-ride requires waiting space Feeder Transit Convenient service coordinated with line-haul schedule Bicycle Facilities around the station Parking and/or bicycles on transit Walking Development near station Safe, direct, and attractive walking facilities 17 Independent Variables Station Access Provisions (from transit agencies) Car Parking Availability and Number of Spaces Daily car parking price Bicycle Parking Availability and Number of Spaces Number of connecting transit lines Station Area Characteristics (US Census/LEHD) Population, Households, and Occupied Housing Units Jobs and Workers Median Household Income and Vehicle Availability Block density Means of Transportation to Work Age Walk Score 18

10 Ridership Forecasting Tool works best where existing/projected boardings are available Developed set of linear regression models Separate linear regression for each access mode (feeder transit, auto, pedestrian, bicycle) Tested wide range of independent variables NOT a replacement for robust demand modeling Identify key relationships between ridership and access Test alternatives at sketch-planning level 19

11 Regression Results Auto Ridership Model (R 2 = 0.821) Coefficient t Significance Constant Heavy rail dummy variable a Car parking spaces Percent zero car households Bicycle Ridership Model (R 2 = 0.771) Constant Jobs within ½ mile Population within ½ mile Bicycle parking spaces Bicycle commute mode share 3, Percent zero car households within ½ mile a Heavy rail = 1; other = 0

12 Regression Results (cont.) Coefficient t Significance Walk Ridership Model (R 2 = 0.717) Constant Heavy rail dummy variable a 1, Jobs within ½ mile Workers within ½ mile Workers who walked to work within ½ mile Feeder Transit Ridership Model (R 2 = 0.373) Constant Heavy rail dummy variable a Connecting transit lines Workers within ½ mile Parking utilization at station a Heavy rail = 1; other = 0

13 Regression Model Findings 22 Automobile access increases with: More parking spaces Primary determinant of the model Not necessarily causative Higher levels of vehicle ownership Bicycle access increases with: Higher population density Lower levels of vehicle ownership More bicycle parking Again, not necessarily causative More bicycle-friendly station area Measured by overall bicycle commute mode share Regression Model Findings (cont.) Pedestrian access increases with: Higher population density More pedestrian-friendly station area Measured by overall pedestrian commute mode share Heavy rail dummy variable Feeder transit access increases with: More connecting transit routes At stations with more constrained parking 23

14 Regression Model Findings (cont.) Lack of available data on transit service quality limited modeling effort Vehicle ownership not significant in the pedestrian model Likely related to collinearity with heavy rail dummy Age, income, and WalkScore not significant in any models 24

15 Using the Tool User-friendly Excel spreadsheet Available online and on CD Color-coded cells Appendix C provides step-by-step t instructions ti Park and Ride and Add S l Add Supply Cost per New Rider Excess Demand Pricing Ridership Impact Cost per Rider Auto Parking Utilization Excess Capacity Development Evaluate Scenarios Trip Gen. Compare Revenue Outcomes 25 Transit Capture

16 Using the Tool Feeder Transit Access Feeder Bus Existing Productivity Cost per RIder Evaluate Scenarios Cost per New Rider Service Elasticity Pedestrian Access Pedestrian Pop/Jobs by RIng Compare access to Standard Equal or better than standard d OK Below Standard Prioritize pedestrian improvements Bicycle Access Bicycle Pop/Jobs by RIng Compare access to Standard Equal or better than standard OK 26 Below Standard Prioritize bicycle improvements

17 Using the Tool Adjusting for Local Context Default values provided for many data inputs (e.g., annual operating cost per structured parking space) Defaults clearly identified within tool (not a black box!) User-encouraged to modify defaults for local context 27 Illustrative Case Study Background characteristics Urban Neighborhood Light Rail Station 300 free parking spaces 85% utilized 12 bicycle parking spaces 2 connecting transit lines (free transfers) City-wide bike commute mode share is 1.6% 28

18 Station Area Characteristics Station Area Demographics (within ½ mile) Population: 6,000 Median household income: Jobs: 1,500 Percent zero car households: $48,000 20% Workers: 3,500 Vehicles per worker 0.85 Workers who walked to work: Suburban Freeway Station Determine Station Type Urban Neighborhood with Parking Housing Density Medium Scale 2-5stories Distance from CBD 5-10 miles Supporting transit Sub-regional hub Non-motorized access High-quality network, highvolume roadways may limit connectivity Land use Residential, some retail Access/Egress Access Parking Off-street parking available 30

19 Estimated Ridership and Access Mode Share Access Mode Daily Boardings Mode Share Auto (Park & Ride) % Auto (Drop off) % Feeder Transit 1, % Bicycle % Wlk Walk 1, % Total 3, % 31 Testing Access Improvements Planners estimate impact of enacting parking pricing and improving feeder transit service Parking to be charged at $2 per day 2 new local circulator bus routes added Improve schedule coordination with 2 other routes Improve bicycle facilities in station-area 32

20 Impact of Changes Parking supply exceeds demand, so some ridership is lost (88 daily boardings, or 44 riders) But 15 riders will find another access mode Net loss of 58 daily boardings Feeder transit improvements yield 392 riders Assume 15 riders switch from auto to bus Since bicycle access mode share is less than regional bicycle travel share, bicycle improvements forecast to increase bike access to transit 33 What about TOD? Replace 300-space lot with 270 housing units (4-story apartment complex) No replacement parking Ridership impacts: Parking loss: New development: Net Impact: boardings +300 boardings boardings 34

21 Ridership Tool Summary Allows multimodal access evaluation Ridership and cost Reflects factors affecting all four major access modes Based on national dataset of access characteristics Value for decision-making Applied successfully by Sound Transit for commuter rail access study 35 Summary Webinar 1: TCRP Report 153 Planning Process, Case Studies and Design Webinar 2: TCRP Report 153 Station Typologies and Mode of Access Planning Tool Chapter 4: Station Typology and Access Modes Chapter 5: Travel Demand Considerations Appendix C: Station Access Planning Tool Appendix D: Station Access Mode Data 36

22 Thank you! Jamie Parks Kathryn Coffel Questions Press *1 to ask a question 38

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