1. Bicycle Modeling with the Santa Clara VTA Models – Proof-of-Concept … and Beyond

2. Overview of the Santa Clara Valley Transportation Authority Special district in Santa Clara County with diverse responsibilities Congestion Management Agency for Santa Clara County Develop and maintain 4-step trip-based VTA Countywide Models Support VTA and Member Jurisdiction Planning Activities Transit operator for Local Bus, Express Bus and LRT System for the County Multi-modal project development Highway, Transit, Express Lanes, Bike and Pedestrian Projects Planning, Environmental, Engineering, Design, Construction Phases Long-Range Valley Transportation Plan (VTP 2040)

3. VTA Bicycle Modeling History In the past, bicycle and pedestrian walk trips and O-Ds were estimated in the VTA models through mode choice but never evaluated in detail in assignment routines Bicycle trip choice in mode choice a function of employment density, bicycle travel times and presence of colleges/universities Lack of bicycle and pedestrian network attributes – coarse input speed assumptions (12 mph applied to all roadways) No explicit coding of bike paths and trails Lack of comprehensive count data to validate models – small markets Transit and auto vehicle volumes historically were the priority

4. What Has Changed? County increased bicycle infrastructure funding - $300 million for bicycle improvements in the most recent Long-Range Transportation Plan – so how do we plan improvements? Multi-modal Complete Streets programs Bicycle counts are now obtained as a routine part of data collection for all projects requiring roadway count data Pioneering work done by others for collecting bicycle path and user data from smartphone technology

5. Bicycle Modeling Enhancement Objectives Establish a basic foundation for incorporating bicycle detail in the Countywide Model framework – keep it simple but provide a fairly robust application for planning Start with a Proof-of-Concept and build from there Summarize and examine bicycle count data Capture observed bicycle speed data using GPS technology that is widely available Calibrate and validate the model outputs to existing bicycle trip mode shares from ACS and bicycle count data Apply the bicycle model in the context of a planning project to test applicability and Measures of Effectiveness (MOEs) Formulate series of enhancements for future development

6. San Francisco Bay Region Topography

7. Existing Bicycle Utilization – PM Peak Hour

8. Home-based Work Bicycle Mode Shares for the Region by County

9. Home-based Work Bicycle Mode Shares for Santa Clara County Jurisdictions

10. Open GPS Tracker Application Open Source Android Smartphone Application Saves detailed x,y coordinates, speed (meters/second) and elevation Track output saved to SD card and sent via email in GPX format Collected by VTA Planning staff over the course of 3 months Limited to staff with intermediate/advanced bicycling skills GPX data processed in QGIS Open Source GIS software and ARC GIS Managing and controlling data collection was key

11. Development of Bicycle Travel Speeds Captured using Open GPS Tracker smartphone application – available through Google Play

12. Coding and Representation of Bicycle Facilities in the Networks Coding of bike lanes for base year was straightforward – code as an added attribute on the link using underlying roadway area and facility types Paved bike and multiuse trails coded using GIS overlay as a guide – coded as series of non-motorized links with unique facility type code Bike trails connected to street networks at designated entry and exit points Did not consider elevation as an attribute

13. Bicycle Network Year 2013 Green = Bike Paths Red = Bike Lanes Blue = Undesignated or bike trips not allowed

14. Bicycle Travel Speeds Speed in MPH Bicycle track data was joined with model roadway network to obtain area type, facility type and speed attributes Cross-classification table developed from merge for a basic speed cross-classification scheme and adjusted for logical breakpoints (1,484 observations in total) Area Type No Bike Facility Bike Lane – Non Expressway Bike Lane Expressway Bike Paths Core 5.66.6 13.7 CBD 8.89.2 13.7 UBD 9.313.2 13.7 Urban 9.513.2 13.7 Suburban 11.813.2 13.7 Rural NA

15. Home-based Work Bicycle Mode Shares for the Region by County

16. Home-based Work Bicycle Mode Shares for Santa Clara County Jurisdictions

17. PM Peak Hour Bicycle Assignments and Validation Create PM peak hour bicycle trips by applying peak hour factors by trip purpose from trips by time of day distribution Keep each bicycle trip purpose as a submatrix class Assign to bike subnetworks using minimum path travel times Grade School and High School trips not allowed to travel on expressways No bicycle trips allowed on freeways Bicycle trips can travel through centroid connectors

18. Model Validation Results EstimatedObserved Estimated/ Observed PM Bike Volumes 4,2663,6561.17

19. 2013 PM Peak Hour Bicycle Volumes from Assignments

20. Typical Bicycle Modeling Outputs Bicycle mode shares by County and City New bike trips and trips diverted from other modes Bike trips assigned to networks (PM peak hour only so far) Bike-Miles Traveled by trip purpose Everything can be processed like typical O-D data – Select-link analysis, select-zone analysis, etc.

21. Average Trip Lengths for Bicycle Trips

22. Bicycle Modeling Outputs

23. 2040 PM Peak Hour Bicycle Volumes from Assignments

24. Bicycle Statistics from Assignment 2013 PM Peak Hour Classification BMTBMT % of TotalMiles% of MilesUtilization Mixed Flow 3,14528.5%1,50158.4%2.10 Bike Lane 6,50758.9%90835.3%7.17 Bike Path 1,38812.6%1626.3%8.57 All 11,040100.0%2,571100.0%4.29 2040 PM Peak Hour Classification BMTBMT % of TotalMiles% of MilesUtilization Mixed Flow 4,66216.9%1,38552.9%3.37 Bike Lane 17,63163.8%1,01738.8%17.34 Bike Path 5,33319.3%2178.3%24.58 All 27,626100.0%2,619100.0%10.55

25. What Lies Ahead? Bicycle Modeling Next Steps Obtain more bicycle path data from actual users Examine other factors that may influence bicycle path choice Obtain bicycle count data for AM, PM and Daily validation Obtain bicycle counts for trails Use the models for project applications – Update of Countywide Bicycle Plan this year

26. Postcard for Bike to Work Day - 2015

27. New Bicycle Count Data! AM and PM 2-Hour Peak Counts 12-Hour counts to capture ‘Daily’ travel

28. Bay and Ridge Trail Connections Project Partnering with Regional Trail Agencies Estimate bicycle demand resulting from implementation of regional trail connections Determine VMT and GHG emission impacts Develop procedures to estimate bike to transit demand for new Berryessa BART stations in Santa Clara County Apply for State Cap and Trade grant funds

29. Acknowledgements Developer of Open GPS Tracker Application – Rene de Groot VTA Planners/Bicyclists – David Kobayashi – Lauren Ledbetter

30. Thank You and Happy Biking!