1. Completing the Cycle:Incorporating CycleTracks into SF-CHAMPUsing technology to understand the needs of cyclistsSAN FRANCISCO COUNTY TRANSPORTATION AUTHORITYFall 2012

2. Outline1. Why make CycleTracks?2. What does CycleTracks do?3. Who used CycleTracks and why?4. What data did we get from CycleTracks?5. What did we do with that data?6. Evolution and future of CycleTracks 3. 1. Why CycleTracks? 4. Why CycleTracks?Need to prioritize projects, including bike projects. Estimate a bike choice model that evaluated various bike infrastructure features Needed bike route choice data on a budget. 5. 2. What doesCycleTracks do? 6. Enter personal data (optional) 7. Enter New Trip 8. Review Saved Trips 9. Thats it?Bells and whistles could promote deviation from planned route. Features! Good Data. Flare! Yawn.More users! 10. 3. Who used CycleTracks and Why?- User Recruitment- Participants 11. Participants: who gaveus data? 12. SF Participants: Fall 2009 to Spring 2010CycleTracksBATSN-366 N=153 z-statAge Mean 34 331.1Gender Female21%36% -3.5Cycling Frequency Daily 60% Several Times/Week34% Several Times/Month7% Less than once a month 0% N/A 13. 4. What data did we get?- Data Quality- Data Summaries 14. Data Quality: some good, some bad 15. Urban Canyon Effect Haight AshburyvsDowntown 16. GPS Signal at Beginning of Trip 17. Not on a Bike 18. Post Processing Warranted5,178 tracesGaussian 497 userssmoothingActivity & modedetection3,034 bikeMap stageshmatching 366 users(Schssler & Axhausen 2009) 19. 5. What did wedo with theCycleTracksData? 20. Matched Route Features to the Chosen Route 21. as well as to a set of routes that were notchosen 22. What makes us choose one bike route overanother ?PersonalTripInfoFeaturesRoute Which routeFeatures ofwas Available Routechosen?Routes Choice Model 23. Estimation resultsAttribute Coef. SEt-stat.p-val.Length (mi)--1.050.09 --11.80 0.00Turns per mile --0.210.02 --12.15 0.00Prop. wrong way--13.30 0.67 --19.87 0.00Prop. bike paths 1.890.31 6.170.00Prop. bike lanes 2.150.12 17.69 0.00Cycling freq. < several per wk. 1.85 0.04 44.94 0.00Prop. bike routes0.350.11 3.140.00Avg. up-slope (ft/100ft) --0.500.08 --6.350.00Female --0.960.22 --4.340.00Commute--0.900.11 --8.210.00Log(path size) 1.070.04 26.38 0.002,678 weighted observations, 2 = 0.28 24. Average Marginal Rates of SubstitutionMRS of Length on Street for Value UnitsTurns 0.10mi/turnTotal Rise1.12mi/100ftLength Wrong Way4.02NoneLength on Bike Paths0.57NoneLength on Bike Lanes0.49NoneLength on Bike Routes 0.92NoneSAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY28 25. Updates to SF-CHAMPSynthesizedCore, 3 iterationsPopulation Work Location, Land UseDestination Choice, Mode ChoiceTour Generation Networks Networks Logsums+Bike Vars!Tour & TripMode ChoiceBike Route Choice SetRoad & TransitNon-Motorized BikeGeneration &Assignment/Skimming (Distances)LogsumsSkimming SkimmingInitial Road & Transit Assignment/SkimmingFinal BicycleAssignmentSAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 29 26. Bike Accessibility: From 4th and KingSAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 30 27. Bike Accessibility: To 4th and KingSAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 31 28. Bike Logsums: From 4th and KingEffect of Bike Plan Build SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 32 29. Bike Logsums: To 4th and KingEffect of Bike Plan Build SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 33 30. Preliminary Results:Tour Mode Choice SensitivityTour Difference Daily Toursv4.1 Harold v4.3 Fury Bike3000.1%1,300 0.9% Walk3000.0%200 0.0% Transit2000.0%-900 -0.1% Auto-1,000 -0.0%-600 -0.0% Total -200 -0.0% 00.0%SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY34 31. Preliminary Results:Trip Mode Choice Sensitivity Trip Difference Daily Toursv4.1 Haroldv4.3 Fury Bike5000.1% 3,000 0.8% Walk1,1000.0%-500-0.0% Transit8500.0%-600-0.0% Auto-2,400 -0.0%-1,300-0.0% Total00.0% 600 0.0%SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 35 32. SF-CHAMP Predicted Bike Trips Bikes / hour 018020360SF-CHAMP v4.1 Harold 33. 6. Evolution andFuture ofCycleTracks 34. All Open Source GPL3 License Code on GitHub Fork us! www.github.com/sfcta 35. e.g. AggieTrackhttp://aggietrack.com 36. CycleTracks Works EverywhereWe already have the database set upAgencies can download scrubbed data Austin,TX Monterey Bay, CAand more! 37. Title 38. Questions?www.sfcta.org/cycletracks 39. Bike Accessibility: From Inner SunsetSAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 43 40. Bike Accessibility: To Inner SunsetSAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 44 41. Bike Logsums: From Inner SunsetEffect of Bike Plan Build SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 45 42. Bike Logsums: To Inner SunsetEffect of Bike Plan Build SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY 46