2. Factors Driving Public Bike Share Demand: The Case of Bike Share Toronto Wafic El-Assi Undergraduate Research Fellow Supervisor: Prof. Khandker Nurul Habib

3. Presentation Outline  Background and Motivation  Data Analysis  Models Developed  Results  Potential Tools

4.  Four Generations: 1.“White Bikes” implemented in Amsterdam in 1965 2.“Coin Deposit System” introduced in the mid 1990s to reduce theft incidents 3.“IT based Systems” added transaction kiosks to solve the problem of anonymous users 4.“Demand-Responsive Multimodal systems” improved on docking stations, bicycle redistribution, and integration with other transport modes History of Public Bike Share Systems

5. Worldwide Bike Sharing Programs  Over 300 bike sharing programs (Shaheen et al.,2010)

6. Canadian Bike Sharing Programs  Bike Share Toronto -Launched in 2011  80 stations  1000 Bicycles -4200 Subscribers in 2012  BIXI Montreal -Launched in 2009  300 Stations  3000 Bicycles -40000 Subscribers in 2012 -Expanded network 2013  450 Stations  5120 Bicycles

7. Canada’s Biking Mode Share  The proportion of commuters via bicycle in Toronto is 1.2%  This represents a 30% increase over previous census years  Commuting via bicycle most common in Downtown area

8. Average Distance Travelled per Commuter Trip Mode  The average trip distance in the downtown core is 2.25 km

9. Who Uses Bike Share Toronto? User AttributesResults Age Group 25 - 5480% Bike Ownership64% Male67% University Degree79% Full Time Worker76% Income > $80000/yr52%

10. How is Toronto Using Bike Share? Home-Work Commute 2 To 5 Times Per Week40% Utilitarian Trip Purposes 1 To 4 Times Per Month39% Leisure Trip Purposes 1 To 4 Times Per Month36%

11. Factors Affecting Bike Share Ridership: User Perspective Location of Stations Very/Extremely Important92% Number of Stations Very/Extremely Important86% Availability of Bikes/Docks Very/Extremely Important85%

12. Bike Share as a Multimodal Transportation Service

13. Available Resources  Bike Share Data  Individuals’ detailed trip information:  day of trip  start time  end time  trip duration  Station Location coordinates

14. Available Resources  Historical Weather Data from Environment Canada: Relative Humidity Precipitation Snow on Ground Hourly Temperature Hourly Wind Speed Visibility

15. Available Resources  Bike Network Level of Service (LOS) Attributes  Generated by Google Maps API and analyzed in GIS  Number of intersections  Percentage of bike route that has a bike infrastructure  Type of bike infrastructure  Surrounding transit stations  Distance between stations

16. Available Resources  2011 Transportation Tomorrow Survey (TTS) Data Detailed trip Information by all travel modes within the study area Zonal employment and population  2013 Bike Share Customer Feedback Survey

17. Year Round Trip Distribution by Time Period Year Round

18. Trip Distribution by Time Period Year Round - Registered Year Round - Casual

19. Trip Distribution by Time Period August February

20. Trip Distribution by Time Period August - Registered August - Casual

21. Trip Distribution by Time Period February - Registered February - Casual

22. Weekend vs Weekday Trip Distribution

25. Trip Attraction at Bike Share Stations

26. Trip Generation at Bike Share Stations

27. Most/Least Active Routes

28. Regression Models  We developed three models:  Trip Attraction Model  Trip Generation Model  Station to Station Origin-Destination Model

29. VariablesDefinitionUnit Aggregation Level Socio- Demographic MaleMale to female ratio%Zonal EmpdenAverage employment densityPers/kM 2 Zonal popdenAverage population density Pers/kM 2 Zonal Weather TempPerceived Temperature oCoCDaily SnowAmount of snow on groundcmDaily HumRelative humidity%Daily PrecipAmount of precipitationmmDaily Variables Included in Attraction/Generation Model

30. VariablesDefinitionUnit Aggregation Level Built Environment n_stationsNumber of stations in 200m bufferNAStation DocksNumber of docks per stationNAStation University = 1 if the zone has university campus; = 0 otherwise NAZonal TransitNumber of Subway/Commuter Rail Stations NAZonal Variables Included in Attraction/Generation Model

31. VariablesDefinitionUnit Correlation Socio- Demographic MaleMale to female ratio% EmpdenAverage employment densityPers/kM 2 popdenAverage population density Pers/kM 2 Weather TempPerceived Temperature oCoC SnowAmount of snow on groundcm HumRelative humidity% PrecipAmount of precipitationmm Attraction-Generation Model - Results

32. VariablesDefinitionUnitCorrelation Built Environment n_stationsNumber of stations in 200m bufferNA DocksNumber of docks per station > 18NA University = 1 if the zone has university campus; = 0 otherwise NA TransitNumber of Subway/Commuter Rail Stations NA Attraction-Generation Model - Results

33. VariablesDefinitionUnit Aggregation Level Built Environment n_stationsNumber of stations in 200m bufferNAStation distance_travelled Distance traveled between an OD pair kmBike Path intersections Number of intersections with major roads between an OD pair NABike Path bike_infra Percent of bike infrastructure compared to total bike path %Bike Path DocksNumber of docks per stationNAStation University = 1 if the zone has university campus; = 0 otherwise NAZonal TransitNumber of Subway/Commuter Rail Stations NAZonal Variables Included in Origin- Destination Model

34. VariablesDefinitionUnitCorrelation Built Environment n_stationsNumber of stations in 200m bufferNA distance_travelled Distance traveled between an OD pair km intersections Number of intersections with major roads between an OD pair NA bike_infra Percent of bike infrastructure > 50% % Docks Number of docks per station = 1 if number of Docks > 18 NA University = 1 if the zone has university campus; = 0 otherwise NA TransitNumber of Subway/Commuter Rail Stations NA Origin-Destination Model Results

35. Why is This Important?  Develop a policy tool capable of forecasting bike share demand at the station level  Utilize models and ArcMap GIS to establish future station locations  Develop policy recommendations for bike lane infrastructure expansion in Toronto

36. Thank You For Listening!  Contact Information:  Email: Wafic.el.assi@mail.utoronto.caWafic.el.assi@mail.utoronto.ca  Cell Number: 647-919-7555