Session 7A, Paper 2

1. Preliminary Results of a Spatial Analysis of Dublin City's Bike Rental Scheme Peter Mooney Padraig Corcoran Adam C. Winstanley

2. Contact Details [email_address] [email_address]

3. DublinBikes (DB) is a recently introduced (Sept, 2009) bike rental scheme for Dublin city, Ireland Commercial company (JCDecaux) and city council partnership Approximately 50,000 subscribers Commercial company (JCDecaux) and city council partnership 95% of rentals are free - under 30 minutes

6. Doherty (2009) reported on bike usage as a means of commuting Only 1.9% of workers commute by bike in Ireland Bike usage as a means of work transport down 33% since 1986 Poor continuity of cycle lanes and integration with other transportation systems

7. Other studies reveal more obvious reasons why cycling has become less popular as a mode of transport “ 16% of people said DISTANCE was the biggest factor preventing them cycling to work” Keegan and Galbrait (2005) “ The streets are too dangerous” “ Cars use the bike lane” Keegan and Galbrait (2005) Irish Times (2007)

8. DB Terminals are clustered around the city center - approx 400 meter separation between stations

9. DublinBikes (DB) website shows current status of every terminal

10. By examining the DB javascript we found the web services providing terminal information

11. Yahoo Weather RSS are downloaded, parsed, and stored Each 30 minutes

12. Data capture is handled by a set of scheduled PHP scripts CRON Task 4 minute intervals All 40 Stations PHP GET HTTP Scrip t April 13 th (2,078,366) rows

14. OpenStreetMap contains all 40 DublinBike locations

15. We built a web application to monitor data capturing

16. Froehlich et al (2009) studied Barcelona's BICING system 390 STATIONS 6,000 BIKES 150,000 Subscribers Data Capture: Web Page Scraping

18. Some DB stations are integrated with LUAS TRAM stops

19. Almost 95% of DB terminals are more than 400 meters from suburban train stations Marteens et al (2004) - “best integration of bikes – 400 meters from train stations”

20. Dublin's extensive bus network integrates well with DB terminals Currie (2009) – high service level bus stops

21. Including all modes – there is reasonably good integration North-west inner city DB terminals are somewhat isolated.

22. Analysis of checkout statistics for Weekdays and Weekends

23. Availability of bikes at the three busiest stations on the network

24. Looking at the periods of inactivity at a station gives an indication of how “busy” the terminal is Mean number of minutes during weekdays where no checkout or return occurs at this station

25. Normalised checkouts - weekdays

26. Normalised Checkouts - Weekends

27. Weekends vrs Weekday – busy station patterns City center cluster is always busy

28. Total number of bikes available in the network – September - April Christmas period No Data Daily – maximum usage

29. Usage patterns during the Dublin Marathon 2009 Spectators using Dublin Bikes to “follow” the race

30. Last Sunday..... “First day of Spring” Heavy demand on bikes in mid-afternoon – steady flow of return

31. “ Typical” Weekday Rush hour pattern – bikes out – and bike returns to other stations

32. Wettest November (2009) days on record 60 bikes MAX Little or no usage – until a massive rush for bikes in the late evening

34. There are a number of issues for future Work Gain access to the trips database – model flows of bike trips etc Prediction of Station Usage Integrate population models - see areas of the city where large numbers of people are working/etc Compare with other similiar sized free bike rental schemes