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London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
London Shared Bicycles: Measuring Intervention Impact
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London Shared Bicycles: Measuring Intervention Impact

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Read the research paper here: http://www.cl.cam.ac.uk/~nkl25/publications/papers/lathia_transport_research_c.pdf

Read the research paper here: http://www.cl.cam.ac.uk/~nkl25/publications/papers/lathia_transport_research_c.pdf

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  • 1. London Shared Bicycles: Measuring Intervention Impact @neal_lathia Computer Laboratory, University of CambridgeFriday, 7 December 12
  • 2. Measure Analyse Research Cycle Intervene ModelFriday, 7 December 12
  • 3. Measure Analyse Research Cycle Intervene ModelFriday, 7 December 12
  • 4. How Smart is Your Smart card? Measuring Travel Behaviours, Perceptions, & Incentives ACM Ubicomp 2011, Beijing, ChinaFriday, 7 December 12
  • 5. Uncovers the (typical) mismatch between perceived behaviour and actions transcribed in smart card data. Highlights cases where travel ‘incentives’ (e.g., peak-time fares) do not produce the expected behaviours.Friday, 7 December 12
  • 6. Individuals Among Commuters: Building Personalised Transport Information Services from Fare Collection Systems IEEE Pervasive and Mobile Computing, in press.Friday, 7 December 12
  • 7. There is a widespread variability in travellers’ experiences, as captured by transport data. This data can be used to design future travel information systems.Friday, 7 December 12
  • 8. Measure Analyse Research Cycle Intervene ModelFriday, 7 December 12
  • 9. Mining Mobility Data to Minimise Travellers’ Spending on Public Transport ACM KDD 2011, San Diego, California.Friday, 7 December 12
  • 10. Passengers’ trust in public transport relates to their perception of its cost. Their mobility patterns can be used to provide them with tailored fare recommendations (and help them save money).Friday, 7 December 12
  • 11. Measure Analyse Research Cycle Intervene Model This would be the ‘holy grail’Friday, 7 December 12
  • 12. Friday, 7 December 12
  • 13. System Opened: July 30, 2010 5,000 bikes; 315 stations; 44 km2 Payment Membership: £1 (24hrs) to £45 (annual) Usage: Free (30 mins) to £50 (24hrs) Access July 30 - Dec 3: register for access key Dec 3 - today: key or credit card at stationFriday, 7 December 12
  • 14. How are policy changes reflected in the city’s mobility data? Can this kind of analysis produce a granular picture of the effect of interventions?Friday, 7 December 12
  • 15. Friday, 7 December 12
  • 16. Conducting a “quasi-experiment:” We observe a city’s data over the timespan where policy changes are implemented. The main challenge, though, remains: can we attribute or infer any causality from our observations?Friday, 7 December 12
  • 17. Cluster 0 Cluster 1 0.8 0.78 0.6 0.4 0.74 0.2 0 2 4 6 8 10 13 16 19 22 0 2 4 6 8 10 13 16 19 22 Cluster 2 Cluster 3 0.6 0.65 0.4 0.55 0.2 0 2 4 6 8 10 13 16 19 22 0 2 4 6 8 10 13 16 19 22 Cluster 4 Cluster 5 0.55 0.35 0.45 0.25 0.35 0 2 4 6 8 10 13 16 19 22 0 2 4 6 8 10 13 16 19 22Friday, 7 December 12
  • 18. Cluster 0 Cluster 1 0.8 0.60.6 0.40.2 0.2 0 2 4 6 8 10 13 16 19 22 0 2 4 6 8 10 13 16 19 22 Cluster 2 Cluster 30.6 0.650.4 0.550.2 0 2 4 6 8 10 13 16 19 22 0 2 4 6 8 10 13 16 19 22 Cluster 4 Cluster 5 0.30 0.34 0.38 0.420.40 0.50 0.60 0.70 0 2 4 6 8 10 13 16 19 22 0 2 4 6 8 10 13 16 19 22 Friday, 7 December 12
  • 19. Friday, 7 December 12
  • 20. Hyde Park Corner Hyde Park Corner 1.0 1.0 0.8 0.8 Normalised Available Bicycles Normalised Available Bicycles 0.6 0.6 0.4 0.4 0.2 0.2 Week Day Week Day 0.0 Week End 0.0 Week End 0 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 10 12 14 16 18 20 22 24 Hour of Day Hour of DayFriday, 7 December 12
  • 21. Note: Station was moved!Friday, 7 December 12
  • 22. Friday, 7 December 12
  • 23. Who cares? Data insights provide targets for qualitative work; they provide localised success metrics; they inform the design of future interventions.Friday, 7 December 12
  • 24. Who cares? Data insights provide targets for qualitative work; they provide localised success metrics; they inform the design of future interventions.Friday, 7 December 12
  • 25. Finally, what is still missing?Friday, 7 December 12
  • 26. Finally, what is still missing?Friday, 7 December 12
  • 27. 1: What about other cities? 2: What are peoples’ habits in this context? There is no available data to answer this! 3: How does this use case relate to other data from the city?Friday, 7 December 12
  • 28. Contact: neal.lathia@cl.cam.ac.uk N. Lathia, L. Capra. How Smart is Your Smart card? Measuring Travel Behaviours, Perceptions, Incentives. In ACM Ubicomp 2011, Beijing, China. N. Lathia, C. Smith, J. Froehlich, L. Capra. Individuals Among Commuters: Building Personalised Transport Information Services from Fare Collection Systems. In IEEE Pervasive and Mobile Computing, in press. N. Lathia, L. Capra. Mining Mobility Data to Minimise Travellers’ Spending on Public Transport. ACM KDD 2011, San Diego, California. N. Lathia, S. Ahmed, L. Capra. Measuring the Impact of Opening the London Shared Bicycle Scheme to Casual Users. In Transportation Research Part C, December 2011. Bike Sharing Research and Practice Google Group http://groups.google.com/group/bikesharingsystemsFriday, 7 December 12

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