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Interactions Impacting Bicycle Service Measures: Insights from Research

Explore the significance of interactions in determining service measures for bicycles through research findings. Analyze the quality of service, capacity of motor and pedestrian infrastructure, and the social dynamics affecting cycling behavior. The study assesses the relationship between interactions and service quality, using models to simulate various scenarios. Findings reveal a lack of quantitative measures for assessing service capacity and highlight the importance of considering service quality for optimal flow rates. This research prompts a deeper understanding of how interactions influence the overall biking experience and emphasizes the need for robust evaluation metrics.

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Interactions Impacting Bicycle Service Measures: Insights from Research

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  1. The importance of interactions in determining service measures for bicycles Chris Osowskichris.osowski@soton.ac.uk – www.osowski.co.ukInstitute for Complex Systems Science, University of Southampton Ben Watersonb.j.waterson@soton.ac.ukTransportation Research Group, University of Southampton

  2. Is this good? From: Warrington Cycle Campaign “Cycle Facility of the Month” (http://goo.gl/EiBnDv)

  3. Are these value for money? From: Warrington Cycle Campaign “Cycle Facility of the Month” (http://goo.gl/EiBnDv)

  4. How good is this?

  5. Capacity of Motor Infrastructure From: Transportation Research Board. (2010). Highway Capacity Manual.

  6. Capacity of Motor Infrastructure From: www.flownz.com

  7. Capacity of Pedestrian Infrastructure From: Colin Buchanan Ltd. (2010) From: Fruin, J. J. (1971). Pedestrian Planning and Design From: Halcrow Group Ltd. (2005)

  8. Capacity of CycleInfrastructure From: Navin, F. P. D. (1994). Bicycle Traffic Flow Characteristics: Experimental Results and Comparisons. ITE Journal, (March), 31–36.

  9. A Quote from Fruin… “[...] many authorities are using maximum capacity ratings for dimensioning pedestrian space. No evaluation or consideration of human convenience has been made in developing these design standards. The flow curves [... demonstrate] that the maximum capacity of a pedestrian traffic scheme is attained only when there is a dense crowding of pedestrians.” From: Fruin, J. J. (1971). Pedestrian Planning and Design

  10. Capacity of CycleInfrastructure

  11. What about Quality of Service? • Botma(1995) assumed no impedance; i.e. fixed speed. • Does this matter…? • Can we use simulation tools, take the best practice of the simulation of other modes and cross-apply itto find out?

  12. Use Pedestrian Modelling? From: Colin Buchanan Ltd. (2010) • Often continuous space (2D) models. • Successful tools at variety of scales • Pedroute • Legion • VisWalk • … From: Halcrow Group Ltd. (2005)

  13. The Social Force Model • Helbing, D., & Molnár, P. (1995). Social force model for pedestrian dynamics. Physical Review E, 51(5), 4282–4286. • “Motivation to act”

  14. Our Model – Purpose • Do interactions matter? From: CXMagazine.com

  15. Our Model – Implementation • Agent Based Model • 2 dimensional continuous space • Unidirectional flow • Fixed path width • Parallel boundaries

  16. Our Model – Force Generation

  17. SFM – Directional Perception • In Helbing and Molnár (2005):

  18. Our Model – Directional Perception

  19. SFM vs Our Model

  20. Our Model – Parameters and Outputs • Bicycle behavioural parameters: • Generally from CROW (2007) • Exploratory variables: • Path Width and Bicycle Arrival Rate • Output data: • Average speed, average crashing proportion, average distance to the nearest bicycle, etc.

  21. Results – Speed vs. Flow High Quality Poor Quality Variable Quality

  22. Results – Crashes (No impedance)

  23. Results – Crashes • Flow breakdown with speed-selection occurs primarily as multi-bicycle collisions at the entry: • Without speed-selection:

  24. Results – Literature Comparison

  25. Conclusions • Lack of robust quantitative measures for capacity or quality of service. • Inherent assumption that service quality is satisfactory up to capacity… …bicycles do not interact in a meaningful way.

  26. Conclusions • 2Dmicrosimulation model using the SFM. • Basic behavioural traits applied. • Data show qualitatively different result... …sudden collapse in quality of service. • Modellingconfirms intuition that we can’t ignore service quality for non-trivial flow rates.

  27. Acknowledgements • EPSRC Doctoral Training Centre grant: EP/G03690X/1 • University of Southampton: • Institute for Complex Systems Simulation www.icss.soton.ac.uk • Transportation Research Group www.trg.soton.ac.uk • IRIDIS High Performance Computing Facility (and support services)

  28. Questions? Paper at: https://db.tt/8APJ8Vrk

  29. Maths…

  30. Our Model – Algorithm

  31. Bicycle Arrival Rate – Proximity

  32. Barriers to Cycling • TfGM, 2011

  33. Barriers to Cycling From: City of Copenhagen. (2011). Copenhagen: City of Cyclists - Bicycle Account 2010.

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