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Estimating Parameters of Demand for Trips by Public Bicycle System Using GPS Data

  • Vitalii Naumov
  • Krystian BanetEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1091)

Abstract

Bicycles become one of the main modes of public transport in modern cities. In many cases, they replace private cars and even public buses, especially in the cities with the developed bicycle infrastructure. However, designing and developing public transport systems should be implemented on the grounds of known parameters of demand for travels. The paper describes an approach to the travel demand estimation with the use of data obtained from GPS trackers. The article mainly focuses on data cleaning procedures and the estimations of the demand parameters on the base of the obtained dataset. The authors propose the software for reading raw records from GPX-files and cleaning the data. The case study of the bicycle share system in Kraków, Poland, is discussed in the paper: the results of the data cleansing and estimating demand parameters for recreational trips allocated from the obtained sample are shown.

Keywords

Public bicycle system Demand parameters Data cleansing Recreational trips 

References

  1. Antonakos, C.L.: Environmental and travel preferences of cyclists. Transp. Res. Rec. 1438, 25–33 (1994)Google Scholar
  2. Aultman-Hall, L.: Commuter Bicycle Route Choice: Analysis of Major Determinants and Safety Implications, p. 224. McMaster University, Ontario (1996)Google Scholar
  3. Axhausen, K.W., Smith, R.L.: Bicyclist link evaluation: a stated-preference approach. Transp. Res. Rec. J. Transp. Res. Board 1085, 7–15 (1986)Google Scholar
  4. Bovy, H.L., Bradley, M.A.: Route choice analyzed with stated-preference approaches. Transp. Res. Rec. 1037, 11–20 (1985)Google Scholar
  5. Broach, J., Dill, J., Gliebe, J.: Where do cyclists ride? A route choice model developed with revealed preference GPS data. Transp. Res. Part A Policy Pract. 46(10), 1730–1740 (2012)CrossRefGoogle Scholar
  6. Davis, W.J.: Bicycle test route evaluation for urban road conditions. In: Transportation Congress: Civil Engineers – Key to the World’s Infrastructure, vol. 2, pp. 1063–1076 (1995)Google Scholar
  7. Dekoster, J., Schollaert, U.: Cycling: The Way Ahead for Towns and Cities, p. 63. Office for Official Publications of the European Communities, Luxembourg (1999)Google Scholar
  8. Fall, M., Dąbrowski, M.: Jak rowery miejskie tworzą “smart cities”. In: Biała Księga Mobilności, pp. 118–121 (2015)Google Scholar
  9. Froehlich, J., Neumann, J., Oliver, N.: Sensing and predicting the pulse of the city through shared bicycling. IJCAI Int. J. Conf. Artif. Intell. 3, 1420–1426 (2009)Google Scholar
  10. Guttenplan, M., Patten, R.: Off-road but on track: using bicycle and pedestrian trails for transportation. TR News 178(3), 7–11 (1995)Google Scholar
  11. Hopkinson, P., Wardman, M.: Evaluating the demand for new cycle facilities. Transp. Policy 3(4), 241–249 (1996)CrossRefGoogle Scholar
  12. Hunt, J.D., Abraham, J.E.: Influences on bicycle use. Transportation 34(4), 453–470 (2007)CrossRefGoogle Scholar
  13. Hydén, C., Nilsson, A., Risser, R.: How to enhance WALking and CYcliNG instead of shorter car trips and to make these modes safer. Lund University Faculty of Engineering, Technology and Society, Transport and Roads, Lund, p. 68 (1999)Google Scholar
  14. Jacyna, M., Wasiak, M., Gołębiowski, P.: Model ruchu rowerowego dla Warszawy według Warszawskiego Badania Ruchu 2015. Transport Miejski i Regionalny 10, 5–11 (2016)Google Scholar
  15. Kopta, T., Rudnicki, A.: Planistyczno-realizacyjne aspekty komunikacji rowerowej. Transport Miejski, 5–6 (1996)Google Scholar
  16. Kuzmyak, J.R., Dill, J.: Walking and bicycling in the united states: the who, what, where, and why. TR News 280, 4–15 (2012)Google Scholar
  17. Landis, B.W., Vattikutti, V.R., Brannick, M.: Real-time human perceptions: towards a bicycle level of service. Transp. Res. Rec. 1578, 119–126 (1997)CrossRefGoogle Scholar
  18. Lott, D.Y., Tardiff, T., Lott, D.F.: Evaluation by experienced riders of a new bicycle lane in an established bikeway system. Transp. Res. Rec. 683, 40–46 (1978)Google Scholar
  19. Nair, R., Miller-Hooks, E., Hampshire, R.C., Bušić, A.: Large-scale vehicle sharing systems: analysis of Vélib. Int. J. Sustain. Transp. 7(1), 85–106 (2013)CrossRefGoogle Scholar
  20. Proulx, F.R., Pozdnukhov, A.: Bicycle traffic volume estimation using geographically weighted data fusion. Preprint (2017). http://faculty.ce.berkeley.edu/pozdnukhov/papers/Direct_Demand_Fusion_Cycling.pdf
  21. Pucher, J., Buehler, R.: Cycling for everyone: lessons from Europe. Transp. Res. Rec. J. Transp. Res. Board 2074(12), 58–65 (2008)CrossRefGoogle Scholar
  22. Rakower, R., Łabędzki, J., Gadziński, J.: Konkurencyjność ruchu rowerowego w przestrzeni miejskiej. Transport Miejski i Regionalny 2, 31–38 (2011)Google Scholar
  23. Sener, I.N., Eluru, N., Bhat, C.R.: An analysis of bicycle route choice preferences in Texas, US. Transportation 36(5), 511–539 (2009)CrossRefGoogle Scholar
  24. Sign up for the bike: design manual for a cycle-friendly infrastructure. Centre for Research and Contract Standardization in Civil and Traffic Engineering. The Centre, Ede, p. 325 (1993)Google Scholar
  25. Stinson, M.A., Bhat, C.R.: An analysis of commuter bicyclist route choice using a stated preference survey. Transp. Res. Rec. J. Transp. Res. Board 1828(1), 107–115 (2003)CrossRefGoogle Scholar
  26. Tilahun, N.Y., Levinson, D.M., Krizek, K.J.: Trails, lanes, or traffic: valuing bicycle facilities with an adaptive stated preference survey. Transp. Res. Part A Policy Pract. 41(4), 287–301 (2007)CrossRefGoogle Scholar
  27. Turner, S., Sandt, L., Toole, J., Benz, R., Patten, R.: FHWA University Course on Bicycle and Pedestrian Transportation: Student Workbook. US Department of Transportation, p. 453 (2006)Google Scholar
  28. Twaddle, H., Schendzielorz, T., Fakler, O.: Bicycles in urban areas. Transp. Res. Rec. J. Transp. Res. Board 2434(1), 140–146 (2014)CrossRefGoogle Scholar
  29. Zalewski, A.: Modele ruchu rowerowego w miastach i aglomeracjach. In: Zeszyty Naukowo-Techniczne Stowarzyszenia Inżynierów i Techników Komunikacji w Krakowie. Seria: Materiały Konferencyjne: Ogólnopolska Konferencja Naukowo-Techniczna Modelowanie podróży i prognozowanie ruchu. pp. 263–275 (2009)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Transport Systems DepartmentCracow University of TechnologyKrakowPoland

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