AGILE 2015 pp 201-217 | Cite as

Usage Differences Between Bikes and E-Bikes

Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

A high share of bicycle traffic in urban areas can be advantageous in order to tackle traffic related problems such as congestion, over-crowded public transportation or air pollution. Through an increased dissemination of e-bikes in recent years, cycling has become a viable transportation alternative for an even broader audience. The consequences of this trend on urban mobility are not yet clear. In order to get a clearer picture, one first needs to understand the major usage differences between e-bikers and cyclists. In this paper we demonstrate how a first insight into these differences can be gained by analysing GPS tracking data, recorded within the context of a field study. E-bikers as well as conventional cyclists prefer riding on any kind of bike trail whilst e-bikers rather choose bike trail types with a larger exposure to vehicular traffic. Taking a minimal distance route was the most important route choice factor for both cyclists and e-bikers. E-bikers perceived their rides to be slightly more safe and convenient as compared to conventional cyclists.

Keywords

Urban mobility Route choice Tracking data Bikes E-bikes Field study 

References

  1. Aultmann-Hall, L., Hall, F., & Baetz, B. (1997). Analysis of bicycle commuter routes using geographic information systems: Implications for bicycle planning. Transportation Research Record: Journal of the Transportation Research Record, 1578, 102–110.CrossRefGoogle Scholar
  2. Ben-Akiva, M., Bradley, B., Morikawa, T., Benjamin, J., Novak, T., Oppewal, H., et al. (1994). Combining revealed and stated preferences data. Marketing Letters, 5(4), 335–349.CrossRefGoogle Scholar
  3. Bohte, W., Maat, K., & Quak, W. A. (2008). A method for deriving trip destinations and modes for GPS-based travel surveys. In J. Van Schaick & S. C. Van der Spek (Eds.), Urbanism on track (pp. 129–145). Amsterdam, The Netherlands: IOS Press.Google Scholar
  4. Brick, E., McCarthy, O. T., & Caulfield, B. (2012). Determining bicycle infrastructure preferences—a case study of Dublin. Transportation Research Part D: Transport and Environment, 17(5), 413–417.CrossRefGoogle Scholar
  5. Broach, J., Dill, J., & Gliebe, J. (2012). Where do cyclists ride? A bicycle route choice model developed with revealed preference GPS data. Transportation Research Part A: Policy and Practice, 46(10), 1730–1740.Google Scholar
  6. Cellina, F., Förster, A., Rivola, D., Pampuri, L., Rudel, R., & Rizzoli, A. E. (2013). Using smartphones to profile mobility patterns in a living lab for the transition to e-mobility. In J. Hřebíček, G. Schimak, M. Kubásek, & A. E. Rizzoli (Eds.), Environmental software systems. Fostering information sharing, IFIP advances in information and communication technology (Vol. 413, pp. 154–163). Berlin, Germany: Springer.Google Scholar
  7. Cherry, C., Worley, S., & Jordan, D. (2011). Electric bike sharing—system requirements and operational concepts. Paper presented at the 90th annual meeting of the Transportation Research Board, Washington, January 2011.Google Scholar
  8. Chung, E.-H., & Shalaby, A. (2005). A trip reconstruction tool for GPS-based personal travel surveys. Transportation Planning and Technology, 28(5), 381–401.CrossRefGoogle Scholar
  9. Dalumpines, R., & Scott, D. M. (2011). GIS-based map-matching: Development and demonstration of a postprocessing map-matching algorithm for transportation research. In S. Geertman, W. Reinhardt, & F. Toppen (Eds.), Advancing geoinformation science for a changing world (pp. 101–120). Berlin, Germany: Springer.CrossRefGoogle Scholar
  10. De Hartog, J. J., Boogaard, H., Nijland, H., & Hoek, G. (2010). Do the health benefits of cycling outweigh the risks? Environmental Health Perspectives, 118(8), 1109–1116.CrossRefGoogle Scholar
  11. DeMaio, P. (2009). Bike-sharing: History, impacts, models of provision, and future. Journal of Public Transportation, 12(4), 41–56.CrossRefGoogle Scholar
  12. Dill, J. (2009). Bicycling for transportation and health: The role of infrastructure. Journal of Public Health Policy, 30, 95–110.CrossRefGoogle Scholar
  13. Dill, J., & Rose, G. (2012). Electric bikes and transportation policy: Insights from early adopters. Transportation Research Record: Journal of the Transportation Research Board, 2314, 1–6.CrossRefGoogle Scholar
  14. Fajans, J., & Curry, M. (2001). Why bicyclists hate stop signs. Access, 18(1), 28–31.Google Scholar
  15. Golledge, R. G. (1995). Defining the criteria used in path selection. Paper presented at the international conference on activity based approaches: Activity scheduling and the analysis of activity patterns, Eindhoven, The Netherlands, May 1995.Google Scholar
  16. Golledge, R. G., & Stimson, R. J. (1997). Spatial behavior: A geographic perspective. New York: Guilford Press.Google Scholar
  17. Harvey, F. J., & Krizek, K. (2007). Commuter bicyclist behavior and facility disruption. St. Paul, Minnesota: Minnesota Department of Transportation, Research Services Section.Google Scholar
  18. Heinen, E., Maat, K., & van Wee, B. (2013). The effect of work-related factors on the bicycle commute mode choice in the Netherlands. Transportation, 40(1), 23–43.CrossRefGoogle Scholar
  19. Heinen, E., van Wee, B., & Maat, K. (2010). Commuting by bicycle: An overview of the literature. Transport Reviews: A Transnational Transdisciplinary Journal, 30(1), 59–96.CrossRefGoogle Scholar
  20. Hunt, J. D., & Abraham, J. E. (2007). Influences on bicycle use. Transportation, 43(4), 453–470.CrossRefGoogle Scholar
  21. Kroes, E. P., & Sheldon, R. J. (1988). Stated preference methods. An introduction. Journal of Transport Economics and Policy, 22(1), 11–26.Google Scholar
  22. Menghini, G., Carrasco, N., Schüssler, N., & Axhausen, K. W. (2010). Route choice of cyclists in Zürich. Transportation Research Part A: Policy and Practice, 44(9), 754–765.Google Scholar
  23. Montello, D. R. (2005). Navigation. In P. Shah & A. Miyake (Eds.), The Cambridge handbook of visuospatial thinking. Cambridge: Cambridge University Press.Google Scholar
  24. Parkes, S. D., Marsden, G., Shaheen, S. A., & Cohen, A. P. (2013). Understanding the diffusion of public bikesharing systems: Evidence from Europe and North America. Journal of Transport Geography, 31, 94–103.CrossRefGoogle Scholar
  25. Popovich, N., Gordon, E., Shao, Z., Xing, Y., Wang, Y., & Handy, S. (2014). Experiences of electric bicycle users in the Sacramento, California area. Travel Behavior and Society, 1(2), 37–44.CrossRefGoogle Scholar
  26. Rondinella, G., Fernandez-Heredia, A., & Monzon, A. (2012). Analysis of perceptions of utilitarian cycling by level of user experience. In Proceedings of Transport Research Board Annual Meeting 2012, Washington, DC.Google Scholar
  27. Rose, G. (2012). E-bikes and urban transportation: Emerging issues and unresolved questions. Transportation, 39(1), 81–96.CrossRefGoogle Scholar
  28. Shaheen, S. A., Guzman, S., & Zuang, H. (2010). Bikesharing in Europe, the Americas, and Asia. Transportation Research Record: Journal of the Transportation Research Board, 2143, 159–167.CrossRefGoogle Scholar
  29. Stinson, M. A., & Bhat, C. R. (2003). Commuter bicyclist route choice: Analysis using a stated preference survey. Transportation Research Record: Journal of the Transportation Research Board, 1828, 107–115.CrossRefGoogle Scholar
  30. Stinson, M. A., & Bhat, C. R. (2005). A comparison of route preferences of experienced and inexperienced bicycle commuters. Paper presented at the 84th annual meeting of the Transportation Research Board, Washington, January 2005.Google Scholar
  31. Stopher, P., Bullock, P., & Horst, F. (2002). Exploring the use of passive GPS devices to measure travel. In Proceedings of the 7th International Conference on Application of Advanced Technologies in Transportation (pp. 959–967). MA, USA: Cambridge.Google Scholar
  32. Taylor, D., & Mahmassani, H. (1996). Analysis of stated preferences for intermodal bicycle-transit interfaces. Transportation Research Record: Journal of the Transportation Research Board, 1556, 86–95.CrossRefGoogle Scholar
  33. Tsui, A., & Shalaby, A. (2006). Enhanced system for link and mode identification for personal travel surveys based on global positioning systems. Transportation Research Record: Journal of the Transportation Research Board, 1972, 38–45.CrossRefGoogle Scholar
  34. United Nations. (2012). World urbanization prospects: The 2011 revision. New York: Department of Economic and Social Affairs, Population Division, United Nations. Available online: http://de.slideshare.net/undesa/wup2011-highlights. Accessed 15 November 2014.
  35. Van der Spek, S. (2008). Tracking pedestrians in historic city centres using GPS. In S. Van der Spek, F. D. Van der Hoeven, & M. G. J. Smit (Eds.), Street level desires (pp. 86–111). Delft, The Netherlands: Delft University of Technology Urbanism.Google Scholar
  36. Van der Spek, S., Van Schaick, J., De Bois, P., & De Haan, R. (2009). Sensing human activity: GPS tracking. Sensors, 9(4), 3033–3055.CrossRefGoogle Scholar
  37. Van Evert, H., Brög, W., & Erl, E. (2006). Survey design: The past, the present and the future. In P. Stopher & C. Stecher (Eds.), Travel survey methods—quality and future directions (pp. 75–93). Amsterdam, Oxford: Elsevier.Google Scholar
  38. Weinert, J. X., Ma, C. T., Yang, X. M., & Cherry, C. (2008). The transition to electric bikes in China: Effect on travel behavior, mode shift, and user safety perceptions in a medium-sized city. Transportation Research Record: Journal of the Transportation Research Board, 2038, 62–68.CrossRefGoogle Scholar
  39. Wolf, J. (2006). Application of new technologies in travel surveys. In P. Stopher & C. Stecher (Eds.), Travel survey methods—quality and future directions (pp. 531–544). Amsterdam, Oxford: Elsevier.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Institute of Cartography and GeoinformationETH ZurichZurichSwitzerland

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