Abstract
Information and Communication Technology is increasingly recognised as a key element for the ability of cycling mobility initiatives to create real, profound, incremental and measurable impact. Even though previous work has extensively explored many applications of smart cycling data, the first challenge is to actually produce consistent cycling data in a systematic way. In this research, we explore the range of sensors which could be more relevant to integrate into urban bicycles to support the systematic collection of data about cycle routes. To gain a deeper insight into the real-world challenges of systematic cycle-based sensing, we conducted an experimental data collection. We equipped a bicycle with a diverse set of low-cost sensors, and we collected data in a pre-defined route, in which it was possible to experience very diverse environmental circumstances regarding road surface or the level of surrounding traffic. The results highlight some of the practical challenges that can be faced by systematic sensing for urban cycling, suggesting that not all sensors might be appropriate for this type of large-scale deployment on bicycles. The main contribution is a set of design implications, which should help to inform the design of novel sensing systems for bicycles.
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References
Violeta Bulc: Cycling: green and efficient transport for the future. European Commission (2016). https://ec.europa.eu/commission/commissioners/2014-2019/bulc/blog/cycling-green-and-efficient-transport-future_en. Accessed 31 Oct 2019
Lee, J., Leem, Y.T., Lee, S.H.: Categorizing U-Bike service and assessing its adoptability under it-. In: 12th World Conference for Transportation Research, pp. 1–10 (2010)
Ricci, M.: Bike sharing: a review of evidence on impacts and processes of implementation and operation. Res. Transp. Bus. Manag. 15, 28–38 (2015)
Li, S.: Cycling in Toronto: route choice behavior and implications to infrastructure planning. Master thesis. University of Waterloo (2017)
Harvey, F., Krizek, K.: Commuter bicyclist behavior and facility disruption. Transp. Res. Board 60 (2007)
Winters, M., Davidson, G., Kao, D., Teschke, K.: Motivators and deterrents of bicycling: comparing influences on decisions to ride. Transportation 38(1), 153–168 (2011)
Félix, R.: Gestão da Mobilidade em Bicicleta Master thesis, Engenharia do Território. Universidade Técnica de Lisboa (2012)
Hochmair, H.: Decision support for bicycle route planning in urban environments. In: 7th AGILE Conference on Geographic Information Science, pp. 697–706 (2004)
Srivastava, M., Abdelzaher, T., Szymanski, B.: Human-centric sensing. Philos. Trans. R. Soc. A: Math. Phys. Eng. Sci. 370(1958), 176–197 (2012)
Torres, S., Lalanne, F., Del Canto, G., Morales, F., Bustos-Jimenez, J., Reyes, P.: BeCity: sensing and sensibility on urban cycling for smarter cities. In: Proceedings - International Conf of the Chilean Computer Science Society, SCCC 2016 (2016)
Eisenman, S.B., Miluzzo, E., Lane, N.D., Peterson, R.A., Ahn, G.-S., Campbell, A.T.: BikeNet. ACM Trans. Sens. Netw. 6(1), 1–39 (2009)
Verstockt, S., Slavkovikj, V., De Potter, P., Van De Walle, R.: Collaborative bike sensing for automatic geographic enrichment: geoannotation of road/terrain type by multimodal bike sensing. IEEE Signal Process. Mag. 31(5), 101–111 (2014)
Reddy, S., Shilton, K., Denisov, G.: Biketastic: sensing and mapping for better biking. In: Proceedings of the 28th International Conference on Human factors in Computing Systems, pp. 9–12 (2010)
Elen, B., et al.: The Aeroflex: a bicycle for mobile air quality measurements. Sens. (Switz.) 13(1), 221–240 (2013)
Auer, E., et al.: ELAN as flexible annotation framework for sound and image processing detectors. In: Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC 2010), European Language Resources Association (ELRA), pp. 890–893 (2010)
Zhao, M., Stasinopoulos, S., Yu, Y.: Obstacle detection and avoidance for autonomous bicycles. In: IEEE International Conference on Automation Science and Engineering, 2017 August, pp. 1310–1315.1 (2018)
Acknowledgements
This work has been supported by national funds through FCT, Fundação para a Ciência e Tecnologia, within the Project Scope: UID/CEC/00319/2019, and also by the European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039334; Funding Reference: POCI-01-0247-FEDER-039334].
Development of the Arduino code was made by André Torrinha, Marcelo Alves, Pedro Lobo and Rui Almeida as part of a Masters’ Project.
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Costa, M., José, R. (2020). Challenges and Limitations for the Systematic Collection of Cycling Data from Bike Sensors. In: Santos, H., Pereira, G., Budde, M., Lopes, S., Nikolic, P. (eds) Science and Technologies for Smart Cities. SmartCity 360 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-030-51005-3_8
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DOI: https://doi.org/10.1007/978-3-030-51005-3_8
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