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Bike-sharing system in Poznan – what will Web API data tell us?

Treść / Zawartość
Warianty tytułu
PL
System rowerów miejskich w Poznaniu - co nam powiedzą dane z Web API?
Języki publikacji
EN
Abstrakty
EN
Bike-sharing systems, also known as public bicycles, are among the most dynamically developing mobility solutions in contemporary cities. In the past decade, numerous Polish cities hoping to increase the modal share of cycling have also adopted bike-sharing. Such systems continuously register user movements through installed sensors. The resulting database allows a highly detailed representation of this segment of urban mobility. This article illustrates how a database accessed via a Web API (Web Application Programming Interface) could be used to investigate the spatial distribution of trips, using the case study of Poznań, the fifth-largest city in Poland. Using geographical information systems, we identify the hot spots of bike-sharing as well as areas with low usage. The research procedure outlined in the paper provides knowledge that allows better responding to users’ needs.
Twórcy
  • Department of Spatial Econometrics, Faculty of Human Geography and Planning, Adam Mickiewicz University in Poznań, Krygowskiego 10, 61-680 Poznań, Poland
  • Department of Spatial Econometrics, Faculty of Human Geography and Planning, Adam Mickiewicz University in Poznań, Krygowskiego 10, 61-680 Poznań, Poland
  • Department of Regional and Local Studies, Faculty of Human Geography and Planning, Adam Mickiewicz University in Poznań, Krygowskiego 10, 61-680 Poznań, Poland
Bibliografia
  • [1] Bieliński, T., Kwapisz, A., Ważna, A., 2019. Bike-Sharing Systems in Poland, Sustainability, 11, 2458. (DOI 10.3390/su11092458).
  • [2] Buehler, R., & Pucher, J., 2017. Trends in walking and cycling safety: Recent evidence from high-income countries, with a focus on the United States and Germany. American Journal of Public Health, 107(2), 281–287. (DOI 10.2105/AJPH.2016.303546).
  • [3] Caulfield, B., O’Mahony, M., Brazil, W., Weldon, P., 2017. Examining usage patterns of a bike-sharing scheme in a medium sized city, Transportation Research Part A: Policy and Practice, 100, 152–161. (DOI 10.1016/j.tra.2017.04.023).
  • [4] Demsar, J. i in. Orange: Data Mining Toolbox in Python, Journal of Machine Learning Research, 14, 2349–2353, 2013.
  • [5] Dębowska-Mróz M., Lis P., Szymanek A., Zawisza T., 2017, Rower miejski jako element systemu transportowego w miastach, Autobusy, 6, 1173-1182.
  • [6] Du, M., Cheng, L., 2018. Better Understanding the Characteristics and Influential Factors of Different Travel Patterns in Free-Floating Bike Sharing: Evidence from Nanjing, China, Sustainability, 10, 1244. (DOI 10.3390/su10041244).
  • [7] Du, Y., Deng, F., Liao, F., 2019. A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system. Transportation Research Part C: Emerging Technologies, 103, 39–55. (DOI 10.1016/j.trc.2019.04.006).
  • [8] Faghih-Imani, A., Eluru, N., El-Geneidy, A.M., Rabbat, M., Haq, U., 2014. How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal. Journal of Transport Geography, 41, 306–314. (DOI 10.1016/j.jtrangeo.2014.01.013).
  • [9] Faghih-Imani, A., Hampshire, R., Marla, L., & Eluru, N. (2017). An empirical analysis of bike sharing usage and rebalancing: Evidence from Barcelona and Seville. Transportation Research Part A: Policy and Practice, 97, 177–191. (DOI 10.1016/j.tra.2016.12.007).
  • [10] Fishman, E., 2016. Bikeshare: A Review of Recent Literature. Transport Reviews, 36, 92–113. (DOI 10.1080/01441647.2015.1033036).
  • [11] Giot, R., Cherrier, R., 2014. Predicting bikeshare system usage up to one day ahead, [in:] 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS). Presented at the 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS), IEEE, Orlando, FL, USA, 22–29. (DOI 10.1109/CIVTS.2014.7009473).
  • [12] Goodman, A., Cheshire, J., 2014. Inequalities in the London bicycle sharing system revisited: impacts of extending the scheme to poorer areas but then doubling prices. Journal of Transport Geography, 41, 272–279. (DOI 10.1016/j.jtrangeo.2014.04.004).
  • [13] Heidelberg Institute for Geoinformation Technology, https://openrouteservice.org/dev/#/api-docs/directions/get [24.02.2020].
  • [14] Jensen, P., Rouquier, J.-B., Ovtracht, N., Robardet, C., 2010. Characterizing the speed and paths of shared bicycle use in Lyon. Transportation Research Part D: Transport and Environment, 15, 522–524. (DOI 10.1016/j.trd.2010.07.002).
  • [15] Jiménez, P., Nogal, M., Caulfield, B., Pilla, F., 2016. Perceptually important points of mobility patterns to characterise bike sharing systems: The Dublin case. Journal of Transport Geography, 54, 228–239. (DOI 10.1016/j.jtrangeo.2016.06.010).
  • [16] Kwiatkowski M.A., 2018, Bike-sharing-boom – rozwój nowych form zrównoważonego transportu w Polsce na przykładzie roweru publicznego, Prace Komisji Geografii Komunikacji PTG, 21(3), 60–69. (DOI: 10.4467/2543859XPKG.18.017.10142).
  • [17] Łastowska A., Bryniarska Z., 2015, Analiza funkcjonowania wypożyczalni rowerów miejskich w Krakowie, Transport Miejski i Regionalny, 03, 30-35.
  • [18] Martin, E.W., Shaheen, S.A., 2014. Evaluating public transit modal shift dynamics in response to bikesharing: a tale of two U.S. cities. Journal of Transport Geography, 41, 315–324. (DOI 10.1016/j.jtrangeo.2014.06.026).
  • [19] Médard de Chardon, C., 2019. The contradictions of bike-share benefits, purposes and outcomes. Transportation Research Part A: Policy and Practice, 121, 401–419. (DOI 10.1016/j.tra.2019.01.031).
  • [20] Médard de Chardon, C., Caruso, G., 2015. Estimating bike-share trips using station level data. Transportation Research Part B: Methodological, 78, 260–279. (DOI 10.1016/j.trb.2015.05.003).
  • [21] Médard de Chardon, C., Caruso, G., Thomas, I., 2016. Bike-share rebalancing strategies, patterns, and purpose. Journal of Transport Geography, 55, 22–39. (DOI 10.1016/j.jtrangeo.2016.07.003).
  • [22] Médard de Chardon, C., Caruso, G., Thomas, I., 2017. Bicycle sharing system ‘success’ determinants. Transportation Research Part A: Policy and Practice, 100, 202–214. (DOI 10.1016/j.tra.2017.04.020).
  • [23] Nextbike Web API, http://api.nextbike.net/maps/nextbike-live.xml?city=192 [03.02.2020].
  • [24] O’Brien, O., Cheshire, J., Batty, M., 2014. Mining bicycle sharing data for generating insights into sustainable transport systems. Journal of Transport Geography, 34, 262–273. (DOI 10.1016/j.jtrangeo.2013.06.007).
  • [25] 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. (DOI 10.1016/j.jtrangeo.2013.06.003).
  • [26] Poznański Rower Miejski, https://poznanskirower.pl/ [03.02.2020].
  • [27] Raux, C., Zoubir, A., Geyik, M., 2017. Who are bike sharing schemes members and do they travel differently? The case of Lyon’s “Velo’v” scheme. Transportation Research Part A: Policy and Practice, 106, 350–363. (DOI 10.1016/j.tra.2017.10.010).
  • [28] Ricci, M., 2015. Bike sharing: A review of evidence on impacts and processes of implementation and operation. Research in Transportation Business & Management, 15, 28–38. (DOI 10.1016/j.rtbm.2015.03.003).
  • [29] Romanillos, G., Zaltz Austwick, M., Ettema, D., De Kruijf, J., 2016. Big Data and Cycling. Transport Reviews, 36, 114–133. (DOI 10.1080/01441647.2015.1084067).
  • [30] Shen, Y., Zhang, X., Zhao, J., 2018. Understanding the usage of dockless bike sharing in Singapore. International Journal of Sustainable Transportation, 12, 686–700. (DOI 10.1080/15568318.2018.1429696).
  • [31] Sun, F., Chen, P., Jiao, J., 2018. Promoting public bike-sharing: A lesson from the unsuccessful Pronto system. Transportation Research Part D: Transport and Environment, 63, 533–547. (DOI 10.1016/j.trd.2018.06.021).
  • [32] Wang, K., Akar, G., 2019. Gender gap generators for bike share ridership: Evidence from Citi Bike system in New York City. Journal of Transport Geography, 76, 1–9. (DOI 10.1016/j.jtrangeo.2019.02.003).
  • [33] Winters, M., Hosford, K., Javaheri, S., 2019. Who are the ‘super-users’ of public bike share? An analysis of public bike share members in Vancouver, BC. Preventive Medicine Reports, 15, 100946. (DOI 10.1016/j.pmedr.2019.100946).
  • [34] Woodcock, J., Tainio, M., Cheshire, J., O’Brien, O., Goodman, A., 2014. Health effects of the London bicycle sharing system: health impact modelling study. BMJ, 348, g425–g425. (DOI 10.1136/bmj.g425).
  • [35] Yao, Y., Zhang, Y., Tian, L., Zhou, N., Li, Z., Wang, M., 2019. Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System. Sustainability, 11, 5425. (DOI 10.3390/su11195425).
  • [36] Zhang, Y., Mi, Z., 2018. Environmental benefits of bike sharing: A big data-based analysis. Applied Energy, 220, 296–301. (DOI 10.1016/j.apenergy.2018.03.101).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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