IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v59y2016icp242-249.html
   My bibliography  Save this article

Using smart card and GPS data for policy and planning: The case of Transantiago

Author

Listed:
  • Gschwender, Antonio
  • Munizaga, Marcela
  • Simonetti, Carolina

Abstract

The introduction in 2007 of a new public transport system in Santiago, Chile, brought to us an unexpected gift: the availability of Big Data; massive amounts of passive data obtained from technological devices installed to control the operation of buses and to administer the fare collection process. Many other cities in the world have experienced the same, and sooner or later, this is likely to happen everywhere. Seeing this opportunity, many researchers have developed tools to obtain valuable information from the available data. However, the case of Transantiago is particularly advantageous because all buses have GPS devices and the smart card presents an overall 97% penetration rate.

Suggested Citation

  • Gschwender, Antonio & Munizaga, Marcela & Simonetti, Carolina, 2016. "Using smart card and GPS data for policy and planning: The case of Transantiago," Research in Transportation Economics, Elsevier, vol. 59(C), pages 242-249.
    • Handle: RePEc:eee:retrec:v:59:y:2016:i:c:p:242-249
    DOI: 10.1016/j.retrec.2016.05.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739885915300998
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.retrec.2016.05.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Itf, 2015. "Big Data and Transport: Understanding and Assessing Options," International Transport Forum Policy Papers 8, OECD Publishing.
    2. Gibson, Jaime & Munizaga, Marcela A. & Schneider, Camila & Tirachini, Alejandro, 2016. "Estimating the bus user time benefits of implementing a median busway: Methodology and case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 72-82.
    3. Bass, Pablo & Donoso, Pedro & Munizaga, Marcela, 2011. "A model to assess public transport demand stability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 755-764, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rathachai Chawuthai & Agachai Sumalee & Thanunchai Threepak, 2023. "GPS Data Analytics for the Assessment of Public City Bus Transportation Service Quality in Bangkok," Sustainability, MDPI, vol. 15(7), pages 1-23, March.
    2. Yuhui Guo & Zhiwei Tang & Jie Guo, 2020. "Could a Smart City Ameliorate Urban Traffic Congestion? A Quasi-Natural Experiment Based on a Smart City Pilot Program in China," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    3. Reinhart Buenk & Sara S (Saartjie) Grobbelaar & Isabel Meyer, 2019. "A Framework for the Sustainability Assessment of (Micro)transit Systems," Sustainability, MDPI, vol. 11(21), pages 1-24, October.
    4. Cortés, Cristián E. & Donoso, Pedro & Gutiérrez, Leonel & Herl, Daniel & Muñoz, Diego, 2023. "A recursive stochastic transit equilibrium model estimated using passive data from Santiago, Chile," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    5. Amaya, Margarita & Cruzat, Ramón & Munizaga, Marcela A., 2018. "Estimating the residence zone of frequent public transport users to make travel pattern and time use analysis," Journal of Transport Geography, Elsevier, vol. 66(C), pages 330-339.
    6. Pezoa, Raúl & Basso, Franco & Quilodrán, Paulina & Varas, Mauricio, 2023. "Estimation of trip purposes in public transport during the COVID-19 pandemic: The case of Santiago, Chile," Journal of Transport Geography, Elsevier, vol. 109(C).
    7. Mauricio Herrera & Alex Godoy-Faúndez, 2021. "Exploring the Roles of Local Mobility Patterns, Socioeconomic Conditions, and Lockdown Policies in Shaping the Patterns of COVID-19 Spread," Future Internet, MDPI, vol. 13(5), pages 1-24, April.
    8. Yap, Menno & Munizaga, Marcela, 2018. "Workshop 8 report: Big data in the digital age and how it can benefit public transport users," Research in Transportation Economics, Elsevier, vol. 69(C), pages 615-620.
    9. Jacqueline Arriagada & Claudio Mena & Marcela Munizaga & Daniel Schwartz, 2023. "The effect of economic incentives and cooperation messages on user participation in crowdsourced public transport technologies," Transportation, Springer, vol. 50(5), pages 1585-1612, October.
    10. Herrera, Fernanda & López, Sergio I., 2022. "Bus drivers in competition: A directed location approach," Research in Transportation Economics, Elsevier, vol. 95(C).
    11. Zhao, Pengjun & Cao, Yushu, 2020. "Commuting inequity and its determinants in Shanghai: New findings from big-data analytics," Transport Policy, Elsevier, vol. 92(C), pages 20-37.
    12. Munizaga, Marcela A. & Gschwender, Antonio & Gallegos, Nestor, 2020. "Fare evasion correction for smartcard-based origin-destination matrices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 307-322.
    13. Gramsch, Benjamin & Guevara, C. Angelo & Munizaga, Marcela & Schwartz, Daniel & Tirachini, Alejandro, 2022. "The effect of dynamic lockdowns on public transport demand in times of COVID-19: Evidence from smartcard data," Transport Policy, Elsevier, vol. 126(C), pages 136-150.
    14. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    15. Fangye Du & Jiaoe Wang & Yu Liu & Zihao Zhou & Haitao Jin, 2022. "Equity in Health-Seeking Behavior of Groups Using Different Transportations," IJERPH, MDPI, vol. 19(5), pages 1-16, February.
    16. Cristina Pronello & Davide Longhi & Jean-Baptiste Gaborieau, 2018. "Smart Card Data Mining to Analyze Mobility Patterns in Suburban Areas," Sustainability, MDPI, vol. 10(10), pages 1-21, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas E. Guerrero & C. Angelo Guevara & Elisabetta Cherchi & Juan de Dios Ortúzar, 2021. "Addressing endogeneity in strategic urban mode choice models," Transportation, Springer, vol. 48(4), pages 2081-2102, August.
    2. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2019. "Reliable single-allocation hub location problem with disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 123(C), pages 90-120.
    3. Holod, Dmytro & Torna, Gökhan, 2018. "Do community banks contribute to international trade? Evidence from U.S. Data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 185-204.
    4. Günter Knieps, 2019. "Internet der Dinge und die Zukunft der Netzökonomie [Internet of Things and the Future of Network Economics]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 99(5), pages 348-354, May.
    5. Tyndall, Justin, 2018. "Bus quality improvements and local commuter mode share," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 173-183.
    6. Luis André Wernecke Fumagalli & Denis Alcides Rezende & Thiago André Guimarães, 2022. "Data Intelligence in Public Transportation: Sustainable and Equitable Solutions to Urban Modals in Strategic Digital City Subproject," Sustainability, MDPI, vol. 14(8), pages 1-16, April.
    7. Bastani, Parisa & Heywood, John B. & Hope, Chris, 2012. "The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 517-548.
    8. Espadaler-Clapés, Jasso & Barmpounakis, Emmanouil & Geroliminis, Nikolas, 2023. "Empirical investigation of lane usage, lane changing and lane choice phenomena in a multimodal urban arterial," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    9. Wang, Jiangbo & Yamamoto, Toshiyuki & Liu, Kai, 2022. "Exploring the subscribing behavior of customized bus passengers: Active users versus inactive users," Journal of choice modelling, Elsevier, vol. 43(C).
    10. Fielbaum, Andrés & Jara-Diaz, Sergio, 2021. "Assessment of the socio-spatial effects of urban transport investment using Google Maps API," Journal of Transport Geography, Elsevier, vol. 91(C).
    11. Guenter Knieps, 2021. "Data-driven sector coupling in 5G-based smart networks," Competition and Regulation in Network Industries, , vol. 22(1), pages 53-68, March.
    12. Boon Ean Teoh & S. G. Ponnambalam & Nachiappan Subramanian, 2018. "Data driven safe vehicle routing analytics: a differential evolution algorithm to reduce CO $$_{2}$$ 2 emissions and hazardous risks," Annals of Operations Research, Springer, vol. 270(1), pages 515-538, November.

    More about this item

    Keywords

    Public transport; Passive data; Automatic vehicle location; Automatic fare collection;
    All these keywords.

    JEL classification:

    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:retrec:v:59:y:2016:i:c:p:242-249. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/620614/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.