IDEAS home Printed from https://ideas.repec.org/p/ags/ndtr16/319310.html
   My bibliography  Save this paper

Expansion of a GPS Truck Trip Sample to Remove Bias and Obtain Representative Flows for Ontario

Author

Listed:
  • Gingerich, Kevin
  • Maoh, Hanna
  • Anderson, William

Abstract

No abstract is available for this item.

Suggested Citation

  • Gingerich, Kevin & Maoh, Hanna & Anderson, William, 2016. "Expansion of a GPS Truck Trip Sample to Remove Bias and Obtain Representative Flows for Ontario," 57th Transportation Research Forum (51st CTRF) Joint Conference, Toronto, Ontario, May 1-4, 2016 319310, Transportation Research Forum.
    • Handle: RePEc:ags:ndtr16:319310
    DOI: 10.22004/ag.econ.319310
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/319310/files/agecon-trf-1428.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.319310?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
    ---><---

    References listed on IDEAS

    as
    1. Stopher, Peter R. & Greaves, Stephen P., 2007. "Household travel surveys: Where are we going?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 367-381, June.
    2. Du, Jianhe & Aultman-Hall, Lisa, 2007. "Increasing the accuracy of trip rate information from passive multi-day GPS travel datasets: Automatic trip end identification issues," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(3), pages 220-232, March.
    Full references (including those not matched with items on IDEAS)

    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. Chen, Cynthia & Gong, Hongmian & Lawson, Catherine & Bialostozky, Evan, 2010. "Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 830-840, December.
    2. Mehrdad Bagheri & Miloš N. Mladenović & Iisakki Kosonen & Jukka K. Nurminen, 2020. "Analysis of Potential Shift to Low-Carbon Urban Travel Modes: A Computational Framework Based on High-Resolution Smartphone Data," Sustainability, MDPI, vol. 12(15), pages 1-26, July.
    3. Jariyasunant, Jerald & Carrel, Andre & Ekambaram, Venkatesan & Gaker, DJ & Kote, Thejovardhana & Sengupta, Raja & Walker, Joan L., 2011. "The Quantified Traveler: Using personal travel data to promote sustainable transport behavior," University of California Transportation Center, Working Papers qt9jg0p1rj, University of California Transportation Center.
    4. Yijing Lu & Lei Zhang, 2015. "Imputing trip purposes for long-distance travel," Transportation, Springer, vol. 42(4), pages 581-595, July.
    5. Aihua Fan & Xumei Chen, 2020. "Exploring the Relationship between Transport Interventions, Mode Choice, and Travel Perception: An Empirical Study in Beijing, China," IJERPH, MDPI, vol. 17(12), pages 1-19, June.
    6. Li, Linchao & Zhu, Jiasong & Zhang, Hailong & Tan, Huachun & Du, Bowen & Ran, Bin, 2020. "Coupled application of generative adversarial networks and conventional neural networks for travel mode detection using GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 282-292.
    7. Winters, Meghan & Voss, Christine & Ashe, Maureen C. & Gutteridge, Kaitlyn & McKay, Heather & Sims-Gould, Joanie, 2015. "Where do they go and how do they get there? Older adults' travel behaviour in a highly walkable environment," Social Science & Medicine, Elsevier, vol. 133(C), pages 304-312.
    8. Jariyasunant, Jerald & Carrel, Andre & Ekambaram, Venkatesan & Gaker, DJ & Kote, Thejovardhana & Sengupta, Raja & Walker, Joan L., 2011. "The Quantified Traveler: Using personal travel data to promote sustainable transport behavior," University of California Transportation Center, Working Papers qt678537sx, University of California Transportation Center.
    9. Tao Feng & Harry J.P. Timmermans, 2016. "Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(2), pages 180-194, March.
    10. Patrick Bonnel & Etienne Hombourger & Ana-Maria Olteanu-Raimond & Zbigniew Smoreda, 2015. "Passive Mobile Phone Dataset to Construct Origin-destination Matrix: Potentials and Limitations," Post-Print halshs-01664219, HAL.
    11. Lukas Hartwig & Reinhard Hössinger & Yusak Octavius Susilo & Astrid Gühnemann, 2022. "The Impacts of a COVID-19 Related Lockdown (and Reopening Phases) on Time Use and Mobility for Activities in Austria—Results from a Multi-Wave Combined Survey," Sustainability, MDPI, vol. 14(12), pages 1-24, June.
    12. Michael Adjemian & Jeffrey Williams, 2009. "Using census aggregates to proxy for household characteristics: an application to vehicle ownership," Transportation, Springer, vol. 36(2), pages 223-241, March.
    13. Nina Verzosa & Stephen Greaves & Chinh Ho & Mark Davis, 2021. "Stated willingness to participate in travel surveys: a cross-country and cross-methods comparison," Transportation, Springer, vol. 48(3), pages 1311-1327, June.
    14. Hannah Badland & Phil Donovan & Suzanne Mavoa & Melody Oliver & Moushumi Chaudhury & Karen Witten, 2015. "Assessing neighbourhood destination access for children: development of the NDAI-C audit tool," Environment and Planning B, , vol. 42(6), pages 1148-1160, November.
    15. Laranjeiro, Patrícia F. & Merchán, Daniel & Godoy, Leonardo A. & Giannotti, Mariana & Yoshizaki, Hugo T.Y. & Winkenbach, Matthias & Cunha, Claudio B., 2019. "Using GPS data to explore speed patterns and temporal fluctuations in urban logistics: The case of São Paulo, Brazil," Journal of Transport Geography, Elsevier, vol. 76(C), pages 114-129.
    16. Ying Hui & Mengtao Ding & Kun Zheng & Dong Lou, 2017. "Observing Trip Chain Characteristics of Round-Trip Carsharing Users in China: A Case Study Based on GPS Data in Hangzhou City," Sustainability, MDPI, vol. 9(6), pages 1-15, June.
    17. Nigro, Marialisa & Castiglione, Marisdea & Maria Colasanti, Fabio & De Vincentis, Rosita & Valenti, Gaetano & Liberto, Carlo & Comi, Antonio, 2022. "Exploiting floating car data to derive the shifting potential to electric micromobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 78-93.
    18. Egu, Oscar & Bonnel, Patrick, 2020. "How comparable are origin-destination matrices estimated from automatic fare collection, origin-destination surveys and household travel survey? An empirical investigation in Lyon," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 267-282.
    19. Mofeng Yang & Yixuan Pan & Aref Darzi & Sepehr Ghader & Chenfeng Xiong & Lei Zhang, 2022. "A data-driven travel mode share estimation framework based on mobile device location data," Transportation, Springer, vol. 49(5), pages 1339-1383, October.
    20. Andreas Dypvik Landmark & Petter Arnesen & Carl-Johan Södersten & Odd André Hjelkrem, 2021. "Mobile phone data in transportation research: methods for benchmarking against other data sources," Transportation, Springer, vol. 48(5), pages 2883-2905, October.

    More about this item

    Keywords

    Public 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:ags:ndtr16:319310. 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: AgEcon Search (email available below). General contact details of provider: http://www.trforum.org/journal/ .

    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.