IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v41y2014i4p673-695.html
   My bibliography  Save this article

Travel demand forecasts improved by using cross-sectional data from multiple time points

Author

Listed:
  • Nobuhiro Sanko

Abstract

Forecasts of travel demand are often based on data from the most recent time point, even when cross-sectional data is available from multiple time points. This is because forecasting models with similar contexts have higher transferability, and the context of the most recent time point is believed to be the most similar to the context of a future time point. In this paper, the author proposes a method for improving the forecasting performance of disaggregate travel demand models by utilising not only the most recent dataset but also an older dataset. The author assumes that the parameters are functions of time, which means that future parameter values can be forecast. These forecast parameters are then used for travel demand forecasting. This paper describes a case study of journeys to work mode choice analysis in Nagoya, Japan, using data collected in 1971, 1981, 1991, and 2001. Behaviours in 2001 are forecast using a model with only the most recent 1991 dataset and models that combine the 1971, 1981, and 1991 datasets. The models proposed by the author using data from three time points can provide better forecasts. This paper also discusses the functional forms for expressing parameter changes and questions the temporal transferability of not only alternative-specific constants but also level-of-service and socio-economic parameters. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Nobuhiro Sanko, 2014. "Travel demand forecasts improved by using cross-sectional data from multiple time points," Transportation, Springer, vol. 41(4), pages 673-695, July.
  • Handle: RePEc:kap:transp:v:41:y:2014:i:4:p:673-695
    DOI: 10.1007/s11116-013-9464-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11116-013-9464-7
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-013-9464-7?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. L A Silman, 1981. "The Time Stability of a Modal-Split Model for Tel-Aviv," Environment and Planning A, , vol. 13(6), pages 751-762, June.
    2. Nobuhiro Sanko & Takayuki Morikawa, 2010. "Temporal transferability of updated alternative-specific constants in disaggregate mode choice models," Transportation, Springer, vol. 37(2), pages 203-219, March.
    3. Abrantes, Pedro A.L. & Wardman, Mark R., 2011. "Meta-analysis of UK values of travel time: An update," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 1-17, January.
    4. McCarthy, Patrick S., 1982. "Further evidence on the temporal stability of disaggregate travel demand models," Transportation Research Part B: Methodological, Elsevier, vol. 16(4), pages 263-278, August.
    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. Nobuhiro Sanko, 2018. "Travel demand forecasts improved by using cross-sectional data from multiple time points: enhancing their quality by linkage to gross domestic product," Transportation, Springer, vol. 45(3), pages 905-918, May.
    2. Vij, Akshay & Gorripaty, Sreeta & Walker, Joan L., 2017. "From trend spotting to trend ’splaining: Understanding modal preference shifts in the San Francisco Bay Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 238-258.
    3. Sabreena Anowar & Naveen Eluru & Luis F. Miranda-Moreno, 2018. "How household transportation expenditures have evolved in Canada: a long term perspective," Transportation, Springer, vol. 45(5), pages 1297-1317, September.
    4. Chenfeng Xiong & Di Yang & Jiaqi Ma & Xiqun Chen & Lei Zhang, 2020. "Measuring and enhancing the transferability of hidden Markov models for dynamic travel behavioral analysis," Transportation, Springer, vol. 47(2), pages 585-605, April.
    5. Zannat, Khatun E. & Laudan, Janek & Choudhury, Charisma F. & Hess, Stephane, 2024. "Developing an agent-based microsimulation for predicting the Bus Rapid Transit (BRT) demand in developing countries: A case study of Dhaka, Bangladesh," Transport Policy, Elsevier, vol. 148(C), pages 92-106.
    6. Maruyama, Takuya & Fukahori, Tatsuya, 2020. "Households with every member out-of-home (HEMO): Comparison using the 1984, 1997, and 2012 household travel surveys in Kumamoto, Japan," Journal of Transport Geography, Elsevier, vol. 82(C).
    7. Rezaei, Ali & Patterson, Zachary, 2018. "Preference stability in household location choice: Using cross-sectional data from three censuses," Research in Transportation Economics, Elsevier, vol. 67(C), pages 44-53.

    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. Vij, Akshay & Gorripaty, Sreeta & Walker, Joan L., 2017. "From trend spotting to trend ’splaining: Understanding modal preference shifts in the San Francisco Bay Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 238-258.
    2. Maria Börjesson, 2014. "Inter-temporal variation in the travel time and travel cost parameters of transport models," Transportation, Springer, vol. 41(2), pages 377-396, March.
    3. Fox, James & Daly, Andrew & Hess, Stephane & Miller, Eric, 2014. "Temporal transferability of models of mode-destination choice for the Greater Toronto and Hamilton Area," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(2), pages 41-62.
    4. Habib, Khandker M. Nurul & Swait, Joffre & Salem, Sarah, 2014. "Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 110-126.
    5. Bouscasse, Hélène & de Lapparent, Matthieu, 2019. "Perceived comfort and values of travel time savings in the Rhône-Alpes Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 370-387.
    6. Hirte, Georg & Tscharaktschiew, Stefan, 2018. "The impact of anti-congestion policies and the role of labor-supply margins," CEPIE Working Papers 04/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    7. Mahieu, Pierre-Alexandre & Andersson, Henrik & Beaumais, Olivier & Crastes dit Sourd, Romain & Hess, François-Charles & Wolff, François-Charles, 2017. "Stated preferences: a unique database composed of 1657 recent published articles in journals related to agriculture, environment, or health," Review of Agricultural, Food and Environmental Studies, Institut National de la Recherche Agronomique (INRA), vol. 98(3), November.
    8. Kolarova, Viktoriya & Steck, Felix & Bahamonde-Birke, Francisco J., 2019. "Assessing the effect of autonomous driving on value of travel time savings: A comparison between current and future preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 155-169.
    9. Allard, Ryan F. & Moura, Filipe, 2018. "Effect of transport transfer quality on intercity passenger mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 89-107.
    10. Clifton, Geoffrey T. & Mulley, Corinne, 2016. "A historical overview of enhanced bus services in Australian cities: What has been tried, what has worked?," Research in Transportation Economics, Elsevier, vol. 59(C), pages 11-25.
    11. Maria Börjesson & Jonas Eliasson, 2019. "Should values of time be differentiated?," Transport Reviews, Taylor & Francis Journals, vol. 39(3), pages 357-375, May.
    12. Manout, Ouassim & Bonnel, Patrick & Bouzouina, Louafi, 2018. "Transit accessibility: A new definition of transit connectors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 88-100.
    13. Rich, Jeppe & Vandet, Christian Anker, 2019. "Is the value of travel time savings increasing? Analysis throughout a financial crisis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 145-168.
    14. Carrion, Carlos & Levinson, David, 2012. "Value of travel time reliability: A review of current evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 720-741.
    15. Anas, Alex & Chang, Huibin, 2023. "Productivity benefits of urban transportation megaprojects: A general equilibrium analysis of «Grand Paris Express»," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    16. Morrison, Geoffrey M. & Lin Lawell, C.-Y. Cynthia, 2016. "Does employment growth increase travel time to work?: An empirical analysis using military troop movements," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 180-197.
    17. Dickerson, Andy & Hole, Arne Risa & Munford, Luke A., 2014. "The relationship between well-being and commuting revisited: Does the choice of methodology matter?," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 321-329.
    18. Rotaris, Lucia & Danielis, Romeo, 2014. "The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste, Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 127-140.
    19. Franco Chingcuanco & Eric Miller, 2014. "A meta-model of vehicle ownership choice parameters," Transportation, Springer, vol. 41(5), pages 923-945, September.
    20. Filipi Nikol & Karlínová Bára & Krčál Ondřej, 2022. "The disutility of driving below the speed limit on highways," Review of Economic Perspectives, Sciendo, vol. 22(4), pages 267-277, December.

    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:kap:transp:v:41:y:2014:i:4:p:673-695. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.