IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v41y2007i5p464-488.html

Synthesis of first practices and operational research approaches in activity-based travel demand modeling

Author

Listed:
  • Davidson, William
  • Donnelly, Robert
  • Vovsha, Peter
  • Freedman, Joel
  • Ruegg, Steve
  • Hicks, Jim
  • Castiglione, Joe
  • Picado, Rosella

Abstract

Regional travel models in the United States are clearly evolving from conventional models towards a new generation of more behaviorally realistic activity-based models. The new generation of regional travel demand models is characterized by three features: (1) an activity-based platform, that implies that modeled travel be derived within a general framework of the daily activities undertaken by households and persons, (2) a tour-based structure of travel where the tour is used as the basic unit of modeling travel instead of the elemental trip, and (3) micro-simulation modeling techniques that are applied at the fully-disaggregate level of persons and households, which convert activity and travel related choices from fractional-probability model outcomes into a series of discrete or "crisp" decisions. While the new generation of model has obvious conceptual advantages over the conventional four-step models, there are still numerous technical issues that have to be addressed as well as a better understanding of practical benefits should be achieved before the new generation of models can fully replace conventional models. The paper summarizes the recent successful experience in the development and application of activity-based demand models for Metropolitan Planning Organizations in the US. Moving activity-based approaches into practice is analyzed in a broad context of travel demand modeling market tendencies and policy implications.

Suggested Citation

  • Davidson, William & Donnelly, Robert & Vovsha, Peter & Freedman, Joel & Ruegg, Steve & Hicks, Jim & Castiglione, Joe & Picado, Rosella, 2007. "Synthesis of first practices and operational research approaches in activity-based travel demand modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 464-488, June.
    • Handle: RePEc:eee:transa:v:41:y:2007:i:5:p:464-488
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965-8564(06)00112-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    2. Mark Bradley & Peter Vovsha, 2005. "A model for joint choice of daily activity pattern types of household members," Transportation, Springer, vol. 32(5), pages 545-571, September.
    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. Franco, Patrizia & Johnston, Ryan & McCormick, Ecaterina, 2020. "Demand responsive transport: Generation of activity patterns from mobile phone network data to support the operation of new mobility services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 244-266.
    2. Siripirote, Treerapot & Sumalee, Agachai & Ho, H.W. & Lam, William H.K., 2015. "Statistical approach for activity-based model calibration based on plate scanning and traffic counts data," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 280-300.
    3. Naqavi, Fatemeh & Sundberg, Marcus & Västberg, Oskar Blom & Karlström, Anders & Hugosson, Muriel Beser, 2023. "Mobility constraints and accessibility to work: Application to Stockholm," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    4. Mohammad Hesam Hafezi & Lei Liu & Hugh Millward, 2019. "A time-use activity-pattern recognition model for activity-based travel demand modeling," Transportation, Springer, vol. 46(4), pages 1369-1394, August.
    5. Shasha Liu & Toshiyuki Yamamoto & Enjian Yao, 2023. "Joint modeling of mode choice and travel distance with intra-household interactions," Transportation, Springer, vol. 50(5), pages 1527-1552, October.
    6. Dong, Xiaojing & Ben-Akiva, Moshe E. & Bowman, John L. & Walker, Joan L., 2006. "Moving from trip-based to activity-based measures of accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(2), pages 163-180, February.
    7. Frank Primerano & Michael Taylor & Ladda Pitaksringkarn & Peter Tisato, 2008. "Defining and understanding trip chaining behaviour," Transportation, Springer, vol. 35(1), pages 55-72, January.
    8. Ermagun, Alireza & Levinson, David, 2016. "Intra-household bargaining for school trip accompaniment of children: A group decision approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 222-234.
    9. André de Palma & Nathalie Picard & Ignacio Inoa, 2014. "Discrete choice decision-making with multiple decision-makers within the household," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 16, pages 363-382, Edward Elgar Publishing.
    10. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    11. Moyano, Amparo & Martínez, Héctor S. & Coronado, José M., 2018. "From network to services: A comparative accessibility analysis of the Spanish high-speed rail system," Transport Policy, Elsevier, vol. 63(C), pages 51-60.
    12. Blom Västberg, Oskar & Karlström, Anders & Jonsson, Daniel & Sundberg, Marcus, 2016. "Including time in a travel demand model using dynamic discrete choice," MPRA Paper 75336, University Library of Munich, Germany, revised 11 Nov 2016.
    13. Zhao, Juanjuan & Ren, Huan & Gu, Yan & Pan, Haojie, 2023. "Relationships between the residential environment, travel attitude and behaviour among knowledge workers: The role of job types," Journal of Transport Geography, Elsevier, vol. 106(C).
    14. André de Palma & Nathalie Picard & Robin Lindsey, 2024. "Activity and transportation decisions within households," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 16, pages 426-451, Edward Elgar Publishing.
    15. Nathalie Picard & André de Palma & Ignacio Inoa, 2014. "Intra-household Decision Models of Residential and Job Location," Working Papers hal-00964351, HAL.
    16. Luo, Lichen & Parady, Giancarlos & Takami, Kiyoshi, 2024. "Evaluating the impact of automated vehicles on residential location distribution using activity-based accessibility: A case study of Japanese regional areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    17. Yan, Qianqian & Feng, Tao & Timmermans, Harry, 2023. "A model of household shared parking decisions incorporating equity-seeking household dynamics and leadership personality traits," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    18. Auld, Joshua & Mohammadian, Abolfazl (Kouros) & Doherty, Sean T., 2009. "Modeling activity conflict resolution strategies using scheduling process data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 386-400, May.
    19. Harsh Shah & Andre L. Carrel & Huyen T. K. Le, 2024. "Impacts of teleworking and online shopping on travel: a tour-based analysis," Transportation, Springer, vol. 51(1), pages 99-127, February.
    20. Joseph F. Wyer, 2018. "Urban Transportation Mode Choice And Trip Complexity: Bicyclists Stick To Their Gears," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1777-1787, July.

    More about this item

    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:transa:v:41:y:2007:i:5:p:464-488. 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/547/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.