IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v54y2020i1p21-41.html
   My bibliography  Save this article

A Dynamic Discrete Choice Activity-Based Travel Demand Model

Author

Listed:
  • Oskar Blom Västberg

    (Division of Systems Analysis and Economics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden;)

  • Anders Karlström

    (Division of Systems Analysis and Economics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden;)

  • Daniel Jonsson

    (Division of Systems Analysis and Economics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden;)

  • Marcus Sundberg

    (Division of Systems Analysis and Economics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden)

Abstract

This paper presents a dynamic discrete choice model (DDCM) for daily activity–travel planning. A daily activity–travel pattern is constructed from a sequence of decisions of when, where, why, and how to travel. Individuals’ preferences for activity–travel patterns are described by the sum of the utility of all travel and activity episodes in that pattern, but components of the utility functions, such as travel times, may be stochastic. In each decision stage, individuals act as if they maximized the expected utility of the remainder of the day. The DDCM-model presented allows for a detailed treatment of timing decision consistent with other choice dimensions, respects time–space constraints, and enables the inclusion of explicitly modeled uncertainties in, for example, travel time. In a case study, a model for daily planning of activity and travel on workdays is estimated whereby individuals can perform any number of trips that each is a combination of one of 1,240 locations, four modes, and six activities. Simulation results indicate that the model within sample accurately replicates timing decisions, trip lengths, and the distributions of the number of trips, tours, and trips per tour.

Suggested Citation

  • Oskar Blom Västberg & Anders Karlström & Daniel Jonsson & Marcus Sundberg, 2020. "A Dynamic Discrete Choice Activity-Based Travel Demand Model," Transportation Science, INFORMS, vol. 54(1), pages 21-41, January.
    • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:1:p:21-41
    DOI: 10.1287/trsc.2019.0898
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/trsc.2019.0898
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.2019.0898?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. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    3. Fosgerau, Mogens & Karlström, Anders, 2010. "The value of reliability," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 38-49, January.
    4. Mai, Tien & Fosgerau, Mogens & Frejinger, Emma, 2015. "A nested recursive logit model for route choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 100-112.
    5. Adler, Thomas & Ben-Akiva, Moshe, 1979. "A theoretical and empirical model of trip chaining behavior," Transportation Research Part B: Methodological, Elsevier, vol. 13(3), pages 243-257, September.
    6. Recker, W. W., 2001. "A bridge between travel demand modeling and activity-based travel analysis," Transportation Research Part B: Methodological, Elsevier, vol. 35(5), pages 481-506, June.
    7. Aura Reggiani & Peter Nijkamp (ed.), 2009. "Complexity and Spatial Networks," Advances in Spatial Science, Springer, number 978-3-642-01554-0, February.
    8. John Rust, 1997. "Using Randomization to Break the Curse of Dimensionality," Econometrica, Econometric Society, vol. 65(3), pages 487-516, May.
    9. Yusak Susilo & Kay Axhausen, 2014. "Repetitions in individual daily activity–travel–location patterns: a study using the Herfindahl–Hirschman Index," Transportation, Springer, vol. 41(5), pages 995-1011, September.
    10. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
    11. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    12. Khandker Habib, 2011. "A random utility maximization (RUM) based dynamic activity scheduling model: Application in weekend activity scheduling," Transportation, Springer, vol. 38(1), pages 123-151, January.
    13. 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.
    14. Recker, Will W & Duan, J. & Wang, H., 2008. "Development of an estimation procedure for an activity-based travel demand model," University of California Transportation Center, Working Papers qt0rz778v6, University of California Transportation Center.
    15. Allahviranloo, Mahdieh & Recker, Will, 2013. "Daily activity pattern recognition by using support vector machines with multiple classes," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 16-43.
    16. Mai, Tien, 2016. "A method of integrating correlation structures for a generalized recursive route choice model," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 146-161.
    17. Jenelius, Erik & Mattsson, Lars-Göran & Levinson, David, 2011. "Traveler delay costs and value of time with trip chains, flexible activity scheduling and information," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 789-807, June.
    18. Dominik Grether & Yu Chen & Marcel Rieser & Kai Nagel, 2009. "Effects of a Simple Mode Choice Model in a Large-Scale Agent-Based Transport Simulation," Advances in Spatial Science, in: Aura Reggiani & Peter Nijkamp (ed.), Complexity and Spatial Networks, chapter 0, pages 167-186, Springer.
    19. 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.
    20. Chang-Hyeon Joh & Theo A Arentze & Harry J P Timmermans, 2005. "A Utility-Based Analysis of Activity Time Allocation Decisions Underlying Segmented Daily Activity–Travel Patterns," Environment and Planning A, , vol. 37(1), pages 105-125, January.
    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. Kai Shen & Jan-Dirk Schmöcker & Wenzhe Sun & Ali Gul Qureshi, 2023. "Calibration of sightseeing tour choices considering multiple decision criteria with diminishing reward," Transportation, Springer, vol. 50(5), pages 1897-1921, October.
    2. 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).
    3. Ren, Xiyuan & Chow, Joseph Y.J., 2022. "A random-utility-consistent machine learning method to estimate agents’ joint activity scheduling choice from a ubiquitous data set," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 396-418.
    4. Song, Yuchen & Li, Dawei & Liu, Dongjie & Cao, Qi & Chen, Junlan & Ren, Gang & Tang, Xiaoyong, 2022. "Modeling activity-travel behavior under a dynamic discrete choice framework with unobserved heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    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.

    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. 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.
    2. Mai, Tien & Yu, Xinlian & Gao, Song & Frejinger, Emma, 2021. "Routing policy choice prediction in a stochastic network: Recursive model and solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 151(C), pages 42-58.
    3. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.
    4. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
    5. Evanthia Kazagli & Michel Bierlaire & Matthieu de Lapparent, 2020. "Operational route choice methodologies for practical applications," Transportation, Springer, vol. 47(1), pages 43-74, February.
    6. Tien Mai & Fabian Bastin & Emma Frejinger, 2018. "A decomposition method for estimating recursive logit based route choice models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 253-275, September.
    7. Oyama, Yuki & Hato, Eiji, 2019. "Prism-based path set restriction for solving Markovian traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 528-546.
    8. Badiola, Nicolás & Raveau, Sebastián & Galilea, Patricia, 2019. "Modelling preferences towards activities and their effect on departure time choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 39-51.
    9. Yuki Oyama, 2022. "Capturing positive network attributes during the estimation of recursive logit models: A prism-based approach," Papers 2204.01215, arXiv.org, revised Jan 2023.
    10. Jenelius, Erik, 2012. "The value of travel time variability with trip chains, flexible scheduling and correlated travel times," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 762-780.
    11. Mai, Tien & Bui, The Viet & Nguyen, Quoc Phong & Le, Tho V., 2023. "Estimation of recursive route choice models with incomplete trip observations," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 313-331.
    12. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens & Bastin, Fabian, 2017. "A dynamic programming approach for quickly estimating large network-based MEV models," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 179-197.
    13. Daniel Jonsson & Anders Karlström & Masoud Fadaei Oshyani & Per Olsson, 2014. "Reconciling User Benefit and Time-Geography-Based Individual Accessibility Measures," Environment and Planning B, , vol. 41(6), pages 1031-1043, December.
    14. Oyama, Yuki & Hara, Yusuke & Akamatsu, Takashi, 2022. "Markovian traffic equilibrium assignment based on network generalized extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 135-159.
    15. Song, Yuchen & Li, Dawei & Liu, Dongjie & Cao, Qi & Chen, Junlan & Ren, Gang & Tang, Xiaoyong, 2022. "Modeling activity-travel behavior under a dynamic discrete choice framework with unobserved heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    16. Pougala, Janody & Hillel, Tim & Bierlaire, Michel, 2022. "Capturing trade-offs between daily scheduling choices," Journal of choice modelling, Elsevier, vol. 43(C).
    17. 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).
    18. Börjesson, Maria & Eliasson, Jonas & Franklin, Joel, 2012. "Valuations of travel time variability in scheduling versus mean-variance models," Working papers in Transport Economics 2012:2, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    19. 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.
    20. Tien Mai & The Viet Bui & Quoc Phong Nguyen & Tho V. Le, 2022. "Estimation of Recursive Route Choice Models with Incomplete Trip Observations," Papers 2204.12992, arXiv.org.

    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:inm:ortrsc:v:54:y:2020:i:1:p:21-41. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.