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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
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    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.
    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.
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    5. 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.

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