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multi-state non-homogeneous semi-markov model of daily activity type, timing and duration sequence

Author

Listed:
  • Tai-Yu Ma

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Charles Raux

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Eric Cornelis

    (Groupe de recherche sur les transports - FUNDP - Facultés Universitaires Notre Dame de la Paix)

  • Iragaël Joly

    (GAEL - Laboratoire d'Economie Appliquée = Grenoble Applied Economics Laboratory - UPMF - Université Pierre Mendès France - Grenoble 2 - INRA - Institut National de la Recherche Agronomique)

Abstract

Understanding travelers' daily travel-activity pattern formation is an important issue for activity-based travel demand analysis. The activity pattern formation concerns not only complex interrelations between household members and individual's socio-demographic characteristics but also urban form and transport system settings. To investigate the effects of these attributes and the interrelationship between conducted activities, a multistate semi-Markov model is applied. The underlying assumption of the proposed model states that the state transition probability depends on its adjoining states. Based on the statistical tests of significance, it is affirmed that the duration of activity depends not only on its beginning time-of-day but also on the duration of travel/activity previously conducted. The empirical study based on Belgian Mobility survey is conducted to estimate individual's daily activity durations of different episodes and provides useful insight for the effects of socio-demographic characteristics, urban and transportation system settings on the activity pattern formation.

Suggested Citation

  • Tai-Yu Ma & Charles Raux & Eric Cornelis & Iragaël Joly, 2009. "multi-state non-homogeneous semi-markov model of daily activity type, timing and duration sequence," Post-Print halshs-00310900, HAL.
    • Handle: RePEc:hal:journl:halshs-00310900
    DOI: 10.3141/2134-15
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00310900v2
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    References listed on IDEAS

    as
    1. Bhat, Chandra R. & Srinivasan, Sivaramakrishnan & Axhausen, Kay W., 2005. "An analysis of multiple interepisode durations using a unifying multivariate hazard model," Transportation Research Part B: Methodological, Elsevier, vol. 39(9), pages 797-823, November.
    2. Bhat, Chandra R., 1996. "A hazard-based duration model of shopping activity with nonparametric baseline specification and nonparametric control for unobserved heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 189-207, June.
    3. Hemmens, George C., 1970. "Analysis and simulation of urban activity patterns," Socio-Economic Planning Sciences, Elsevier, vol. 4(1), pages 53-66, March.
    4. Lee, Backjin & Timmermans, Harry J.P., 2007. "A latent class accelerated hazard model of activity episode durations," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 426-447, May.
    5. Peter T.L. Popkowski Leszczyc & Harry Timmermans, 2002. "Unconditional and conditional competing risk models of activity duration and activity sequencing decisions: An empirical comparison," Journal of Geographical Systems, Springer, vol. 4(2), pages 157-170, June.
    6. Ram Pendyala & Chandra Bhat, 2004. "An Exploration of the Relationship between Timing and Duration of Maintenance Activities," Transportation, Springer, vol. 31(4), pages 429-456, November.
    7. Lee, Yuhwa & Hickman, Mark & Washington, Simon, 2007. "Household type and structure, time-use pattern, and trip-chaining behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1004-1020, December.
    8. D. Y. Lin & L. J. Wei & Z. Ying, 2002. "Model-Checking Techniques Based on Cumulative Residuals," Biometrics, The International Biometric Society, vol. 58(1), pages 1-12, March.
    9. Bhat, Chandra R., 1996. "A generalized multiple durations proportional hazard model with an application to activity behavior during the evening work-to-home commute," Transportation Research Part B: Methodological, Elsevier, vol. 30(6), pages 465-480, December.
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    Cited by:

    1. Tai-Yu Ma & Iragaël Joly & Charles Raux, 2010. "A shared frailty semi-parametric markov renewal model for travel and activity time-use pattern analysis," Working Papers hal-00477695, HAL.
    2. Raux, Charles & Ma, Tai-Yu & Joly, Iragaël & Kaufmann, Vincent & Cornelis, Eric & Ovtracht, Nicolas, 2011. "Travel and activity time allocation: An empirical comparison between eight cities in Europe," Transport Policy, Elsevier, vol. 18(2), pages 401-412, March.

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    Keywords

    travel-activity pattern; semi-Markov process; Cox regression model;
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