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Trend analysis of activity generation attributes over time

Author

Listed:
  • Farhana Yasmin

    (Polytechnique Montreal)

  • Catherine Morency

    (Polytechnique Montreal)

  • Matthew J. Roorda

    (University of Toronto)

Abstract

Activity generation models are relatively poorly developed in activity-based travel demand modelling frameworks. This research investigates whether observed distributions of activity attributes (activity frequency, start time and duration) used as inputs in the activity generation component of an activity-based travel demand model have changed over time. This research empirically examines changes in the distributions of activity generation attributes over time in the Greater Montreal area (GMA), Quebec, Canada. It also focuses on how these attributes vary with peoples’ socio-demographic characteristics. This research relies on the 1998, 2003 and 2008 origin–destination (O–D) household travel surveys of the GMA. The comparative analysis at three time points in a 10-year period clearly reveals that distributions of activity attributes are significantly changing over time. Work and school activities show similar trends; frequency “1” has increased and frequency “2+” has decreased over time. The occurrence of shopping activity on weekdays is decreasing over time. Start time and duration distributions for each activity have also changed significantly over time. The research allows preparing activity attributes for the application of an activity-based model, TASHA, such that they reflect temporal changes in travel behaviour of the GMA.

Suggested Citation

  • Farhana Yasmin & Catherine Morency & Matthew J. Roorda, 2017. "Trend analysis of activity generation attributes over time," Transportation, Springer, vol. 44(1), pages 69-89, January.
  • Handle: RePEc:kap:transp:v:44:y:2017:i:1:d:10.1007_s11116-015-9624-z
    DOI: 10.1007/s11116-015-9624-z
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    References listed on IDEAS

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    1. Arentze, Theo A. & Timmermans, Harry J. P., 2004. "A learning-based transportation oriented simulation system," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 613-633, August.
    2. Yasmin, Farhana & Morency, Catherine & Roorda, Matthew J., 2015. "Assessment of spatial transferability of an activity-based model, TASHA," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 200-213.
    3. Arentze, Theo A. & Timmermans, Harry J.P., 2009. "A need-based model of multi-day, multi-person activity generation," Transportation Research Part B: Methodological, Elsevier, vol. 43(2), pages 251-265, February.
    4. Bhat, Chandra R. & Koppelman, Frank S., 1993. "A conceptual framework of individual activity program generation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(6), pages 433-446, November.
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    Cited by:

    1. Gozde Ozonder & Eric J. Miller, 2021. "Longitudinal analysis of activity generation in the Greater Toronto and Hamilton Area," Transportation, Springer, vol. 48(3), pages 1149-1183, June.
    2. Kim, Seheon & Rasouli, Soora & Timmermans, Harry & Yang, Dujuan, 2018. "Estimating panel effects in probabilistic representations of dynamic decision trees using bayesian generalized linear mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 168-184.
    3. Wang, Kaili & Liu, Yicong & Mashrur, Sk Md & Loa, Patrick & Habib, Khandker Nurul, 2021. "COVid-19 influenced households’ Interrupted Travel Schedules (COVHITS) survey: Lessons from the fall 2020 cycle," Transport Policy, Elsevier, vol. 112(C), pages 43-62.
    4. Pani, Agnivesh & Sahu, Prasanta K. & Tavasszy, Lóránt & Mishra, Sabya, 2023. "Freight activity-travel pattern generation (FAPG) as an enhancement of freight (trip) generation modelling: Methodology and case study," Transport Policy, Elsevier, vol. 144(C), pages 34-48.

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