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Modelling inter-activity duration to capture weekly activity-travel dynamics: instilling inherent dynamics within daily travel demand models

Author

Listed:
  • Wang, Kaili
  • Nurul Habib, Khandker

Abstract

Explicitly modelling the multi-day dynamics can result in an accurate and unbiased understanding of activity-travel choices. The study introduces a copula approach to jointly model individuals’ inter-activity duration and travel mode choices using week-long travel diaries. This study uses the simulated likelihood technique to address the inherent left-censoring issue in inter-activity duration modelling using week-long travel diaries. The joint model is empirically estimated using week-long travel diaries collected in the Greater Toronto and Hamilton Area (GTHA), Canada. Seven mandatory and discretionary activity types are examined. The empirical model reveals a statistically significant dependency between inter-activity duration and travel mode choices. This dependency indicates that the frequent scheduling of specific activity types is positively correlated with higher utility from travel mode choices, particularly for retail shopping and service activities. Conversely, work/study and errand/grocery shopping activities show lower correlations, suggesting that higher mode choice utility has a lesser impact on the time between these activities.

Suggested Citation

  • Wang, Kaili & Nurul Habib, Khandker, 2025. "Modelling inter-activity duration to capture weekly activity-travel dynamics: instilling inherent dynamics within daily travel demand models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 202(C).
    • Handle: RePEc:eee:transa:v:202:y:2025:i:c:s0965856425003635
    DOI: 10.1016/j.tra.2025.104730
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    References listed on IDEAS

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