Generating Realistic Individual Activity Schedules via Activity Location Allocation Based on Simulated Travel Times

2026-06-23

AI Summary

Existing approaches struggle to generate individual daily activity schedules that are both realistic and temporally consistent with reported travel survey data. This work proposes an iterative optimization framework that integrates dynamic programming, travel time simulation, and activity location assignment algorithms to progressively refine synthetic activity schedules while preserving privacy. By iteratively adjusting activity timing and sequencing, the method aligns simulated travel times with empirical distributions derived from travel surveys. Experimental results demonstrate that the proposed approach reduces the discrepancy between simulated and observed travel times by 52.2% compared to initial schedules, substantially improving both temporal consistency and behavioral realism in the generated activity plans.

Abstract

Individual level daily activity schedules are essential for a wide range of applications, including infectious disease control, urban transportation planning, and policy design. In practice, such schedules are typically generated by combining population data with travel survey data. These data sources are used because they are often publicly available, whereas observed individual activity schedules are difficult to obtain due to privacy concerns. However, because of the complexity of mobility modelling, it is difficult to generate realistic activity schedules that also preserve travel times consistent with those reported in travel surveys. To address this issue, we propose a framework for generating activity schedules that iteratively applies a dynamic programming method to allocate activity locations based on simulated travel times. Numerical experiments with dummy data show that the proposed method reduces the discrepancy between simulated travel times and those reported in travel surveys by 52.2% relative to the first iteration through iterative refinement.

Problem

• activity schedule generation
• travel time consistency
• individual mobility
• location allocation
• realistic simulation

Innovation

• activity schedule generation
• dynamic programming
• travel time simulation
• location allocation
• iterative refinement