The Activity-based model ABIT: Modeling 24 hours, 7 days a week

Abstract

The paper introduces the activity-based model ABIT as a novel approach to modeling travel demand. Traditional aggregate transport models are limited in their ability to assess certain transport policies, such as ride-pooling services and autonomous cars, due to their inability to accurately represent complex travel behaviors. ABIT generates weekly activity patterns for individuals, forming the basis for understanding habitual and incremental travel behavior. Unlike traditional models, ABIT can distinguish between day-to-day variations in travel behavior and more significant year-to-year changes. The model's base-year structure is described in detail, including steps for assigning habitual modes, mandatory activities, discretionary activities, subtours, duration, start times, destination choices, and vehicle allocation. The paper emphasizes the importance of habitual mode choice, especially in modeling commute modes. The results of ABIT show variations in activity frequency across different days of the week, with weekdays dominated by work and education activities, while weekends exhibit a higher proportion of discretionary activities. The paper acknowledges longer runtimes and random variations as potential limitations, suggesting caution in analyzing results at a fine- grained level.