<p>Activity-based modeling (ABM) is widely recognized as the preferred approach in travel demand modeling, but it still exhibits certain limitations, particularly in its neglect of day-to-day dynamics over a week by solely focusing on modelling a single “typical” day. An important challenge of developing a week-long ABM is data collection. To face this challenge, this study centres on the design and execution of the Toronto Household Activity Travel Survey (THATS) to acquire comprehensive week-long activity-travel diary data for a maximum number of household members. The primary objective is to minimize participant burden through passive recording of data while maintaining flexibility in data collection based on the survey’s specific objectives. This is achieved through a combination of a smartphone GPS tracking application and a web-based survey platform embedded in the app. Initial results demonstrate an acceptable participation rate with representative high-quality data meeting the primary objectives of the study, though the collection of full household data remains a complex undertaking. Additionally, the recorded number and duration of trips and daily activities underscores the significance of innovative data collection methods and the extension of modeling time units to encompass a full week.</p>