Activity-based models are a specific type of agent-based models widely used in transport and urban planning to generate and study travel demand. They deal with agents that structure their behaviour in terms of daily activity schedules: sequences of activity instances (such as work, sleep or shopping) with assigned start times, durations and locations, and interconnected by trips with assigned transport modes and routes. Despite growing importance of activity-based models in transport modelling, there has been no work focus- ing specifically on statistical validation of such models so far. In this paper, we propose a six-step Validation FrameworkforActivity-basedModels(VALFRAM)thatexploitshistoricalreal-worlddatatoquantifythemodel's validityintermsofasetofnumericmetrics. Theframeworkcomparesthetemporalandspatialpropertiesand the structure of modelled activity schedules against real-world origin-destination matrices and travel diaries. We demonstrate the usefulness of the framework on a set of six dierent activity-based transport models.
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