This joint research program aims to develop a dynamic activity-travel assignment platform for advanced travel demand management and information system. To that effect, we combine two major fields in transportation research/operations research, i.e. activity-based modelling and dynamic traffic assignment. To accommodate the diverse choice dimensions involved in daily activity-travel patterns, the action spaces of individuals will be represented and modelled in a structural multi-state supernetwork by integrating activity programs with networks of multi-modal transport, locations of facilities\services and ICT. A derived feature is that any path through the supernetwork represents a feasible activity-travel pattern at the highest level of details. By considering the start and end points of multi-state supernetworks as virtual O-D pairs, the activity-travel assignment model will be formulated as a variational inequality problem. Thereafter, algorithms will be developed for a synthesized population to seek a state of user optimization that for each O-D pair the used path/pattern has the minimum activity-travel cost. This process will be evaluated for different scenarios concerning transport and spatial planning policies with the purpose of improving mobility efficiency and reducing the use of fuel-based private vehicles.