This thesis reports on significant progress in three research areas. First, a major in-depth longitudinal data collection effort has been undertaken which has provided groundbreaking information on various elements of the activity scheduling process. The three year panel survey involved a variety of methodological techniques aimed at capturing different components of the activity scheduling process. Analysis of these new data has significantly improved our understanding of behavioural processes surrounding household activity scheduling. Second, a new rule-based technique for simulating activity schedules has been developed. Third, a tour-based mode choice model that incorporates crucial household interactions including vehicle allocation, ridesharing to joint activities and dropoff/pickup scenarios has been estimated and applied in a large-scale microsimulation framework. The latter two pieces of work have been developed into a modelling software package entitled the Travel Activity Scheduler for Household Agents (TASHA). It is felt that the TASHA modelling system that is more behaviourally valid than current state-of-practice models, provides more precise outputs with no additional input requirements, and has potential for the analysis of contemporary demand-oriented policies. With some additional research, testing and development, it is felt that this approach can evolve to become the "next generation" of travel demand modelling for major urban centres such as the Greater Toronto Area.