  Travel demand management measures/policies are important to sustain positive
changes among individuals' travel behaviour. An integrated agent-based
microsimulation platform provides a rich framework for examining such
interventions to assess their impacts using indicators about demand as well as
supply side. This paper presents an approach, where individual schedules,
derived from a lighter version of an activity-based model, are fed into a
MATSIM simulation framework. Simulations are performed for two European cities
i.e. Hasselt (Belgium), Bologna (Italy). After calibrating the modelling
framework against aggregate traffic counts for the base case, the impacts of a
few traffic management policies (restricting car access, increase in bus
frequency) are examined. The results indicate that restricting car access is
more effective in terms of reducing traffic from the network and also shifting
car drivers/passengers to other modes of travel. The enhancement of bus
infrastructure in relation to increase in frequency caused shifting of
bicyclist towards public transport, which is an undesirable result of the
policy if the objective is to improve sustainability and environment. In future
research, the framework will be enhanced to integrate emission and air
dispersion models to ascertain effects on air quality as a result of such
interventions.
