  The study focuses on estimating and predicting time-varying origin to
destination (OD) trip tables for a dynamic traffic assignment (DTA) model. A
bi-level optimisation problem is formulated and solved to estimate OD flows
from pre-existent demand matrix and historical traffic flow counts. The
estimated demand is then considered as an input for a time series OD demand
prediction model to support the DTA model for short-term traffic condition
forecasting. Results show a high capability of the proposed OD demand
estimation method to reduce the DTA model error through an iterative solution
algorithm. Moreover, the applicability of the OD demand prediction approach is
investigated for an incident analysis application for a major corridor in
Sydney, Australia.
