Estimating Time-Dependent Origin-Destination Demand in a Large-Scale Congested Network Using Multi-Source Traffic Data

2018-12-13T03:23:42Z (GMT) by MOHAMMAD SAJJAD SHAFIEI
Traffic simulation models are capable of replicating traffic network conditions and providing accurate forecasts. These models involve a number of parameters that need to be calibrated based on the available archived traffic data. Time-Dependent Origin-Destination (TDOD) demand is a crucial input for traffic simulations. The reliability of the traffic simulations is highly dependent on the accuracy of the TDOD demand. Since the demand data cannot be observed directly, a common approach to obtain TDOD demand is to use a priori demand matrix and traffic count data in some parts of the network. The broad aim of this research is to develop a TDOD estimation model using multi-source traffic data applied to a large-scale congested urban network (Melbourne).