Maximum likelihood estimation for a road traffic network model

The use of the maximum likelihood method for parameter estimation in a probabilistic path choice model used for road traffic networks is described. The method requires observation of mean travel costs in a given network rather than the traffic flows throughout the network, and thus data collection efforts may be reduced. A test network, for which many sets of artificial data were generated, is examined so that the usefulness of the parameter estimation procedure may be assessed. It is shown that the procedure is both convenient and quick, and that accurate estimates of model parameters may be obtained.