The evaluation and application of a fully disaggregate method for trip matrix estimation with platoon dispersion

This paper addresses the problem of estimating an Origin-Destination (O-D) matrix with platoon dispersion from fully disaggregate data: that is, the passage times of vehicles at the entries and exits or the origins and destinations of a network. Given a list of entry times and a list of exiting times, a fully disaggregate method or a matching method tries to match each pair of entry-exiting times such that the resultant journey times for each O-D pair fit the given distributions best. Bell et al., 1991 formulated the problem of finding the most likely set of matches as a 0-1 assignment problem. In this paper, two estimators will be considered: maximum likelihood estimator and the matching-Furness technique. It will be shown that the maximum likelihood estimation can be formulated more generally as a transportation problem. The matching-Furness method is investigated by use of simulated traffic data and is applied to a set of real data collected on the Brescia-Padova motorway network in Italy. The matching-Furness method gives consistently better estimates than the least squares estimator (Cremer and Keller, 1987) and the linked static-dynamic correlation model (Keller and Ploss, 1987). The method is therefore suitable for off-line estimations for general networks.