This paper describes the family of aggregate models of freight movements which can be calibrated from traffic counts and other low cost data. Three model types were developed, a gravity (GR), an opportunity (OP) and a gravity-opportunity (GO) model. There are reasons for this variety as each may be more appropriate for particular conditions. It is relevant to point out that a suitable parameter for the deterrence function in the GR model may lead to a good approximation to a non-linear programming solution to the shipment problem. Three different methods were developed to calibrate these models from low cost data: a non-linear-least-squares (NLLS), a weighted-non-linear-least-squares (WNLLS) and a maximum-likelihood (ML1,ML2) methods. The models and these calibration methods have been implemented in a microcomputer package capable of dealing with up to ten commodities simultaneously. The approach has been tested using the 1982 Freight Movement Survey in Bali (Indonesia). The models were found to provide a reasonably good fit when dealing with five commodity types. General conclusions regarding the applicability of the approach to other environments and its potential for transport demand forecasting and planning are given at the end of the paper.
Abstract