Freight demand synthesis with mode choice-a combined estimation procedure

Abstract

This dissertation contributes to the field of Freight Demand Synthesis (FDS) through the development of a mathematical formulation that jointly estimates the models of distribution, modal split, and empty trips; that maximizes the level of agreement between the estimated and observed traffic. The main intent of the formulation is to reduce the need for expensive and time-consuming data collection efforts, by using the secondary data that are easier to assemble, and to calibrate the models. The input data used by the formulation include traffic counts, link costs, distances, travel times, payloads, and freight productions, and attractions.

The scope of the research is limited to intercity or regional freight that are transported by two mutually exclusive and collectively exhaustive modes, truck and rail. The freight flows associated with, imports, exports are not included. The trip distribution flows are assumed to follow a doubly constrained gravity model with negative exponential impedance function; a binary logit model with utility depending only on the impedance is assumed for mode choice; and Noortman and van Es’ empty trip models for both truck and rail. An optimization model that minimizes the sum of squared errors between the observed and estimated link flows provides the basis of model calibration. The calibration process entails the computation of four parameters (gravity, mode choice, truck empty trip, and rail empty trip models). The optimization algorithms involved both convex and nonconvex methods, because the objective function is nonconvex with respect to the mode choice parameter. Two methods, Ordinary Least Squared (OLS) inference and an interior point method with a set of random starting points (multi-start algorithm), were tested to overcome the non-convexity of the problem. The results indicate that the multi-start algorithm provided closer estimates to the global optimal mode choice parameter compared to OLS inference. The potential of the methodology developed in regional freight transportation planning is demonstrated using a test case based on a national level freight transportation planning scenario in Bangladesh. The challenges involved with the estimation and validation of model parameters are also discussed. The approach to FDS in this research provides the freight transportation planners and policy makers a faster and cheaper way to assess the outcomes with considerable accuracy.