Freight demand synthesis with mode choice-a combined estimation procedure

Kalahasthi, Lokesh Kumar
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Holguín-Veras, José
Mitchell, John E.
Wang, Xiaokun (Cara)
He, Xiaozhang
Reilly, Jack
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Transportation engineering
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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.
August 2018
School of Engineering
Dept. of Civil and Environmental Engineering
Rensselaer Polytechnic Institute, Troy, NY
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