Abstract
Freight transportation is an important research topic in the transportation domain of high-income countries, but middle-income and low-income countries lack quality research on this, especially for heterogeneous roadway freight movement on narrower rural roads. This study addresses this issue in northern Bangladesh, analyzing the volume of five dedicated freight vehicle types across 1,162 roadway segments. A negative binomial generalized linear model (NB-GLM), along with a supporting negative binomial generalized additive model (NB-GAM), was found suitable to better explain the interrelation between freight volume and different predictors like area, population, household size, solvency rate, crest width, embankment height, and international roughness index. Freight movement was notably higher on market days. The NB-GLM highlighted significant linear effects of socioeconomic attributes, whereas the NB-GAM revealed strong nonlinear influences of roadway and spatial characteristics. Distinct variations were observed for predictor significance in statistical terms across different vehicle classes. These findings serve as a decision-support tool for policy makers wanting to implement targeted interventions, including temporal zoning, last-mile surface funds, and village freight consolidation hubs. The results provide a robust framework for predicting freight movements in regions with similar economic conditions, aiding in sustainable road network development and maintenance planning.
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