Highway construction and maintenance relies heavily upon mined aggregates as a core ingredient. The proximity of aggregate mine sites to highway or other construction locations is an important issue since the total project costs are highly affected by transportation cost/efficiency and also deterioration of the existing highway infrastructure as influenced by frequent, heavy shipments traveling long distances. Likewise, the transportation costs for hauling mined aggregates are minimized when shipments are loaded to capacity payload weights. This is the first attempt in a series of forthcoming studies to explore mineral shipment characteristics with a spatial regression model. A comprehensive survey was conducted to determine both the location and type of need for road improvements. This study investigates the spatial relationships between construction aggregate shipments and the hauling trucks’ payload weights as it pertains to highway deterioration in the State of Washington. Many studies have examined the relationship between transportation cost and construction unit productivity but there’s minimal information available pertaining to the relationship between payload weights, shipment distances and highway deterioration. To identify impacted highway segments resulting from aggregates shipments, mine locations and shipment distances in cooperation with payload weights are examined. Naturally, spatial nonstationarity of the data is possible whenever any process takes place over many different geographical locations. As such, it’s appropriate and necessary to test the mining industry data for spatial dependences. As a result, the paper employs a spatial error regression model with distance based weights matrix to address spatial autocorrelation, to capture the interaction between spatial units and to predict the incremental change in payload weights resulting from increasing hauling distance. Results show a highly significant positive relationship between payload weights and increasing shipment distances.