Truck weight prediction modeling

Typescript (photocopy).A reasonable forecast of anticipated traffic loading's is necessary to design or rehabilitate a highway. Underestimating the load experience for a highway could result in an under designed facility, leading to the need for major unanticipated repairs. An overestimate, however, could result in the construction of over designed facilities that ties up monies badly needed for other projects. The result of this study can be helpful in providing a better understanding of prediction of truck loads and their trends for future decision making processes. This dissertation considers the single axles, tandem axles, and gross weight distributions of seven truck types at three weigh-in-motion (WIM) stations in Texas between 1977 and 1985. It also provides evaluation of the trend in average weights over this nine year period. In addition, predictability of future truck weight distributions based on the past collected data are examined. The results cast doubt on the concept of statistically sampling truck weights at a site and projecting future trends in the axle load distribution at a particular site. The results suggest that predicting axle loads at another site base and sampling of data on roadways of similar classification may not be possible with any degree of statistical reliability