Author(s):
J.L. Buffington, D.L. Schafer, W.G. Adkins
Publication Date
September 1970
Abstract
The primary purpose of this research study was to develop and test procedures for making accurate estimates of the total load in terms of 18-km axle equivalents that a highway will experience from cargo vehicles over its design period. Such an endeavor involved an evaluation of vehicle weight and classification count data previously collected at existing loadometer and manual count stations located throughout the State of Texas. Two procedures were used to make estimates of the actual total 18-kip axle equivalents generated by cargo vehicles weighed at each of the 21 conventional static weight loadometer stations during 1967 and 1964-68. One procedure used multiple regression models in which "dummy" variables represent various characteristics of the vehicles weighed. The sets of variables entered into the models included vehicle type, body type, fuel type, time of weighing (night, day of week, summer and year) and load status. The other procedure used axle weight frequency distribution sets composed of one-kip (1000-pound) weight classes, 40 for single axles and 50 for tandem axles. The frequency sets developed were as follows: (1) Combined stations, (2) Combined stations by vehicle type, (3) Combined stations by fuel type, (4) Combined stations by load status, (5) Combined stations by highway system and vehicle type and, (6) Combined stations by highway system. Frequency Set 5 proved to be the most accurate. In fact, it was more accurate than the regression models.|Another purpose of this research study was to test the adequacy of previously collected vehicle weight and count samples at the various loadometer stations, These samples were tested for representativeness of the vehicle traffic and reliableness of statistics generated therefrom. To determine the above, the weighing and counting schedules and sample sizes were evaluated. Also, conventional loadometer station data were compared with limited weigh-in-motion station data. The weight and count sample size requirements were established through the use of a statistical formula which utilizes sample averages and variances with 10 percent error and 95 percent probability level criteria.|It was found that a considerable amount of station to station variation in the sample statistics was due to differences in the weighing or counting schedules and sample sizes, Combining stations and/or years made the data more representative and increased the reliability of the sample statistics.
Report Number:
131-2F
Link(s):
Document/Product
http://tti.tamu.edu/documents/131-2F.pdf
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