The primary objective of this research study was to modify the existing EAL estimation system to include data obtained using the Golden River Weigh-In-Motion system and automated vehicle classification equipment. Data are to be collected over a three-year cycle in accordance with the FHWA Traffic Monitoring Guide. Having the capability of moving the portable weigh-in-motion scales to locations other than interstate sites permits the collection and analyses of specific data at sites on other highway functional classifications. Such data permits estimating both accumulated and future EAL requirements for that site. Such data permits estimating EAL requirements for sites on the same highway functional classification for which AADT is the only available data.
An algorithm was developed to identify heavy/coal trucks weighed by W\M. The algorithm involves a minimum weight for straight-frame trucks and for semi-trailer coal trucks has the additional parameter of gross weight divided by the spacing between the last axle on the tractor and the first axle on the trailer. The algorithm works because the coal semi-trailer is shorter than a normal semi-trailer.
Historical data files have been sorted by highway functional classification to permit calculating EAL requirements on a three-year cycle corresponding to the requirements of the FHWA Traffic Monitoring Guide. The revised computer programs use the same data format contained in historical files. The basic equation for estimating EALs contains the following seven parameters as independent variables; 1) annual average daily traffic volume, 2) average fraction of trucks in the traffic stream, 3) average fraction of coal trucks in the total truck population, 4) average number of axles per coal truck, 5) average number of axles per non-coal truck, 6) average number of equivalent axleloads per coal-truck axle, and 7) average number of equivalent axleloads per non-coal-truck axle.
Digital Object Identifier
Southgate, Herbert F., "Estimation of Equivalent Axleloads Using Data Collected by Automated Vehicle Classification and Weigh-in-Motion Equipment" (1990). Kentucky Transportation Center Research Report. 485.