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Full-Text Articles in Engineering
Weigh-In-Motion Auto-Calibration Using Automatic Vehicle Identification, Fu Ren Zhang Zhang Durandal
Weigh-In-Motion Auto-Calibration Using Automatic Vehicle Identification, Fu Ren Zhang Zhang Durandal
Graduate Theses and Dissertations
Weigh-in-Motion (WIM) sensors are installed on mainline lanes at highway locations to record vehicle weights, axle spacing, vehicle class, travel speed, vehicle length, and traffic volume. These data elements support effective transportation planning, infrastructure design, and policy development. Therefore, it is important that WIM sensors supply accurate data. After initial installation and calibration, WIM systems may experience measurement drifts in weight and axle detection. Recalibration takes two general forms: (a) On-site calibration involving running trucks of known weight over WIM scales and (b) Auto-calibration methods involving comparisons to assumed reference weights. Auto-calibration can be more cost and time effective than …
Auto-Calibration Of Wim Using Traffic Stream Characteristics, Johnson Baker
Auto-Calibration Of Wim Using Traffic Stream Characteristics, Johnson Baker
Graduate Theses and Dissertations
This project evaluates the performance of Weigh-in-Motion (WIM) auto-calibration methods used by the Arkansas Department of Transportation (ARDOT). Typical auto-calibration algorithms compare the WIM measured weights of vehicles from the traffic stream to reference values, using five-axle tractor-trailer configured trucks for comparisons, e.g. Federal Highway Administration (FHWA) Class 9. Parameters of the existing algorithms including the Front Axle Weight (FAW) reference value, the sampling frequency required to update the calibration factor, and thresholds for Gross Vehicle Weight (GVW) bins were evaluated. The primary metric used to estimate algorithm performance was Mean Absolute Percent Error (MAPE) between the WIM and static …