Guidelines for Effective Weigh-in-Motion (WIM) Equipment Calibration, Application for Modeling WIM Errors, and Comparison of the ASTM and LTPP Accuracy Protocols
The data collected at Weigh-in-Motion (WIM) stations have many applications. Primarily, the data are used for pavement design, bridge design, freight studies, transportation planning, and enforcement. The WIM data are also used in mechanistic-empirical pavement design guide (Pavement-ME) for predict...
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Veröffentlicht in: | International journal of pavement research & technology 2024-09, Vol.17 (5), p.1124-1144 |
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Sprache: | eng |
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Zusammenfassung: | The data collected at Weigh-in-Motion (WIM) stations have many applications. Primarily, the data are used for pavement design, bridge design, freight studies, transportation planning, and enforcement. The WIM data are also used in mechanistic-empirical pavement design guide (Pavement-ME) for predicting performance. Highway agencies and the state department of transportation (DOTs) are the main users of WIM data. With a number of important applications, all WIM users desire to collect accurate loading data. This paper addresses three core issues related to WIM systems accuracy and calibration procedures, i.e., how to; (1) perform successful calibration of a WIM system by quantifying the effect of sample size (truck runs), speed, temperature, and truck type on measurement errors, (2) model gross vehicle weight (GVW) WIM errors as a function of individual axle errors [(single axle (SA) and two tandem axles (TA), (drive and trailer)], and (3) estimate WIM measurement errors using the long-term pavement performance (LTPP) and the ASTM protocols. The research objectives were accomplished by synthesizing and analyzing the WIM error data available in the LTPP database for bending plate (BP) and quartz piezo (QP) sensors. Successful WIM equipment calibration can eliminate systematic weights, speed, and axle spacing errors. The ASTM and the LTPP accuracy estimation methods agree; however, the methods should be compared when the sample size is small (10 or fewer truck runs). The representative pre- and post-calibration data can be collected accurately using one test truck with 12 or more runs at multiple speed points for QP and BP sensors. The developed models showed that the GVW errors could be accurately predicted using SA and two TA. The results also show that if GVW errors are within ASTM Type I tolerance, the SA and TA errors will likely be within acceptable limits. Therefore, calibrating a WIM site using GVW errors should continue. The suggested changes in current WIM procedures can significantly reduce time and resources for successful equipment calibration. |
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ISSN: | 1996-6814 1997-1400 |
DOI: | 10.1007/s42947-022-00267-7 |