# Comparative Accuracy Analysis of Truck Weight Measurement Techniques
## 2 Material and Methods
### B-WIM Instrumentation
Based on the collected vehicle data, there was a possibility to analyze cross-sectional forces  
Figure 4: Considered truck weigh systems: (**a**) overview, (**b**) specific locations. acting on selected elements of the bridge. However, the assessment of these options was not part of this study. The three days of measurements were performed on 6, 16, and 18 March 2020. Approximately 50 trucks were measured per day, and in total, the sample data was nearly 150 vehicles. All measured vehicles were class 9 vehicles, with 5-axles, and typically with a steering axle and two tandem axles (two neighboring axles with spacing between them not exceeding 6 ft.). From the ALDOT WIM data analysis, it was concluded that over 43% of all collected data were class 9 vehicles, and it was decided to perform the analysis for the most typical trucks in Alabama traffic. The ALDOT WIM data was continuously recorded, and the decrypted WIM data was transferred for all three days of measurement. The static measurements were conducted by the State Troopers, and the data was given in a printed version, including vehicle parameters, time stamps, and plate number. The collected traffic data by static scales were as follows: 6 March--42 trucks, 16 March--48 trucks, and 18 March--50 trucks. The weigh station measured the steering axle and two tandems, but the portable scales weighted every axle separately. The weigh-in-motion data was then analyzed to find the measured vehicles by the number of axles, the time stamp, plate number, and US DOT number. All the statically measured vehicles were captured in the WIM database. Afterward, the B-WIM system was analyzed to find the measured vehicles. To capture the vehicles, the vehicle class, a number of axles, timestamp estimation, the distance, and the speed limit were considered to match those vehicles. The B-WIM was located further from other truck weigh station, with exit 205 to route 46 located between them. Thus, some of the vehicles were able to exit I-20. Therefore, a few of them were not found in the B-WIM system--they did not pass the weighting system in the predicted time window or, the truck was not recognized while passing with another similar vehicle. Figure 6 presents the traffic data collection flowchart. The data analysis captured 34 trucks on 6 March, 46 trucks on 16 March, and 49 trucks on 18 March. An overall number of considered vehicles measured by portable scales is 140, truck weigh station--139, WIM--136, and 127 by B-WIM system. The matching vehicles were taken into consideration in the accuracy analysis. Figure 5: Simplified measurement scheme [28]. All four measuring techniques captured different vehicle parameters. The following vehicle attributes were considered during the analysis: GVW, axle weight, and tandem axle weight. Figure 7 shows the symbols of attributes used in this study. The attributes available for considered weighing systems are summarized in Table 1.  
The measurement accuracy was assessed by comparing the results of measurements by static and dynamic weighing systems. The analysis of measurement accuracy involved the following:  
* statistical analysis of the considered parameters,
* multiple \(t\)-tests for paired means,
* vehicle attributes tolerances, according to ASTM E1318-09 2009 (Table 2, WIM Type I),
* correlation coefficient calculations. Figure 6: Traffic data collection flowchart. Figure 7: Attributes of the vehicle considered during measurements.