# Comparative Accuracy Analysis of Truck Weight Measurement Techniques
## 4 Discussion  
The statistical parameters, such as mean and standard deviation, were calculated for all four weighing systems. For GVW, the minimum difference between the mean values of GVW recorded by portable scales and B-WIM system was 0.8 kips, and the standard deviation of the results was 5.6 kips for portable scales and 6.5 for B-WIM system. In contrast, the highest difference between the mean values of GVW was observed for WIM, with the highest standard deviation of 8.8 kips. For the axle weight measurements, the largest difference between the mean and standard deviation values was observed for the WIM measurement data set. It can be noticed that in the case of axles one to three loads, the difference in statistical parameters was relatively low. The most significant difference was for axle four and five. The average axle 1-3 loads were almost the same (around 16 kips), but in the case of axle four and five loads, the values of standard deviation are over 2.0 kips. Tandem axle weight analysis showed that in comparison to the certificated portable scales, the lowest difference between the mean and standard deviation values was observed in the case of the static scale's measurements data, the set for both the first tandem (axle 2 and 3) and the second one (axle 4 and 5). B-WIM measurement results mean that standard deviation values were slightly lower than the portable scales, but the statistical parameters' difference is relatively low. However, the most significant differences were noticed in WIM measurements. The standard deviation value was almost three times higher, and then the value of the standard deviation was obtained by the portable scale measuring technique. It means that the results of measurements varied much more. The multiple \(t\)-tests for paired means were conducted to check whether there was enough evidence to claim a difference in vehicle weight attributes for a 95% confidence interval. The mean difference and standard deviation of difference were computed. Table 8 summarizes the results of the mean and standard deviation of difference, compared to portable scales and weigh station measurements. Based on the comparison to portable scales measurements, it could be noticed that the mean difference was the smallest for weigh station measurements. The mean difference for GVW, AG1, AG2 was larger for WIM measurements than B-WIM. On the other hand, in comparison to weigh station measurements, it can be concluded that the mean difference was the smallest for portable scales but the largest for WIM measurements. Only, the first axle weight (W1) is larger for B-WIM measurements in comparison to the weigh station. The next step was to calculate the standard error for the compared measurements and find the t-value. Table 6 showed the calculated \(t\)-values for compared weighing systems. It can be concluded that t_stat was greater than t_crit. Therefore, the null hypothesis can be rejected, which means that with 95% confidence, there was enough evidence to claim there was a difference in the static and dynamic measurements. In the \(t\)-test analysis, the measurement tolerances were not taken into account. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multicolumn{3}{c}{**Portable Scales**} & \multicolumn{3}{c}{**Weigh Station**} \\ \cline{2-7}  & **B-WIM** & **Weigh Station** & **WIM** & **B-WIM** & **Portable Scales** & **WIM** \\ \hline GVW & 0.87 & 0.64 & 0.68 & 0.59 & 0.64 & 0.45 \\ W1 & 0.67 & 0.80 & 0.60 & 0.66 & 0.80 & 0.52 \\ W2 & 0.80 & - & 0.72 & - & - & - \\ W3 & 0.81 & - & 0.75 & - & - & - \\ W4 & 0.72 & - & 0.60 & - & - & - \\ W5 & 0.76 & - & 0.73 & - & - & - \\ AG1 & 0.84 & 0.78 & 0.74 & 0.77 & 0.78 & 0.51 \\ AG2 & 0.80 & 0.65 & 0.76 & 0.59 & 0.65 & 0.47 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Summary of the correlation coefficients calculated for portable scales and weigh station measurements.