## 4 Verification and Analysis
### Long-Term Stability Verification  
In order to verify the long-term stability of the proposed method in the paper, we used the statistical data of the inductance loop vehicle detector as a reference. The experimental data from 1 October to 30 October in 2018 is shown as follows.  
From Figure 6, we can also see that the overall accuracy of our proposed two-sensors fusion method is 0.97% higher than that of the traditional single magnetism-based detection method. The main reason for the result is that most of the large vehicles running on the tested road are public buses and commuter buses, which will be out of service after 7 PM. What is more, there are very few big trucks and pickup trucks running on the tested road and the small vehicles account for a high proportion of the total traffic flow on the tested road.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Single**} & \multicolumn{3}{c}{**Proposed**} & \multicolumn{3}{c}{**Inductance Loop**} \\  & \multicolumn{3}{c}{**Manual Statistic**} & \multicolumn{3}{c}{**Magnetism-Based**} & \multicolumn{3}{c}{**Two-Sensors Data**} & \multicolumn{3}{c}{**Vehicle Detector**} \\  & & & \multicolumn{3}{c}{**Method**} & \multicolumn{3}{c}{**Fusion Method**} & \multicolumn{3}{c}{**Vehicle Detector**} \\ \cline{2-10}
**Periods** & **big** & **small** & **big** & **small** & **big** & **small** & **big** & **small** & **big** & **small** \\  & **vehicle** & **vehicle** & **vehicle** & **vehicle** & **vehicle** & **vehicle** & **vehicle** & **vehicle** & **vehicle** \\  & **number** & **vehicle** & **number** & **number** & **number** & **number** & **number** & **number/** & **number/** & **number/** \\  & & & & **accuracy** & **accuracy** & **accuracy** & **accuracy** & **accuracy** & **accuracy** \\ \hline
07:30–07:50 & 21 & 72 & 24/85.7\% & 75/95.8\% & 22/95.2\% & 73/98.6\% & 22/95.2\% & 72/100\% \\
08:00–08:20 & 19 & 81 & 24/73.6\% & 83/97.5\% & 20/94.7\% & 82/98.7\% & 19/100\% & 82/98.7\% \\
12:00–12:20 & 7 & 39 & 8/85.7\% & 40/97.4\% & 7/100\% & 39/100\% & 7/100\% & 39/100\% \\
12:30–12:50 & 10 & 32 & 11/90.0\% & 32/100\% & 11/90.0\% & 33/96.8\% & 10/100\% & 32/100\% \\
17:00–17:20 & 28 & 89 & 32/85.7\% & 92/96.6\% & 29/96.4\% & 93/95.5\% & 28/100\% & 90/98.9\% \\
17:30–17:50 & 24 & 85 & 28/83.3\% & 85/100\% & 25/95.8\% & 86/98.8\% & 24/100\% & 85/100\% \\ Total & 109 & 398 & 127/83.4\% & 407/98.0\% & 114/95.4\% & 406/98.2\% & 110/99.0\% & 400/99.4\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: Short-term vehicle detection statistical results.  
Figure 6: Long-term vehicle statistics and accuracy comparison.  
From Table 1, we can find that the small vehicle detection accuracy of ours is as similar as that of traditional single magnetism-based detection method. Due to the above several reasons, the overall accuracy of our proposed method is only slightly improved compared with the traditional single magnetism-based vehicle detection method in the long-term test. From the above analysis, we can find that the proposed method can work as stable and reliable as the inductance loop and the traditional single magnetism-based vehicle detectors.