## 6 Conclusions  
In this paper, we have presented plausible methods for a FMCW TMRD system to achieve high detection accuracy of multiple-lane vehicle flow and traffic volume. Noticeably, FFT-, and lane-related  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{(**a**) Proposed Method 2} \\ \hline
**Lane** & **Actual Vehicle Number** & **Detected Vehicle Number** & **LVF Accuracy** & **DTV Accuracy** \\ \hline A & 119 & 124 & 95.8\% & 99.2\% \\ B & 123 & 120 & 98.4\% & 99.2\% \\ \hline C & 84 & 88 & 95.2\% & 99.4\% \\ D & 94 & 89 & 94.7\% & 99.4\% \\ \hline \multicolumn{4}{c}{(**b**) Conventional Method} \\ \hline
**Lane** & **Actual Vehicle Number** & **Detected Vehicle Number** & **LVF Accuracy** & **DTV Accuracy** \\ \hline A & 119 & 135 & 86.6\% & 87.6\% \\ B & 123 & 137 & 88.6\% & 86.5\% \\ \hline C & 84 & 96 & 85.7\% & 86.5\% \\ D & 94 & 106 & 87.2\% & 86.5\% \\ \hline \hline \end{tabular}
\end{table}
Table 10: Results of LVF and DTV detection during 7:30-7:40 PM (rush-hour traffic) using (**a**) proposed method 2 and (**b**) conventional method.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{(**a**) Proposed Method 1} \\ \hline
**Lane** & **Actual Vehicle Number** & **Detected Vehicle Number** & **LVF Accuracy** & **DTV Accuracy** \\ \hline A & 66 & 72 & 90.9\% & 100\% \\ B & 95 & 89 & 93.7\% & 99.4\% \\ \hline C & 71 & 77 & 91.5\% & 99.4\% \\ D & 89 & 84 & 94.4\% & 99.4\% \\ \hline \multicolumn{4}{c}{(**b**) Conventional Method} \\ \hline
**Lane** & **Actual Vehicle Number** & **Detected Vehicle Number** & **LVF Accuracy** & **DTV Accuracy** \\ \hline A & 66 & 74 & 87.9\% & 90.0\% \\ B & 95 & 103 & 91.6\% & 90.0\% \\ C & 71 & 78 & 90.1\% & 89.3\% \\ D & 89 & 99 & 88.8\% & 89.3\% \\ \hline \hline \end{tabular}
\end{table}
Table 11: Results of LVF and DTV detection during 7:50–8:00 PM (rush-hour traffic) using (**a**) proposed method 1 and (**b**) conventional method.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{(**a**) Proposed Method 2} \\ \hline
**Lane** & **Actual Vehicle Number** & **Detected Vehicle Number** & **LVF Accuracy** & **DTV Accuracy** \\ \hline A & 78 & 74 & 94.9\% & 100\% \\ B & 89 & 93 & 95.5\% & 100\% \\ C & 65 & 68 & 95.4\% & 97.9\% \\ D & 78 & 72 & 92.3\% & 97.9\% \\ \hline \multicolumn{4}{c}{(**b**) Proposed Method 1} \\ \hline
**Lane** & **Actual SSVehicle Number** & **Detected Vehicle Number** & **LVF Accuracy** & **DTV Accuracy** \\ \hline A & 78 & 73 & 93.6\% & 98.8\% \\ B & 89 & 92 & 96.6\% & 98.8\% \\ \hline C & 65 & 67 & 96.9\% & 95.8\% \\ D & 78 & 70 & 89.7\% & 95.8\% \\ \hline \hline \end{tabular}
\end{table}
Table 12: Results of LVF and DTV detection during 8:10–8:20 PM (rush-hour traffic) using (**a**) proposed method 2 and (**b**) proposed method 1.  
information are incorporated into the development of the proposed methods 1 and 2. Unlike the conventional scheme, the proposed methods can make smart decisions for reducing the effects of FFT side lobes of vehicle signals adverse to traffic detection. Therefore, the proposed methods can significantly outperform the conventional method. Predicted performance analysis shows that the proposed method 2 is more sophisticated and adaptive in terms of the detection of vehicle number within a lane than the proposed method 1. Based on FFT and time-stamp information, we can also obtain an equivalent alternative of the proposed method 2. On-site experiments have confirmed that the proposed methods 1 and 2 significantly outperform the conventional scheme. In addition, the proposed method 2 can achieve the best overall performance over the proposed method 1.  
This research work of [PERSON] was partially supported by Chung Yuan Christian University.  
[PERSON] and [PERSON] initiated and discussed the research problem; [PERSON] conceived and developed the methods; [PERSON] performed the experiments and took photos; [PERSON] and [PERSON] analyzed the data; [PERSON] prepared and wrote the paper.  
The authors declare no conflict of interest.