# A Study on the Evaluation Method of Highway Driving Assist System Using Monocular Camera
## 5 Conclusions  
In this study, we proposed a method to evaluate HDA systems using a monocular camera and verified its reliability through a real vehicle test with DAQ and DGPS. The main findings are summarized below:  
1. We used a monocular camera (1920 \(\times\) 1080/30 frames per second) similar to the commercial black-box camera specification.
2. The evaluation method used the images captured by the camera and the geometric composition of the lead vehicles to calculate the distances of the lead vehicle and the center of the lane.
3. A test was conducted using a vehicle with DAQ and DGPS to verify the reliability of the proposed method, and the theoretical values of the monocular camera method were compared with the results of the real vehicle test for analysis.
4. The comparative analysis revealed a maximum error of 0.15 m for the distance to the center of the lane in scenarios 5 and 10, and 5.11 m for the distance to the lead vehicle in scenario 8. The maximum errors occurred on the curved sections of the road, which can be attributed to the difficulties in predicting and detecting the lane, and the large changes in the yaw rate and heading angle of the vehicle when turning.
5. The maximum error between the results of the monocular camera method and the real vehicle test with DGPS and DAQ was 8.6% in the longitudinal direction in scenario 8, 8.2% in the lateral direction in scenario 5, and 8.1% in the lateral direction in scenario 10. Therefore, the method using a monocular camera can be deemed reliable because of the small margin of error.
6. This study proved that it is possible to test and evaluate HDA systems using only a monocular camera, without the need of experts handling expensive equipment such as DGPS and DAQ, thereby saving time and costs.  
In future, we will conduct further research on instances where the lanes cannot be detected or when the rear tries of the preceding vehicle (as in the case of specially modified vehicles) are not visible.  
Conceptualization: S.B.L., methodology: S.B.L., actual test: G.H.B. and S.B.L., data analysis: G.H.B. and S.B.L., investigation: G.H.B., writing--original draft preparation: G.H.B. and S.B.L., writing--review and editing: G.H.B. and S.B.L. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Scenario No.**} & \multicolumn{3}{c}{**Distance to Lead Vehicle (m)**} & \multicolumn{3}{c}{**Distance to Center of Lane (m)**} \\ \cline{2-7}  & **Theoretical Value** & **Test Result** & **Error** & **Theoretical Value** & **Test Result** & **Error** \\ \hline
1 & - & - & - & 0.05 & 0.16 & 0.11 \\
3 & - & - & - & 0.33 & 0.42 & 0.09 \\
4 & - & - & - & \(-\)0.03 & 0.07 & 0.10 \\
5 & - & - & - & 0.30 & 0.45 & 0.15 \\
6 & 5204 & 55.22 & 3.18 & 0.23 & 0.34 & 0.11 \\
8 & 54.39 & 59.51 & 5.11 & 0.03 & 0.16 & 0.13 \\
9 & 34.32 & 37.19 & 2.87 & \(-\)0.45 & \(-\)0.34 & \(-\)0.11 \\
10 & 23.02 & 21.09 & \(-\)1.93 & 0.20 & 0.35 & 0.15 \\
11 & 27.01 & 29.88 & 2.87 & 0.03 & 0.15 & 0.13 \\
12 & 27.82 & 30.30 & 2.47 & \(-\)0.48 & \(-\)0.41 & 0.07 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Maximum calculation errors per scenario.  
**Funding:** This research was funded by the Ministry of Trade, Industry and Energy and the Korea Institute of Industrial Technology Evaluation and Management (KEIT) in 2020, grant number 10079967.  
**Acknowledgments:** This work was supported by the Technology Innovation Program (10079967, Technical development of demonstration for evaluation of autonomous vehicle system) funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea).  
**Conflicts of Interest:** The authors declare no conflict of interest.