## 3 Performance Evaluation of Autonomous Driving Control Algorithm
### Performance Evaluation  
Three trajectories were used in the performance evaluation of the autonomous driving control algorithm. The first trajectory contained 65 waypoints, and the length of the first trajectory was 51 m. The first trajectory included three straight-line sections, one curve section, and one in-situ rotation section. In Figure 7a, the blue points are the waypoints and the red points are the vehicle running in the first trajectory. Figure 7b shows a path-following error and the vehicle's yaw. In the first trajectory, the maximum error of the path-following was calculated to be 0.21 m, and the RMS of the path-following error was 0.09 m. It was found that the error of the in-situ rotation section was higher than that of the other sections, as shown in Figure 7. This result was caused by slip due to vehicle dynamic force when the vehicle stopped in the in-situ rotation section. Figure 8a,b show the vehicle location with the waypoints for the second trajectory and the path-following error with the vehicle's yaw, respectively. As seen in Figure 8, the second trajectory is composed of four curved sections and five straight-line sections. The number of waypoints was 90 and the length of the trajectory was 81 m. Compared with the first trajectory, the turning radius was narrower in the curve sections. The RMSE (Root Mean Square Error) of the path-following was 0.07 m. Specifically, the vehicle was following the path well, but the largest path-following error, which was 0.21 m, occurred in the end part of the first curve section. It means that the set radius for searching a target point was not perfectly operated to follow the desired path in the narrower curve section. Therefore, perfectly to operate autonomous driving, it is considered that an algorithm for adjusting the target search distance according to the turning radius should be added through various field tests. The third trajectory consists of 111 waypoints with a total length of 81 m. The third trajectory includes five straight-line sections, two curve sections, and three in-situ rotation sections. The vehicle location with the waypoints for the third trajectory and the path-following error with the vehicle's yaw are shown in Figure 9. The maximum error and RMSE of the path-following are 0.29 and 0.07 m, respectively. It can be seen that autonomous driving was operated more precisely in curve sections as the turning radius of curve sections is wider than that of curve sections of the second trajectory. However, because the vehicle cannot be perfectly reached, the rotation in-situ waypoint, the first in-situ rotation section, has incurred the largest error. It is considered that the above problem can be solved by adjusting the acceptance radius for switching waypoint based on the characteristic of waypoints such as stop and go. Figure 7: Autonomous driving results in the first trajectory: (**a**) driving path with waypoints; (**b**) path-following error with the vehicle’s yaw. Summing up the test results, the RMS of the path-following error at three trajectories was calculated to be 10 cm and the maximum error was also bound smaller than 30 cm. However, numerous performance analysis based on various agricultural environments that are used by the autonomous driving agricultural vehicle is necessary to commercialize an autonomous driving system for a crawler-type agricultural vehicle. Moreover, to improve the stability and accuracy, the upgrade of the algorithm would be carried out as follows, in the future. At various curve paths, it is necessary to add the adjustment of an adaptive search radius for the enclosed-based LOS guidance depending on the turning radius for stable autonomous driving. Adjusting the acceptance radius for switching waypoint based on the characteristic of waypoints such as stop and go will be also added in the proposed algorithm.