# Automatic Bridge Design Parameter Extraction for Scan-to-BIM
## 4 On-Site Field Validation
### On-Site Field Validation Result and Discussion  
The PCD of the bridges used for Section 3 (extracted directly from the BIM model) was very clear; the PCD did not contain significant data loss for certain point of view. However, most of the data points in the inner part of the bridge was missing when the PCD was obtained by LiDAR as shown in Figure 22. Even though the LiDAR was installed under the bridge, the LiDAR pulse could not fully reach the top of the girder. The proposed system was applied sequentially as discussed in Section 2. First, since the data obtained through LiDAR has noise, the noise was removed through the statistical outlier removal filter (Section 2.2). In the next step, the measurement coordinate system was transformed to the bridge coordinate system. By applying the MSAC algorithm, the most probable plane of the bridge was predicted as shown in Figure 23. The normal vector and the longitudinal direction vector of the plane were extracted, and the corresponding 3D rotation matrix and translation vector were calculated. Using the 3D rotation matrix and the translation vector, the PCD were transformed from the measurement coordinate to the bridge coordinate system as shown in Figure 24. Finally, the design parameters of the beam girder bridge were extracted by decomposing the PCD into multiple layers (Figure 25) and calculating the plane distance as described in Section 2.3. Figure 23: Plane prediction for the Osong test track fifth bridge using the MSAC. Figure 22: Front view (X-Z plane) of point cloud data for Osong test track fifth bridge. Design parameters for the Osong test track fifth bridge were predicted by each span as shown in Table 2. The parameter \(H_{3}\), which represents the thickness of the slab, could not be measured due to railroad gravel. Therefore, the experiment was conducted except for this. The parameter \(W_{4}\) and \(W_{5}\) for span 14 was not predicted, because the PCD was lost. Since the reference value for the parameter was also unable to be measured, this parameter was excluded when calculating the average. The total average error rate for each parameter was about 0.8%. As discussed in the BIM model-based validation test, the parameter that contains more points showed higher accuracy. For example, \(L_{1}\) showed the lowest error (about 0.06%) rate and \(W_{5}\) showed the highest error rate (about 2.17%). By comparing the results of span 2 showed the lowest error rate of about 0.5%, while span 6 had the highest error rate of about 1.35%. This is due to the difference in the PCD quality (noise + data loss) obtained by LiDAR. There are four major sources of the error in the on-site field test. The first source of the error is due to the LiDAR measurement. The LiDAR measurement includes device errors (the inherent error due to the mechanical device) and random errors (remaining error even after removing the error). However, since reference values for the design parameters are obtained manually from the LiDAR data instead of using the parameter from drawings the reference value, the first source of error is assumed to be negligible. The second is the data loss due to the blind spot of the LiDAR measurement. Due to the characteristics of LiDAR, it is not possible to obtain data on certain areas where the laser pulse could not be reached. For example, the PCD in the inner part of the span 14 was omitted as discussed in above, and thus the parameters (i.e., \(W_{4}\) and \(W_{5}\)) of the beam were unable to be predicted. The second source of the error is expected to be decreased with the advance of LiDAR technology. The third is the error caused by point cloud registration (or scan matching). For the on-site validation test, LiDAR measurements were performed in various directions. To combine the PCD into a single  
Figure 24: Measurement coordinate system (**left**) and bridge coordinate system (**right**) for the Osong test track fifth bridge. Figure 25: PCD decomposition for the Osong test track fifth bridge. model, point cloud registration conducted.