## 5 Results  
The experimental field was in the Chang Hua Coastal Industrial Park. The route is shown in Figure 5. The route is 7.5 km long. The positioning system was deployed in the WinBus. The fault detection algorithm was integrated with the system in the WinBus. This experiment obtained three results from three positioning methods: the RTK, SLAM, and prediction. The results were used to compare the different positioning methods for the coordinate results' effect. The result compares the SLAM and RTK information shown in Figure 6. The figure was generated from the latitude and longitude data. The red line presents the SLAM result, and the yellow line shows the RTK. This finding shows that these two positioning systems indicate the two trajectories in the figure. By comparing the actual route with the results, we can see that the SLAM system contained some errors. We discuss the failure detection mechanism below, as well as how to use this mechanism to increase the accuracy of the positioning system. Figure 7 compares the RTK, SLAM, fusion, and prediction results. The fusion result is the blue line from Equation (1), shown in Figure 7. The prediction result is the green line, shown in Figure 7. This result is from Equations (2) and (3). There were some errors detected without a fault detection method that were compared the RTK result. The prediction result showed that the track was similar to the RTK. Another compar  
Figure 5: The experimental route. Figure 6: Comparison of SLAM and RTK results. prediction data showed that the information was similar to the actual trajectory. This also proved that the prediction results and RTK are reliable information for autonomous applications in this field. Figure 8 includes all of the above results for comparison. The purple line is the fusion with the fault detection mechanism. Here, we discuss the impact of the fault detection mechanism of the positioning system. From the previous discussion, it can be seen that this prediction method is feasible. Finally, we compared the actual path, the predicted path, and the results of the fusion algorithm based on the fault detection mechanism. The results showed that the fault detection mechanism can effectively correct the coordinate results of the positioning system. Figure 9 (Iongitude) and Figure 10 (latitude) compare each result. In the figures, lines of different colors represent RTK, SLAM, fusion, prediction, and fusion with the diagnostic mechanism results. The result showed that the SLAM and fusion without any fault detection mechanisms had some problems. Figure 8: Comparison of the RTK, SLAM, fusion prediction, and fusion with the diagnostic mechanism results. Figure 7: Comparison of SLAM, RTK, fusion, and prediction results. We also performed a more detailed comparison regarding the location of anomalous coordinates. Figures 11 and 12 show the parts with abnormal coordinates in Figures 9 and 10, respectively. Figures 11 and 12 show the results of the longitude and latitude coordinates of each method's coordinates, respectively. These diagrams show the coordinates of the anomalous parts for further discussion. The results showed that the coordinates results of SLAM cannot satisfy the requirements for autonomous vehicle applications. SLAM has the greatest number of mistakes after comparing all the methods. Due to the deviation of the coordinates, the system's operation may be faulty. Figure 10: The results from each positioning method (latitude). Figure 9: The results from each positioning method (longitude). The coordinate fusion method was based on Equation (1). The grey line shows the result obtained by the original fusion algorithm. This result is compared with the SLAM and RTK results, shown in Figures 11 and 12. The original fusion result was without reference fault information. This result showed that the fusion algorithm was able to correct the biases in the coordinate information, but it was not sufficient. The original fusion algorithm only considered the weights occupied by the various positioning systems.