## 3 Case Study
### Identification of SOTIF-Related Causes
According to the proposed SOTIF-related classification in Section 2.1.2, the SOTIF-related causal scenarios and causal factors of these UCAs are identified by analyzing the interactions in the control structure. As a result, 154 SOTIF-related causal factors are found in this analysis. Due to limited space, one typical unsafe control action and part of its causal factors are shown as an example in the following. UCA2: The driver does not provide a brake before the train breaks the speed/distance restriction regarding the front train. * CF105. The TIDS does not timely detect the front train. * CF18. The object is in the position that sensors of the TIDS cannot detect. * CF19. The vision of the cameras is blocked due to the geographic characteristics of the section. * CF20. The train is running on a curve. * CF21. The train is running on a slope. * CF22. The inherent blind zone of the cameras. * CF23. The quality of the image from cameras is too poor for perception. * CF8. The driver excessively trusts the TIDS in terrible operational environments. * CF24. The cameras are affected by the atmospheric visibility. * CF25. Terrible weather affects the visibility. * CF8. The driver excessively trusts the TIDS in a terrible operational environment. * CF4. Terrible weather such as rain, snow, sand, or fog. * CF26. The working condition of the train affects the quality of the image from cameras. * CF27. Vibration. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Control Action** & **Not Providing Causes Hazard** & **Providing Causes Hazard** & **Too Early, Too Late, Out of Order** & **Stopped Too Soon, Applied Too Long** \\ \hline \hline \multirow{4}{*}{Brake} & UCA1: The driver does not provide a brake before the train breaks the speed/distance restriction regarding human/obstacle (H1). & UCA5: The driver provides brake too late to decelerate to the speed limit of the section ahead (H1 and H2). \\ \cline{1-1}  & UCA2: The driver does not provide a brake before the train breaks the speed/distance restriction regarding the train in front (H1). & UCA6: The driver uses the thermostals outside the operational design domain (H1 and H2). \\ \hline \multirow{4}{*}{Turn off the TIDS} & UCA8: The driver provides unnecessary emergency brake (H3). & UCA6: The driver uses the thermostals outside the operational design domain (H1 and H2). \\ \cline{1-1}  & UCA7: The driver drives at the speed of assistant mode while the TIDS is off (H1 and H2). \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The identified unsafe control actions (UCAs). * CF28. Degradation of mechanical components of cameras and bad maintenance. * CF29. Water film or sand cover the lens. * CF4. Terrible weather such as rain, snow, sand, or fog. * CF30. Cameras are affected by the illumination condition. * CF31. The illumination is too strong or too weak. * CF32. The light of an opposite train. * CF33. The illumination changes when entering or leaving a tunnel. * CF34. The different illumination during a day. * CF35. The different illumination in different seasons. * CF36. Cameras are exposed directly to an external artificial light. * CF106. Some characteristics of the object train make the train not obvious in the image. * CF107 The lights on the front train are off. * CF108. The coating of the train is not distinct from the background color. * CF109. The lights on the front train are off. * CF110. Rain, snow, or sand covers the surface of the train. * CF4. Terrible weather such as rain, snow, sand or fog. * CF43. The speed of the image recognition is not enough. * CF44. The algorithm is inefficient. * CF45. The software aging during long time operation. * CF44. The image recognition efficiency is low in some operational scenarios. * CF47. The lack of computing power in hardware. * CF111. The image recognition algorithm based on machine learning has some flaws recognizing the front train. * CF49. The situation in the operation is too far from that of the training data. * CF50.