## 4 Discussion  
This study was conducted for developing a collision encountering situation in a simulator using a navigator's behavior model for ship maneuvering. The main contribution of this study is the development of success and failure models to investigate navigator errors from behavior on ship collision avoidance. As mentioned in Section 2.2.1, four variables--rudder, engine, planned route control, and dCPA control--have been applied for the performance level calculation during the simulation time. The reason why these four variables were applied during the simulation time can  
Figure 10: Maneuvering behavior models: (**a**) success of collision avoidance, and (**b**) failure of collision avoidance.  
be explained as follows. First, planned route tracking and dCPA control require both rudder and engine use. Second, changing the vessel course for planned route tracking can lead to a change in dCPA. Third, changing the ship course for dCPA control can cause changes in planned route tracking. As in these three explanations, the four variables have mutual influences. Thus, in this study, the four variables are used in the performance level calculation during simulation time. Moreover, as mentioned in Section 2.2.1, the maximum time estimate for calculating performance levels has been an issue. Unfortunately, the maximum time required to calculate performance levels is not known [36]. The reason for this is that depending on the given situation, the possibility of a performance level varies. Thus, in this study, a collision-prone scenario is applied to the simulation experiment. A study on the estimation of the optimal time required to calculate the performance level was left as a future research work.  
As mentioned in Section 2.2.2, the failure model had higher discriminative power than the success model. This can be interpreted as follows. Since collision avoidance failure was determined after a normal navigational situation, both models had normal navigation situations [44; 45; 46]. In particular, the success model reflects more of the normal navigation situation compared to the failure model. Thus, the failure model can be interpreted as having greater discriminative power than the success model. On the other hand, as mentioned in Section 3.3, different transition characteristics were found between the success and failure models. This can be interpreted as follows. In ship maneuvering, device control technology and route control techniques have complementary characteristics [47; 48]. Successful route control requires a high level of device control technique. Also, the device control effect can be confirmed in a short amount of time compared to the route control effect, and effective route control requires long boarding experience and knowledge. Hence, this results in differences in transfer characteristics for the models.  
It is important to distinguish between measurements in this real-field environment and measurements in virtual reality. The real-field environment was practically difficult due to time and cost [24]. Because this is the reason for the use of virtual reality, the results are expected to be real-field [49]. For the same reason, it is necessary to perform additional verification, because it is an experiment in which the participants of the experiment are aimed at the reserve navigator. Also, the rudder and engine have been used for the analysis of ship's course-keeping control in maritime fields [50], but we propose an analysis method for the error of the navigator divided by device control behavior and route control behavior.  
This problem in ship control techniques has been raised previously in ship navigation, and it is about whether the technique comes first or experience [51; 52]. This will be the subject of further research.