Trans RINA, Vol 161, Part A4, Intl J Maritime Eng, Oct-Dec 2019
computational time of the WBDA (≈ 0.02 s) is much shorter than the GA-based approach (14-26 s). The WBDA based trajectory comprises of 2 leg, while GA- based trajectory is composed of 3 leg.
4.4 (b) Case 5: Crossing Situation (adjusted)
In the GA-based approach, the OS alters her course to avoid collision after proceeding for a while (called as T1 in the study). The WBDA, however, calculates the optimal course assuming that the OS alters her course in its current position without proceeding for a while. Therefore, in order to able to compare the length of trajectories from beginning collision avoidance course alteration, the input data, especially the distance between ships and the relative bearing of the TS, to be entered into the WBDA is needed to be adjusted according to data within GA-based approach. The calculation for the adjustment is shown in Figure 1A. Trajectory solutions for the OS provided by both approaches according to adjusted data is shown in Figure 15. Numerical results are listed in Table 4. The case has similar conclusions as Case 4 and the length of trajectory calculated by the WBDA is 1.02 Nm shorter than that generated by the GA-based algorithm.
test results have revealed that the system is practicable and feasible to solve the optimal collision avoidance problem. The WBDA is compared to GA-based approach and it is revealed that the solution calculated by the method considerably outperforms the heuristic-based approach. The other advantage of the method is that it can produce an identical solution for every run which is not generally possible for heuristic-based algorithms.
In this method, the action taken by the OS to eliminate the collision risk is limited to course alteration. The speed change which is not frequently applied in real operation unless critical situations occur, can be considered in order to upgrade the proposed method which can provide more flexible control. The scope of the study is one-to-one encounter situations because of the nature of COLREGs but, as a further study, the algorithm structure of the method can be adapted to multiple encounter situations. The proposed system can provide guidance to navigators in case of encounter situation at sea. It is believed that the method introduced in the study can contribute to extend the navigation characteristic of the modern ships as well as automation of ship motion control, ship traffic engineering and e-navigation strategy.
To summarize, the following features of the method have come into prominence: • meeting the requirements stipulated by COLREGs. • easy to use, • web accessibility and not require an installation, • very short execution time, • the constant solution value and the same execution time for every run,
• the OS can return to its original route at specified point.
Figure 14. Comparison of trajectories generated by WBDA and GA for Case 4
5. CONCLUSION
A new web-based deterministic method is introduced in the study to solve the ship collision avoidance optimization problem. Experimental tests comprising five encounter situations have been implemented to prove the effectiveness of the proposed method. The experimental
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Figure 15. Comparison of trajectories calculated by WBDA and GA for Case 5
©2019: The Royal Institution of Naval Architects
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