## 7 Conclusions  
In conclusion, this study addresses the ongoing verification of key technologies in Maritime Autonomous Surface Ships (MASS), emphasizing the development of a Synthetic Maritime Traffic Generation System (S-MTGS). This system, comprising a maritime traffic generator and a collision avoidance algorithm, stands as a robust solution for assessing MASS performance in both hazardous and routine scenarios.  
The maritime traffic generator, incorporating both absolute and relative position-based generators, utilizes historical data to craft scenarios or generate virtual ships based on diverse encounter situations. Notably, virtual ships can engage in collision avoidance maneuvers using the integrated algorithm, ensuring a comprehensive evaluation of MASS technologies. The capacity of S-MTGS to generate diverse maritime traffic scenarios aligns with the varied objectives of verifying MASS technologies, thereby contributing to heightened reliability and optimized performance in a secure operational context. Key advantages include the streamlined creation of diverse scenarios under consistent conditions, which differentiates it from traditional methods requiring individual setups for each case. Additionally, the system's adaptability allows it to dynamically create scenarios based on the ship's position for enhanced testing effectiveness, particularly in situations involving deviations from the planned route due to collision avoidance.  
However, an identified limitation is the uniformity of collision avoidance patterns among virtual ships, which typically employ a single algorithm. Addressing this issue, future research should aim to diversify these patterns by including a variety of collision risks and behavioral patterns. Such diversification is key to enhancing the reliability of performance verification and ensuring compliance with international maritime regulations. Furthermore, it is crucial to explore whether the potential for simultaneous collision avoidance maneuvers could inadvertently elevate the risk of accidents, especially in the context of evaluating the efficacy of different systems.  
In essence, the S-MTGS emerges as a significant contribution to the verification landscape of MASS technologies that can help to foster advancements in maritime safety and technology. Its ongoing refinement, coupled with the incorporation of diversified collision avoidance patterns, positions the system as a pivotal player in shaping the rigorous standards governing autonomous maritime operations.  
Conceptualization, K.K. and E.L.; methodology, E.L. and U.Z.; software, E.L. and J.K. ([PERSON]); validation, E.L., J.K. ([PERSON]) and U.Z.; formal analysis, E.L. and S.K.; data curation, E.L. and S.K.; writing--original draft preparation, E.L. and J.K. ([PERSON]); writing--review and editing, E.L.; visualization, E.L.; supervision, K.K.; project administration, K.K.; funding acquisition, K.K. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This study was partly supported by the \"Regional Innovation Strategy (RIS)\" through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE) (2021 RIS-004) and an Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korean government (MSIT) (No. RS-2022-00155857, Artificial Intelligence Convergence Innovation Human Resources Development (Chungnam National University)).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data can be obtained by contacting [EMAIL_ADDRESS].  
**Conflicts of Interest:** The authors declare no conflicts of interest.