Virtual Framework for Verification and Validation of Marine Autonomous Navigation

As maritime autonomous navigation technologies develop, traditional documentation-based or physical test-driven verification and validation (V&V) methods are inadequate to capture the wide variety of real-world operational scenarios due to the substantial costs, logistical complexity and inherent safety concerns of field testing. To address this issue, this work presents a modular, high-fidelity virtual simulation framework designed to support the V&V of autonomous marine navigation functions. The framework integrates dynamic models of marine vessels, sensors, neighboring vessels, and autonomous navigation algorithms along with performance indicators to verify and validate specifications of autonomous navigation functions in various marine navigation scenarios which are necessary for regulatory approval and certification compliance. INTRODUCTION As the maritime industry continues to adopt digitization and new digital tools, stakeholders must embrace the promise of emerging technologies while remaining aware of their limitations. One of the most captivating advances is autonomy; in particular, smart technologies have been developed to advance autonomous navigation, which is exemplified by the IMO Maritime Autonomous Surface Ships (MASS) program. The MASS program holds great promise for addressing critical challenges within the maritime industry, including reducing operator cognitive workload, optimizing vessel operations, and mitigating risks to human life, vessels, and the environment (Kim et al., 2022; Wróbel et al., 2017). As various stakeholders work to capitalize on the commercialization of MASS, the successful integration of these technologies will be the cornerstone of their impact. Implementing MASS will affect all stakeholders, including policy makers, shipowners, and seafarers (Issa et al., 2022). Additionally, the development of autonomous systems for MASS faces significant obstacles due to high costs, potential safety risks, and the logistical complexities of real-world testing. Therefore, before moving forward with MASS implementation, a thorough understanding of both the benefits and potential drawbacks of the new autonomous technologies in MASS is vital. Further, these autonomous systems must be tested in representative conditions that MASS would experience in the real-world. Replicating rare or extreme conditions such as severe weather, equipment failures, or collision scenarios safely and economically adds another layer of difficulty towards the development and evaluation of autonomous navigation systems (Felski and Karolina, 2020; Chan et al., 2025). Addressing these multifaceted challenges will require a comprehensive and methodical approach to ensure the safe and reliable operation of autonomous maritime systems.