Automated maritime collision avoidance will rely on human supervision for the foreseeable future. This necessitates transparency into how the system perceives a scenario and plans a maneuver. However, the causal logic behind avoidance maneuvers is often complex and difficult to convey to a navigator. This paper explores how to explain these factors in a selective, understandable manner for supervisors with a nautical background. We propose a method for generating contrastive explanations, which provide human-centric insights by comparing a system's proposed solution against relevant alternatives. To evaluate this, we developed a framework that uses visual and textual cues to highlight key objectives from a state-of-the-art collision avoidance system. An exploratory user study with four experienced marine officers suggests that contrastive explanations support the understanding of the system's objectives. However, our findings also reveal that while these explanations are highly valuable in complex multi-vessel encounters, they can increase cognitive workload, suggesting that future maritime interfaces may benefit most from demand-driven or scenario-specific explanation strategies.

翻译：在可预见的未来，自动化的海上避碰仍将依赖人类监督。这要求系统在感知场景和规划机动时具备透明度。然而，避碰机动背后的因果逻辑往往复杂且难以向航海员传达。本文探讨了如何以选择性、可理解的方式向具有航海背景的监督者解释这些因素。我们提出了一种生成对比解释的方法，通过将系统提出的解决方案与相关备选方案进行对比，提供以人为中心的洞察。为评估该方法，我们开发了一个框架，利用视觉和文本线索突出显示最先进避碰系统的关键目标。一项与四位资深海事官员进行的探索性用户研究表明，对比解释有助于理解系统的目标。然而，我们的发现也揭示，尽管这些解释在复杂的多船遭遇场景中极具价值，但它们可能增加认知负荷，这表明未来的海上界面可能更受益于需求驱动或场景特定的解释策略。