用对比解释让航海员看懂自动驾驶船的避碰决策。
"Why This Avoidance Maneuver?" Contrastive Explanations in Human-Supervised Maritime Autonomous Navigation
- 通过对比方案解释系统决策逻辑，突出关键目标。
- 专家测试显示解释提升复杂场景理解力。
- 适合经验丰富的航海员，但需控制认知负荷。
自动化海上避碰系统在可预见未来仍需人工监督，因此必须透明展示系统如何感知场景并规划规避动作。然而，避碰决策背后的因果逻辑往往复杂难懂。本文提出一种生成对比解释的方法，通过比较系统方案与相关替代方案，为具有航海背景的监督者提供以人为本的洞察。为此，我们构建了一个框架，利用视觉与文本线索突出先进避碰系统的关键目标。一项包含四位资深海事军官的探索性用户研究显示，对比解释有助于理解系统目标。但研究也发现，尽管在多船复杂场景中价值显著，这类解释可能增加认知负担，提示未来海上人机界面应采用按需或场景定制的解释策略。
原文摘要 · Abstract (English)
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.
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