"Why This Avoidance Maneuver?" Contrastive Explanations in Human-Supervised Maritime Autonomous Navigation
Joel Jose, Andreas Madsen, Andreas Brandsæter, Tor A. Johansen, Erlend M. Coates
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
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.
关键词
相关论文
一种面向线弧增材制造的电动汽车结构可制造性拓扑优化的双环框架
Qiang Cui, Chuan Yu, Daoqian Yang 等 5 位作者
Robotics and Computer-Integrated Manufacturing · 2026
几何数字孪生:一种用于航空发动机装配精度预测的数字智能模型
Ke Shang, Xin Jin, Teli Xu 等 7 位作者
Robotics and Computer-Integrated Manufacturing · 2026
通过人工智能驱动的机器人技术革新产业
Aryan Chaudhary
Recent Advances in Computer Science and Communications · 2026
新型大口径偏置馈电可展开天线设计与动态性能预测
Chuang Shi, Tianming Liu, Ning Xue 等 9 位作者
Aerospace Science and Technology · 2026