Human-autonomy collaboration in supervisory risk control of autonomous ships

This paper presents a method for developing and testing a risk-based control system, as a first step towards including the human supervisor explicitly in the design of the system. The result is a control system with improved decision-making capabilities compared to existing control systems. The methodology presented in the paper uses the Systems Theoretic Process Analysis (STPA) to analyse the risks of an autonomous ship within its concept of operations (CONOPS), and a Human-STPA (H-STPA) is used to analyse human responsibilities and involvement. The STPA results are then used to construct a Bayesian belief network (BBN)-based risk model to assess the operational risk of the ship. This is represented as a risk cost, describing the expected cost of consequences caused by potential hazardous events. This cost is combined with fuel costs, operations costs, and the potential loss of income if new missions are not undertaken using a supervisory risk controller (SRC). The SRC is capable of making decisions about how the ship should be safely operated and notifies the human supervisor in due time when it is necessary for them to take control. The last part of the methodology presented in this paper is testing the control system using a set of verification objectives based on results from the STPA and H-STPA. A case study involving an autonomous cargo ship with a human supervisor located in a remote operation center (ROC) is included; it shows that the proposed control system can operate the ship safely in different conditions and situations. By designing the SRC to notify the human supervisor before it reaches its operational limit, the ship is able to operate in a wider range of conditions compared to when just the autonomous control system is in charge. Hence, the proposed methodology shows promising results and provides useful insights related to shared control for autonomous ships.

本文提出了一种开发与测试基于风险的控制系统的方法，作为将人类监管者明确纳入系统设计的第一步。相较于现有控制系统，所得到的控制系统具备更优异的决策能力。本文所提出的方法论采用系统理论过程分析（Systems Theoretic Process Analysis, STPA）对自主船舶在其运行概念（concept of operations, CONOPS）范围内的风险进行分析，并借助人机协同系统理论过程分析（Human-STPA, H-STPA）剖析人类的职责与参与环节。随后将STPA的分析结果用于构建基于贝叶斯置信网络（Bayesian belief network, BBN）的风险模型，以评估该船舶的运行风险，该风险以风险成本的形式呈现，用于描述潜在危险事件所引发后果的期望损失成本。该成本与燃油成本、运营成本，以及因未执行新任务可能产生的潜在收入损失，通过监督风险控制器（supervisory risk controller, SRC）进行整合。SRC可针对船舶的安全运行方式作出决策，并在需要人类监管者介入时及时发出通知。本文所提出方法论的最后一环，是基于STPA与H-STPA的结果设定一组验证目标，以此对控制系统开展测试。本文附带一项案例研究，对象为搭载远程操作中心（remote operation center, ROC）人类监管者的自主货船，结果表明所提出的控制系统可在不同工况与场景下安全操控船舶。通过将SRC设计为在达到运行极限前向人类监管者发出警报，该船舶可在比仅启用自主控制系统时更广泛的工况范围内运行。综上，本文所提出的方法论取得了颇具前景的研究成果，可为自主船舶的协同控制提供具有参考价值的见解。