Extended Abstract: Supervisory Intelligent Operator/Scheme for optimal shared control authority between human-vessel cooperation for increased autonomy

Abstract

It is challenging to optimize the human-machine control authority allocation for an autonomous marine vessel in general. It is crucial to establish an effective scheme which achieves an optimal coordination between the human operator/crew and the vessel countering any threats to crew or vessel, sensory faults and other hostile operating conditions. An intelligent scheme which in cooperates the potential threats via learning-based modelling which could forecast the restrictions on navigation and control based on redundant sources to execute different level of shared control authority (between a human operator either on-bard or on-shore station and the vessel) with respect to International Maritime Organization (IMO) classification on degrees of autonomy. The scheme systematically constructs a decision-based smooth control allocation based on the potential sensor vulnerabilities (spoofing, interference, GNSS segment errors, jamming, scintillation, solar activity etc.,) and the factors of human-error which causes collision as per the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). Hence, this paper presents a scheme that establishes a topology for shared control authority for marine vessels considering the fact that still standards and regulations regarding marine autonomy still lack clarity and evolving. Hence, this would facilitate integration of existing Collision Avoidance Systems with an intelligent operator which regulates the intervention of human-operator in the loop for increased autonomy, safety and optimal cooperation.