Deep Learning Toward Autonomous Ship Navigation and Possible COLREGs Failures

Abstract

A structured technology framework to address navigation considerations, including collision avoidance, of autonomous ships is the focus of this study. That consists of adequate maritime technologies to achieve the required level of navigation integrity in ocean autonomy. Since decision-making facilities in future autonomous vessels can play an important role under ocean autonomy, these technologies should consist of adequate system intelligence. Such system intelligence should consider localized decision-making modules to facilitate a distributed intelligence type strategy that supports distinct navigation situations in future vessels as agent-based systems. The main core of this agent consists of deep learning type technology that has presented promising results in other transportation systems, i.e., self-driving cars. Deep learning can capture helmsman behavior; therefore, such system intelligence can be used to navigate future autonomous vessels. Furthermore, an additional decision support layer should also be developed to facilitate deep learning-type technologies, where adequate solutions to distinct navigation situations can be facilitated. Collision avoidance under situation awareness, as one of such distinct navigation situations (i.e., a module of the decision support layer), is extensively discussed. Ship collision avoidance is regulated by the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) under open sea areas. Hence, a general overview of the COLREGs and its implementation challenges, i.e., possible regulatory failures, under situation awareness of autonomous ships is also presented with the possible solutions. Additional considerations, i.e., performance standards with the applicable limits of liability, terms, expectations, and conditions, toward evaluating ship behavior as an agent-based system in collision avoidance situations are also illustrated.

Towards Autonomous Shipping: Benefits and Challenges in the Field of Information Technology and Telecommunication

“…Weather conditions affect the ship's safety and its ability to follow the route. Taking the weather into account not only helps to avoid negative effects on the ship [35,41] but also reduces the economical costs of a voyage by reducing the travel time and fuel consumption [16,43]. Therefore, the ability to take weather conditions into account is essential for the route planning system [17,23,38].…”

“…Planning a route for a ship is a complex task that requires attention to many factors affecting routes safety and optimality. The navigators plan routes using their experience and background [35]. Building this experience into a formal route planning algorithm like A* or Dijkstra's is a difficult task.…”

“…It also needs to be predictable and its output needs to be interpretable. That is why designing such an algorithm requires extensive testing and verification [35]. Formal algorithms like A* or Dijkstra's are proven to be able to find the best solution but they pose strong requirements for the environment and the input data [11].…”

“…Therefore, smart ships are expected to have some degree of autonomy to make them able to operate amid the absence of connection with the control centre. It is expected that an autonomous ship can also be controlled remotely, therefore there can be stages of fully autonomous operation and remotely controlled stages within a single voyage [35]. Remote control stages may be required to navigate the ship in the most dangerous or difficult circumstances, e.g.…”

“…This paper is dedicated to the challenges in the field of information technology and telecommunication with regard to smart and autonomous ships. It is expected that the success in these fields will significantly affect the maritime industry as being the most important milestone in the journey towards autonomous shipping [35].…”