Autonomous collision avoidance system for unmanned vessels: algorithms and software.


Ship collision is one of the most substantial concerns in the global maritime transportation industry. Hence, navigation safety is considerably cited topic in maritime literature. Recently, Unmanned Navigation (UN) technology is gradually becoming more widely used across in the field of marine robotics. The paper investigates the problem of navigation safety in the movement control of Unmanned Vessels (UVs). The object of the study is the process of avoiding collisions of UVs. The subject of the research is the algorithms of the autonomous decision-making system and software for preventing vessel collisions during UN. The intent of this article is to improve the safety of UN by developing new Decision-Making algorithms for autonomous collision prevention of UVs in real time, taking into account the International Rules for the Prevention of Collisions at Sea, 1972 (COLREGs-72) and the recommendations of the Federal agency for sea and inland water transport of the Russian Federation (Rosmorrechflot).In this article, the fundamental concept and the key functions set of the Autonomous Collision Avoidance System (ACAS) are carried out for UVs which are marine transport vehicles capable of sensing its environment and operating without human involvement. Along this line of research, this work focuses on the development of a software algorithm for determining the most dangerous obstacle located within a radius of 12 miles (recommendations of Rosmorrechflot) around an UV based on the principle of vessels collision avoidance geometry, collision risk assessment and the characteristics of obstacles. Moreover, the proposed algorithms can prevent the collision and address the issues of real-time collision avoidance for UVs. The simulation results also demonstrate the promising application of the proposed algorithms in studying the UN safety. Nonetheless, this study provides a way forward to conduct a new information decision-making system design for UVs collision avoidance. This is currently under development, and will be proposed later.

Full Text

Improving the marine navigation and safety of sea transportation are a complex multi-level tasks, which are provided by the work of the International Maritime Organization (IMO), ship classification societies and administrations of governments involved in the development of world navigation. Analyzing vessel accidents, it can be noted that ship collisions, in particular, are one of the most common types of sea traffic accidents. Collision of vessels is the name given to an incident that occurred as a result of mutual contact between a vessel and another object during its movement and entailed loss of life or injuries, damage to the vessels and cargo, environmental pollution or other material damage.According to official data from the Federal service for supervision of transport of the Rus-sian Federation (Rostransnadzor), in the period from 2014 to 2020 collisions of vessels flying the State flag of the Russian Federation represent respectively 4.5 %, 1.4 %, 3.66 %, 7.14 %, 8.74 %, 3 % and 11.67 % of the total the number of accidents at sea. And also, were equal to 6.25 %, 11.83 %, 8.6 %, 8 %, 9.5 %, 6.3 % and 3.6 %, respectively, of the total accident rate on the inland waterways transport of the Russian Federation [1]. According to statistics overview annually is-sued by European Maritime Safety Agency (EMSA), over the 2014-2020 period, ship collisions represented 21.7 % of all casualty events [2]. When analyzing underlying factors leading to mari-time accidents, safety investigations determined that 70% of safety investigations were related to “Human Factor” [3].Enhancement of navigational safety in the world merchant fleet is carried out through a number of technical, organizational, economic, environmental and legal standards aimed at pre-venting the occurrence of casualty events, saving human life at sea and reducing environmental risks. In order to reduce or eliminate the need for human involvement in ship control systems and promote navigation safety in the maritime transport sector, Artificial Intelligence (AI) technology based on Machine Learning (ML) methods is being increasingly integrated into maritime transpor-tation industry to create and implement the technology of Unmanned Navigation (UN), providing a reduction of the ship's operational costs, reduction in the ship crew size or complete elimination of the ship crew and a decrease in environmental impacts from direct emissions.Recently, the technology of UN has become a widely discussed topic and one of the fastest growing field of maritime shipbuilding and marine robotics. Furthermore, techniques and meth-ods of ML effectively addressed challenges of ensuring safe remote control of transport vehicles and intellectualization of complex systems. Taking this background into consideration, the devel-opment of an algorithm for the autonomous vessel collision avoidance system (ACAS) in UN is a new trend in the maritime sector and coming out of the growing field of marine robotics.

About the authors

L. A. Barakat

Astrakhan State Technical University

I. Y. Kvyatkovskaya

Astrakhan State Technical University


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