INTERNATIONAL COLLISION REGULATIONS FOR AUTOMATIC COLLISION AVOIDANCE

This thesis considers the relationship between collision regulations and an automatic collision avoidance system (ACAS). Automation of ship operations is increasingly common. The automation of the collision avoidance task may have merit on grounds of reduced manual workload and the elimination of human error. Work to date by engineers and computer programmers has focused on modelling the requirements of the current collision regulations. This thesis takes a new approach and indicates that legislative change is a necessary precursor to the implementation of a fully automatic collision avoidance system. A descriptive analysis has been used to consider the nature of the collision avoidance problem and the nature of rules as a solution. The importance of coordination between vessels is noted and three requirements for coordination are established. These are a mutual perception of: risk, the strategy to be applied, and the point of manoeuvre. The use of rules to achieve coordination are considered. The analysis indicates that the current collision regulations do not provide the means to coordinate vessels. A review of current and future technology that may be applied to the collision avoidance problem has been made. Several ACAS scenarios are contrived. The compatibility of the scenarios and the current collision regulations is considered. It is noted that both machine sensors and processors affect the ability to comply with the rules. The case is made for judicial recognition of a discrete rule-base for the sake of an ACAS. This leads to the prospect of quantified collision regulations for application by mariners. A novel rule-base to match a pm1icular ACAS scenario has been devised. The rules are simple and brief. They avoid inputs dependent on vision and visibility, and meet all the aforementioned coordination requirements. Their application by mariners to two-vessel open sea, encounters was tested on a navigation simulator. The experimental testing of such a rule-base is unique. Mariners were given experience of applying the rule-base in certain circumstances and asked by questionnaire what their agreeable action would be. This was compared with their usual action. While the number of experiments was small, an indication was given of the impm1ant issues in applying a quantified rule-base. Aspects identified for fm1her study include the testing of rule base elements in isolation, and the use of quantified rules in multi-ship and confined water encounters.The Nautical Institut

Collision avoidance for autonomous ship using deep reinforcement learning and prior-knowledge-based approximate representation

Reinforcement learning (RL) has shown superior performance in solving sequential decision problems. In recent years, RL is gradually being used to solve unmanned driving collision avoidance decision-making problems in complex scenarios. However, ships encounter many scenarios, and the differences in scenarios will seriously hinder the application of RL in collision avoidance at sea. Moreover, the iterative speed of trial-and-error learning for RL in multi-ship encounter scenarios is slow. To solve this problem, this study develops a novel intelligent collision avoidance algorithm based on approximate representation reinforcement learning (AR-RL) to realize the collision avoidance of maritime autonomous surface ships (MASS) in a continuous state space environment involving interactive learning capability like a crew in navigation situation. The new algorithm uses an approximate representation model to deal with the optimization of collision avoidance strategies in a dynamic target encounter situation. The model is combined with prior knowledge and International Regulations for Preventing Collisions at Sea (COLREGs) for optimal performance. This is followed by a design of an online solution to a value function approximation model based on gradient descent. This approach can solve the problem of large-scale collision avoidance policy learning in static-dynamic obstacles mixed environment. Finally, algorithm tests were constructed though two scenarios (i.e., the coastal static obstacle environment and the static-dynamic obstacles mixed environment) using Tianjin Port as an example and compared with multiple groups of algorithms. The results show that the algorithm can improve the large-scale learning efficiency of continuous state space of dynamic obstacle environment by approximate representation. At the same time, the MASS can efficiently and safely avoid obstacles enroute to reaching its target destination. It therefore makes significant contributions to ensuring safety at sea in a mixed traffic involving both manned and MASS in near future

Automatic collision avoidance of ships

One of the key elements in automatic simulation of ship manoeuvring in confined waterways is route finding and collision avoidance. This paper presents a new practical method of automatic trajectory planning and collision avoidance based on an artificial potential field and speed vector. Collision prevention regulations and international navigational rules have been incorporated into the algorithm. The algorithm is fairly straightforward and simple to implement, but has been shown to be effective in finding safe paths for all ships concerned in complex situations. The method has been applied to some typical test cases and the results are very encouraging

Model of large scale man-machine systems with an application to vessel traffic control

Mathematical models are discussed to deal with complex large-scale man-machine systems such as vessel (air, road) traffic and process control systems. Only interrelationships between subsystems are assumed. Each subsystem is controlled by a corresponding human operator (HO). Because of the interaction between subsystems, the HO has to estimate the state of all relevant subsystems and the relationships between them, based on which he can decide and react. This nonlinear filter problem is solved by means of both a linearized Kalman filter and an extended Kalman filter (in case state references are unknown and have to be estimated). The general model structure is applied to the concrete problem of vessel traffic control. In addition to the control of each ship, this involves collision avoidance between ship

An Improved Differential Evolution Algorithm for Maritime Collision Avoidance Route Planning

High accuracy navigation and surveillance systems are pivotal to ensure efficient ship route planning and marine safety. Based on existing ship navigation and maritime collision prevention rules, an improved approach for collision avoidance route planning using a differential evolution algorithm was developed. Simulation results show that the algorithm is capable of significantly enhancing the optimized route over current methods. It has the potential to be used as a tool to generate optimal vessel routing in the presence of conflicts

Enhancing AIS to Improve Whale-Ship Collision Avoidance and Maritime Security

Whale-ship strikes are of growing worldwide concern due to the steady growth of commercial shipping. Improving the current situation involves the creation of a communication capability allowing whale position information to be estimated and exchanged among vessels and other observation assets. An early example of such a system has been implemented for the shipping lane approaches to the harbor of Boston, Massachusetts where ship traffic transits areas of the Stellwagen Bank National Marine Sanctuary frequently used by whales. It uses the Automated Identification Systems (AIS) technology, currently required for larger vessels but becoming more common in all classes of vessels. However, we believe the default mode of AIS operation will be inadequate to meet the long-term needs of whale-ship collision avoidance, and will likewise fall short of meeting other current and future marine safety and security communication needs. This paper explores the emerging safety and security needs for vessel communications, and considers the consequences of a communication framework supporting asynchronous messaging that can be used to enhance the basic AIS capability. The options we analyze can be pursued within the AIS standardization process, or independently developed with attention to compatibility with existing AIS systems. Examples are discussed for minimizing ship interactions with Humpback Whales and endangered North Atlantic Right Whales on the east coast, and North Pacific Right Whales, Bowhead Whales, Humpback Whales, Blue Whales and Beluga Whales in west coast, Alaskan and Hawaiian waters

Alternative model-building for the study of socially interactive robots

In this discussion paper, we consider the potential merits of applying an alternative approach to model building (Empirical Modelling, also known as EM) in studying social aspects of human-robot interaction (HRI). The first section of the paper considers issues in modelling for HRI. The second introduces EM principles, outlining their potential application to modelling for HRI and its implications. The final section examines the prospects for applying EM to HRI from a practical perspective with reference to a simple case study and to existing models