Lokukaluge P. Perera

Maritime Traffic Monitoring Based on Vessel Detection, Tracking, State Estimation, and Trajectory Prediction

Maneuvering vessel detection and tracking (VDT), incorporated with state estimation and trajectory prediction, are important tasks for vessel navigational systems (VNSs), as well as vessel traffic monitoring and information systems (VTMISs) to improve maritime safety and security in ocean navigation. Although conventional VNSs and VTMISs are equipped with maritime surveillance systems for the same purpose, intelligent capabilities for vessel detection, tracking, state estimation, and navigational trajectory prediction are underdeveloped. Therefore, the integration of intelligent features into VTMISs is proposed in this paper. The first part of this paper is focused on detecting and tracking of a multiple-vessel situation. An artificial neural network (ANN) is proposed as the mechanism for detecting and tracking multiple vessels. In the second part of this paper, vessel state estimation and navigational trajectory prediction of a single-vessel situation are considered. An extended Kalman filter (EKF) is proposed for the estimation of vessel states and further used for the prediction of vessel trajectories. Finally, the proposed VTMIS is simulated, and successful simulation results are presented in this paper.

Intelligent Ocean Navigation and Fuzzy-Bayesian Decision/Action Formulation

This paper focuses on the formulation of a decision-action execution model that can facilitate intelligent collision avoidance features in ocean navigation systems, while respecting the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) rules and regulations of collision avoidance. The decision/action process in this work consists of a fuzzy-logic-based parallel decision-making (PDM) module whose decisions are formulated into sequential actions by a Bayesian-network-based module. Therefore, the paper presents a collision avoidance system (CAS) that is capable of making multiple parallel collision avoidance decisions regarding several target vessel collision conditions, and those decisions are executed as sequential actions to avoid complex collision situations in ocean navigation.

Experimental Evaluations on Ship Autonomous Navigation and Collision Avoidance by Intelligent Guidance

Experimental evaluations on autonomous navigation and collision avoidance of ship maneuvers by intelligent guidance are presented in this paper. These ship maneuvers are conducted on an experimental setup that consists of a navigation and control platform and a vessel model, in which the mathematical formulation presented is actually implemented. The mathematical formulation of the experimental setup is presented under three main sections: vessel traffic monitoring and information system, collision avoidance system, and vessel control system. The physical system of the experimental setup is presented under two main sections: vessel model and navigation and control platform. The vessel model consists of a scaled ship that has been used in this study. The navigation and control platform has been used to control the vessel model and that has been further divided under two sections: hardware structure and software architecture. Therefore, the physical system has been used to conduct ship maneuvers in autonomous navigation and collision avoidance experiments. Finally, several collision avoidance situations with two vessels are considered in this study. The vessel model is considered as the vessel (i.e., own vessel) that makes collision avoidance decisions/actions and the second vessel (i.e., target vessel) that does not take any collision avoidance actions is simulated. Finally, successful experimental results on several collision avoidance situations with two vessels are also presented in this study.

Evaluations on Ship Performance Under Varying Operational Conditions

Various emission control measures have been introduced in the recent years for improving vessel performance in the shipping industry. That consists of: Energy Efficiency Design Index (EEDI) for new ships and Ship Energy Efficiency Management Plan (SEEMP) and Energy Efficiency Operational Indicator (EEOI) for all ships. These emission control measures enforce the shipping industry to improve operational conditions and to implement modern technology for more energy efficient shipping fleets. Therefore, this study presents preliminary data analysis of a selected vessel for monitoring its performance along the ship routes. The results consist of observing vessel performance under several navigation parameters: ship GPS speed (i.e. speed over the ground), log speed, course, fuel consumption, main and auxiliary engine power, main engine shaft RPM, loading and draft conditions with respect to the route, voyage time and wind conditions. Furthermore, these parameters have been used to analyze potential and optimal energy usage situations in ship navigation with respect to the EEOI, in which represents an important part of the SEEMP.Copyright

A Navigation and Control Platform for Real-Time Manoeuvring of Autonomous Ship Models

Abstract The development of a control and navigation platform for an autonomous surface vessel (ASV) being a scaled self-propelled model of a real ship is presented in this paper. The overall system is described under the hardware structure and the software architecture. The system hardware structure is further divided into the command and monitoring unit (CMU) and the communication and control unit (CCU). The ashore based CMU is used to control the ASV through a wireless Ethernet communication; the ASV mainly consists of the on-board CCU. The system software architecture mainly consists of several software loops for collecting the sensor data and controlling the rudder and propeller actuations. Furthermore, a touch panel as the human machine interface (HMI) is used for autonomous and manual control of the ASV has been implemented. Finally, the future experimental implementations of the ASV are discussed in this paper.

Bayesian Network based sequential collision avoidance action execution for an Ocean Navigational System

This paper focuses on a study of the sequential action execution module for a collision avoidance system in ocean navigation. The overall decision-action process of collision avoidance consists on a Fuzzy logic based parallel decision making module and those decisions are formulated into collision avoidance actions by a Bayesian network based sequential action execution module. The presented collision avoidance system is capable of making multiple sequential actions to avoid complicated collision situations involving multiple vessels in ocean navigation while still respecting the COLREGs rules and regulations.

System Identification of Nonlinear Vessel Steering

In this paper, the stochastic parameters describing a nonlinear ocean vessel steering model are identified, resorting to an extended Kalman filter (EKF). The proposed method is applied to a second-order modified Nomoto model for vessel steering and that is derived from first physics principles. Furthermore, the results obtained resorting to a realistic numerical simulator of nonlinear vessel steering are also illustrated in this study. [DOI: 10.1115/1.4029826]

Solutions to the Failures and Limitations of Mamdani Fuzzy Inference in Ship Navigation

This paper proposes a methodology for overcoming Mamdani-type inference failures on a fuzzy-logic-based decision-making process applied to collision avoidance in ship navigation. The fuzzy inference failures are observed in three distinct situations: 1) intersected contradictory decision boundaries; 2) an improper transition region between the inference boundaries of nonintersected contradictory decisions; and 3) contradictory decision accumulation under multiple obstacle scenarios. The solutions for overcoming these fuzzy inference failures and their limitations are also discussed in this paper. The proposed solutions consist of insertion of smooth transition regions, determination of the proper size of the smooth transition regions, and use of multilevel decision/action formulations. Furthermore, this paper analyzes a decision-making process for ship navigation, derives input and output fuzzy membership functions (FMFs), formulates an if-then-rule-based fuzzy inference system (FIS), and presents simulation results that support recovery from rule inference failures in several contradictory decision boundary conditions.

Vector-product based Collision Estimation and Detection in e-Navigation

Abstract This study focuses on the formulation of collision detection facilities among vessels that can be integrated into an e-Navigation strategy in maritime transportation. The detection of potential collision situations by relative motions of vessels that consist of state and parameter uncertainties in vessel maneuvering is considered in this study. A two vessel collision situation is presented and an extended Kalman filter is used to estimate the relative bearing and relative course-speed vectors between vessels. The collision detection process consists of cross and dot products among vessel velocity, bearing and heading vectors. Finally, a collision/near-collision situation is simulated and successful results on the detection of a potential collision situation with respect to vessel maneuvering are illustrated in this study.

Fuzzy-Logic Based Parallel Collisions Avoidance Decision Formulation for an Ocean Navigational System

This paper focuses on a Fuzzy-logic based parallel decision formulation that aims to improve the safety of marine vessels by avoiding collision situations in ocean navigation. The collision avoidance of the Target vessel with respect to the vessel domain of the Own vessel has been analyzed and input and output Fuzzy Membership Functions are derived in this study. The If-Then rule based decision making process and the integrated novel Fuzzy Inference System are formulated and implemented on MATLAB software platform. Simulations are presented regarding several collision avoidance situations. Furthermore, the decision rules are formulated in accordance with the International Maritime Organization Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) and expert knowledge in navigation, to avoid conflict that might occur during the ocean navigation.