scholarly journals Deep Learning Toward Autonomous Ship Navigation and Possible COLREGs Failures

Author(s):  
Lokukaluge P. Perera

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.

Author(s):  
Lokukaluge P. Perera

A general framework to support the navigation side of autonomous ships is discussed in this study. That consists of various maritime technologies to achieve the required level of ocean autonomy. Decision-making processes in autonomous vessels will play an important role under such ocean autonomy, therefore the same technologies should consist of adequate system intelligence. Each onboard application in autonomous vessels may require localized decision-making modules, therefore that will introduce a distributed intelligence type strategy. Hence, future ships will be agent-based systems with distributed intelligence throughout vessels. The main core of this agent should consist 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 that type system intelligence can be used to navigate autonomous vessels. Furthermore, an additional decision support layer should also be developed to facilitate deep learning type technology including situation awareness and collision avoidance. Ship collision avoidance is regulated by the Convention on the International Regulations for Preventing Collisions at Sea, 1972 (COLREGs) under open sea areas. Hence, a general overview of the COLREGs and its implementation challenges, i.e. regulatory failures and violations, under autonomous ships are also discussed with the possible solutions as the main contribution of this study. Furthermore, additional considerations, i.e. performance standards with the applicable limits of liability, terms, expectations and conditions, towards evaluating ship behavior as an agent-based system on collision avoidance situations are also illustrated in this study.


Author(s):  
A. V. Smirnov ◽  
T. V. Levashova

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.


Author(s):  
Raj Veeramani ◽  
Narayanan Viswanathan ◽  
Shailesh M. Joshi

Abstract New approaches for decision making are emerging to support the use of the Internet for supply-web interactions in the manufacturing industry. In this paper, we discuss one such paradigm, namely similarity-based decision support. It recognizes that knowledge of similar experiences can support rapid and effective decision making in various forms of supply-web interactions. We illustrate this approach using two prototype systems, WebScout (an agent-based system for customer–supplier matchmaking in the job-shop machining industry context) and TOME (Treasury of Manufacturing Experiences — an Intranet application to aid manufacturability assessment in foundries).


2009 ◽  
Vol 5 (4) ◽  
pp. 53-70 ◽  
Author(s):  
Stephen Russell ◽  
Victoria Y. Yoon

Despite the importance of resource availability, the inclusion of availability awareness in current agent-based systems is limited, particularly in decision support settings. This article discusses issues related to availability awareness in agent-based systems and proposes that knowledge of resources’ online status and readiness in these systems can improve decision outcomes. A conceptual model for incorporating availability and presence awareness in an agent-based system is presented, and an implementation framework operationalizing the conceptual model using JADE is proposed. Finally, the framework is developed as an agent-based decision support system (DSS) and evaluated in a decision making simulation.


2013 ◽  
Vol 816-817 ◽  
pp. 1220-1224
Author(s):  
Shou Cai Ma

This paper deeply analyzes the urban civil system, energy-saving decision-making mechanism, the system components and the related energy-saving anti-adjustment mechanism based on the proposed energy-saving urban civil system's basis. It also presents the classification decision-making and decision-making process for the civil on various components on building systems in decision-making energy-saving features on the system proposed civil heat, urban heating network and the energy saving civil monomer decision making. It also builds the decision support for the city civil agent-based energy-saving system, realizing the basic institutions of the agent to propose the energy-saving urban civil decision.


Author(s):  
David J. Bryant ◽  
David G. Smith

Objective: We examined the effectiveness of blue force tracking (BFT) decision support for dismounted infantry soldiers. Background: Technologies to support combat identification (CID) are rapidly evolving and may be deployable to dismounted soldiers in the future. BFT systems are designed to mitigate the risk of fratricide by supplying positional information regarding friendly units to enhance situation awareness. Method: Participants played the role of a dismounted infantry soldier in a first-person perspective gaming environment and made engagement decisions for a series of simulated targets, half of which were enemies and half of which were friends. Results: Participants performed better overall when they were able to use a BFT system than when they performed the task without assistance. When a 10-s latency was added to the updating of position information in the BFT, participants made significantly more false alarms (engaged a friendly target) regardless of whether they knew about the latency. Conclusion: The results indicate the promise of a personal BFT device to reduce the likelihood of fratricide by dismounted infantry soldiers. The results, however, also indicate that the effectiveness of such a device can be dramatically reduced when it does not provide real-time data. Application: Potential applications of this research include development of performance standards for BFT devices and assessment of decision support for dismounted soldiers.


2020 ◽  
Vol 8 (9) ◽  
pp. 640
Author(s):  
Yingjun Hu ◽  
Anmin Zhang ◽  
Wuliu Tian ◽  
Jinfen Zhang ◽  
Zebei Hou

Most maritime accidents are caused by human errors or failures. Providing early warning and decision support to the officer on watch (OOW) is one of the primary issues to reduce such errors and failures. In this paper, a quantitative real-time multi-ship collision risk analysis and collision avoidance decision-making model is proposed. Firstly, a multi-ship real-time collision risk analysis system was established under the overall requirements of the International Code for Collision Avoidance at Sea (COLREGs) and good seamanship, based on five collision risk influencing factors. Then, the fuzzy logic method is used to calculate the collision risk and analyze these elements in real time. Finally, decisions on changing course or changing speed are made to avoid collision. The results of collision avoidance decisions made at different collision risk thresholds are compared in a series of simulations. The results reflect that the multi-ship collision avoidance decision problem can be well-resolved using the proposed multi-ship collision risk evaluation method. In particular, the model can also make correct decisions when the collision risk thresholds of ships in the same scenario are different. The model can provide a good collision risk warning and decision support for the OOW in real-time mode.


2016 ◽  
Vol 69 (5) ◽  
pp. 1154-1182 ◽  
Author(s):  
Dagfinn Husjord

This paper focusses on the development of a tool for decision-making, tailored for personnel involved in complex Ship-To-Ship (STS) operations, to enhance the efficiency and safety of these operations. A step-wise approach has been selected. The first step includes specification, development and testing of the tool in a simulated work environment using full-mission simulators. In the second step the findings from application of the tool in the simulated work environment will be used to develop a prototype which will be tested during real life STS operations. This paper describes work done in the first of these two steps. During four iterations, a Graphical User Interface (GUI) has been made following Interaction Design (IxD) principles. The designs have been iteratively developed and tested by experienced ship's officers in a ship-handling simulator to clarify key information to enhance their Situation Awareness (SA) and decision-making process. In order to find indicators for performance, an initial performance test was carried out in a ship-handling simulator. The test indicates that a logic based Decision-Support System (DSS) can improve existing simulator-based training activities in STS operations.


2019 ◽  
Vol 25 (3) ◽  
pp. 81-90
Author(s):  
Ariane Bitoun ◽  
Hans ten Bergen ◽  
Yann Prudent

Abstract While serious games are being widely adopted by NATO and partner nations, their use is currently limited to training and operations planning. In this paper, we explore new methods that use simulations for decision support during the execution of military operations. During this phase, the commander makes decisions based on knowledge of the situation and the primary objectives. We propose here to take a simulation containing smart and autonomous units, and use it to create new kinds of decision support tools capable of improving situation awareness, and consequently the quality of decisions. The breakthrough behind this initiative is the realization that we can provide HQ decision makers with access to a version of the information that smart simulated units use to make decisions. To ensure the approach was sound we first studied decision-making processes, and analyzed how situation awareness improves decision-making. After analysis of the decision-making processes at various headquarters, and the types of decision criteria employed, we are able to produce innovative information, computed by the simulation, and fed by the command and control system. We then propose a prerequisite architecture and describe the first results of our proof of concept work based on the SWORD (Simulation War gaming for Operational Research and Doctrine) simulation.


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