COLREGs-Coverage in Collision Avoidance Approaches: Review and Identification of Solutions

Transcription

1 COLREGs-Coverage in Collision Avoidance Approaches: Review and Identification of Solutions Mazen Salous *, Axel Hahn**, Christian Denker * * OFFIS e.v. Institute for Information Technology Escherweg, 2, Oldenburg, Germany firstname.lastname@offis.de ** University of Oldenburg Department for Informatics Ammerländer Heerstraße 114, Oldenburg, Germany axel.hahn@uni-oldenburg.de Abstract: The count of maritime collisions increases yearly even with using assistant technologies like Automatic Radar Plotting Aid (ARPA) and Automatic Identification System (AIS). Several approaches for collision avoidance have been introduced in the maritime domain to improve maritime safety. In addition to purely physical aids to navigation (e.g. lighthouses and buoys), information and communication technology have evolved. This paper describes a literature review on the state of the art in maritime collision avoidance systems for checking their COLREGs-coverage in all situations mentioned in COLREGs such as conduct of vessels in sight of one another and in restricted visibility. Gaps are identified and solutions are proposed. A structured review is discussed in this paper to address each COLREGs rule/set of rules and to present approaches, methods and techniques considering the corresponding rule(s). On the basis of the review, the coverage of rules is shown. The rules not addressed by the state of the art collision avoidance approaches, i.e. parts C (Lights and Shapes) & D (Sound and Light Signals) rules, are analyzed and an automatic recognition concept of sound/light signals is proposed. 1. Introduction International shipping plays an essential role in the world trade. Its global character requires global regulations to be applied to all ships [1]. One of the standards of global regulations is called The International Regulations for Preventing Collisions at Sea, shortly COLREGs [2]. COLREGs define different rules considering several issues ranging from the lights and sound appliances a vessel is required to carry, to which course of action a vessel should follow when encountering other vessels at sea. COLREGs were adopted first as a convention of the International Maritime Organization on 20 October 1972 and entered into force on 15 July Since that time, many amendments on COLREGs have been adopted and entered into force [3] to make them more convenient for collision avoidance. This paper checks the compliance to COLREGs as a major requirement of maritime collision avoidance systems. For that, it reviews maritime collision avoidance approaches to check how different rules in COLREGs are addressed in each approach. The analyzed collision avoidance approaches use several data sources (e.g. AIS, Radar) and several technologies (e.g. fuzzy logic, neural networks, etc.). The common property between all analyzed approaches is that COLREGs parts A & B, which are directly related to collision avoidance, are addressed either explicitly or implicitly, whereas parts C & D, which are about light, shapes and sounds, are not addressed. This paper proposes a concept of automatic recognition

2 of sound/light signals, described in COLREGs part C & D, as an additional data source which makes sense especially when e.g. AIS is absent. After this general introduction, the rest of the paper is structured as follows. The COLREGscoverage requirements for maritime collision avoidance systems are discussed in the next section. After that, several approaches of maritime collision avoidance are discussed according to their COLREGs-coverage. As a discussion, the paper proposes future solutions based on automatic recognition of sound/light signals of COLREGs parts C & D. Finally, the paper sketches an idea how the situational awareness is improved by considering the COLREGs parts C & D by two examples. 2. COLREG Requirements for Collision Avoidance Systems Maritime collision avoidance systems have to or are highly recommended to comply with COLREGs as international standard maritime traffic regulations. Therefore, as a main requirement is handling of COLREGs. In this section, the COLREGs-coverage requirements for maritime collision avoidance systems are defined. The coverage of COLREGs in the analyzed collision avoidance approaches is discussed then in section 3 accordingly. COLREGs include 38 rules that have been divided into Part A (General), Part B (Steering and Sailing),Part C (Lights and Shapes), Part D (Sound and Light signals), and Part E (Exemptions) [2]. There are general rules in COLREGs like application rules and definitions. These general rules are less important when extracting requirements. Other rules discuss several important and relevant to collision avoidance issues, from which requirements of collision avoidance systems can be defined. Thus, analyzing such issues discussed in COLREGs leads to extract a requirement from the corresponding rule (e.g. proceeding at safe speed from rule 6) and common requirements from multiple rules (e.g. Alerting for critical situations). a) Maintaining Look-out: (Part B, Section I, Rule 5: Look-out) A navigation system should maintain a proper look-out by all available sensors (e.g. Radar and AIS) to improve the crew s situational awareness. b) Proceeding at safe speed: (Part B, Section I, Rule 6: Safe-Speed) A collision avoidance system should suggest a safe speed so that the vessel can take proper and effective action to avoid collision. The factors of defining such a safe speed are discussed in rule 6. c) Detection of risk of collision: (Part B, Section I, Rule 7: Risk of collision (d)) A collision avoidance system should be able to detect a risk of collision. Rule (7) discusses the assessment of risk of collisions in point (d). According to the rule, a system should assume that a risk of collision exists when the bearing of an approaching vessel does not appreciably change, or when approaching a very large vessel or a tow etc. d) Alerting for critical situations: (Parts B, C, and D) This is a typical requirement for collision avoidance systems. Several alarms and warnings can be defined from COLREGs, e.g. approaching a bend in narrow channel (rule 9 Part B), critical approaching of termination of traffic separation scheme (TSS, Rule 10 Part B), encounter alarms (decision of give-way and stand-on vessels) for overtaking, head-on and crossing (Part B Section II). More advanced Info/Alarms might be issued by collision avoidance systems by automatic recognition of sound/light signals issued by other vessels and mentioned in Parts C & D (Examples for such automatic recognition of COLREGs sound/light signals are explained in section 5). There are of course many other requirements for maritime collision avoidance systems (as safety critical systems) such as real time processing requirements (fast reasoning [6]), user friendly Graphical User Interface GUI and intelligent alarming (i.e. to facilitate all available data sources and visualize the relevant data in useful alarms, marine data visualization [7]).

3 However, since the scope of this paper is to check the COLREGs coverage in collision avoidance approaches, this paper does not discuss such requirements, but focuses on the consideration of COLREGs in different collision avoidance approaches. 3. COLREGs-Coverage in the State of The Art of Maritime Collision Avoidance Approaches This section introduces the approaches of Collision Avoidance and discusses COLREGscoverage (defined in section 2). The authors reviewed maritime collision avoidance approaches from review papers ([11], [12]). In addition, the authors analyzed collision avoidance approaches from an own literature survey [40-42] whose technologies and concepts are not categorized by [11] and [12] as we also did in the following sections Thus, the approaches [40-42] are discussed in section 3.7 as other technologies. In total, we reviewed 30 approaches [13-42]. We discuss them in several categories according to their technologies and concepts. 3.1 COLREGs-Coverage in Fuzzy Theory based Collision Avoidance Approaches [13-17] According to [12], fuzzy approaches based navigation systems have been adopted to overcome the non-linear and ill-defined systems formed typically by ships. Moreover, even if precise mathematical models for an autonomous system exist, the time for the decision making of the system will potentially not be reasonable for a real-time application [12,32]. The design process of a fuzzy logic based Decision Making system begins with defining fuzzy linguistics (e.g. for Risk: Low, Mid and High), then to define inputs and outputs (e.g. inputs: DCPA, relative bearing, etc. and outputs: course change, speed change, etc.), followed by selection of suitable fuzzy membership functions for inputs and outputs (e.g. Gaussian function) and in the end to define the fuzzy rules to be appied in making decisions. We identified James [13], Smeaton et al [14], Lee et al [15], Hwang et al [16] and Perera [17] use fuyyz logic approach in collision avoidance. For COLREGs-coverage requirements (recall section 2 from (a) maintaining look-out till (d) alerting for critical situations), James [13] quantified COLREGSs' concepts like safe passing distance and early action which are mentioned in COLREGs parts A & B. Thus, this approach aims at offering perspective guidelines for mariners in accordance with COLREGs parts A & B. James s approach does not discuss requirement (a), and it addresses (b), (c) and (d) but partially (e.g. COLREGs parts B-III, C & D are not addressed) and implicitly (e.g. safe speed factors in rule 6 are not discussed explicitly). Similarly, Smeaton et al [14] utilized part B in COLREGs as a foundation of his approach. Smeaton used fixed values for processing e.g. DCPA of 500 m to specify a collision course (requirements (c) and (d)) regardless of ship type and maneuverability. Lee et al [15] and Hwang et al [16] depended also on TCPA/DCPA as quantifying concepts to determine a risk of collision complying implicitly with the rule 7; however, bearing change which is discussed in rule 7 as a determining factor of risk of collision is not addressed. A more comprehensive approach has been introduced by Perera [17], in which he addressed COLREGs parts A & B similarly to above approaches but more comprehensively that he addressed the responsibilities of stand-on vessels (rules 17) in case of absence of proper actions from the give-way vessel. It s noticeable that the specific rules of narrow channel (rule 9) and traffic separation scheme (TSS) (rule 10) and parts B-III, C & D are not discussed in all fuzzy theory based approaches. 3.2 COLREGs-Coverage in Knowledge Base based Collision Avoidance Approaches [18-21]

4 Since the main task of a maritime navigation system is to assist the navigator in the decision making process, and given that Knowledge Bases can be used as core parts of such decision making systems, we identified Iijima et al [18], Coenen et al [19], Banas et al [20] and Breitsprecher [21] try to interpret COLREGS as a Knowledge Base (KB) to be used for decision making in a collision avoidance system. The most common methods used for representing knowledge in a KB are listed in [21]: Propositional Calculus, Predicate Calculus, Semantic Networks, Decision Rules and Decision Trees. For representing the knowledge in COLREGs, the first step is to analyze the rules by an expert in the maritime domain, and then to use a technology e.g. Decision Tree to represent such knowledge to be used by the decision support system. Iijima et al [18] and Coenen et al [19] were reported by Tam et al [11] as early approaches trying to interpret the knowledge in COLREGs and represent it in KB. Encounter situation rules (13, 14 and 15) are represented in their KB to make decisions of stand-on and give-way vessels (implicitly addressing of requirements (b), (c) and (d)). Breitsprecher [21] examined several methods (e.g. decision tree) for representing knowledge in COLREGs. For COLREGs-coverage, he analyzed only rule 13 (overtaking), and he addressed, in addition to rule 13, the rule 18 for responsibilities between vessels. No more rules have been discussed by Breitsprecher s paper [21]. Banas et al [20] addressed COLREGs parts A & B more comprehensively in an expert system. The encounter situations rules (13, 14 and 15 (part B-II)) in addition to relevant concepts in parts A & B-I e.g. risk of collision (rule 7) are represented in COLREGs-KB. He presented five different examples covering the encounter situations (head-on, crossing, and overtaking) and the decision of existing risk or safe situation. Similar to fuzzy based approaches, narrow channels and TSS rules (part B-I) and parts B-III, C & D are not addressed in KB based approaches. 3.3 COLREGs-Coverage in Evolutionary Algorithms based Collision Avoidance Approaches [22-28] In general, all evolutionary approaches in maritime collision avoidance aim at optimizing the predicted safe trajectories. The underlying generic principle of these evolutionary approaches is based on the concept of survival of the fittest. This can be applied in collision avoidance by utilizing an evolutionary algorithm to maintain a population of assigned paths, and through a process of variation and selection, to find a near-optimum solution, Statheros et al [12]. We identified Zeng [22], Smierzchalski et al. [23, 24, 27], Tsou et al. [25, 26] and Szlapczynski [28] use evolutionary algorithms for maritime collision avoidance. Two main algorithms have been used; Genetic algorithm adopted by [22-25, 27, 28] and Ant Colony algorithm adopted by Tsou [26]. In genetic algorithms, variables are defined (e.g. latitude, longitude, speed, course, etc.) and controlled and optimized by using genes form chromosomes [12]. Each gene contains information such as ship coordinates. A chromosome specifies the interconnections between its genes to create e.g. a trajectory to be optimized by a genetic cost function. For the other algorithm analyzed in the evolutionary domain, i.e. the ant colony algorithm, it models the behavior of real ants in search of food to find the shortest route from a food source to their nests. It is utilized by Tsou [26] to enable collision avoidance for ships moving towards their goals. This is achieved by choosing the most suitable objective function during the collision avoidance route search so that the search process becomes more efficient. For checking COLREGs-coverage requirements in such approaches, we found that Zeng [22] addressed concepts in COLREGs parts A & B (e.g. risk of collision, safe speed, encounters, etc.) implicitly to ensure safe path planning, that his approach did not discuss the rules e.g. encounter situation rules (13, 14 and 15) explicitly, but instead it defined a genetic cost function for safe path planning (implicit addressing of requirements (b), (c) and (d)).

5 Similarly, Smierzchalski et al. [23], [24] and [27] addressed parts A & B implicitly but with an extension to optimize the safe path by introducing time parameter and variable speed of the ship. Thus, COLREGs safe speed rule 6 is addressed implicitly by this extension. Tsou et al. [25] and [26] addressed part B-II in COLREGs explicitly; that he discussed the encounter situation rules (13, 14 and 15). Tsou calculated DCPA to determine a risk of collision, but he did not monitor the bearing change explicitly (implicit addressing of risk of collision rule 7). Szlapczynski [28] introduced a more comprehensive approach to address multiple encountering ships complying with COLREGs parts A & B, where he estimated the risk of collision (rule 7) using equations considering multiple ships. Similar to above mentioned categories, narrow channels and TSS rules (part B) and parts B- III, C & D are not addressed in evolutionary based approaches. 3.4 COLREGs-Coverage in Robotic Path Planning based Collision Avoidance Approaches [29-32] Several robotics technologies have been adopted in maritime collision avoidance. For example, the Virtual Field Force (VFF) based on the concept of artificial potential field introduced by Khatib in 1985 and discussed by Statheros et al [12]. VFF consists of related forces controlling the motion of robot; For ships path planning, one vector represents the force between the ship and the desired waypoint and another vector represents the force between the obstacle and the ship, and a resultant force from the already mentioned forces is represented as a vector of the direction of the ship for obstacle avoidance. Another example of robotics algorithms is A* algorithm used for optimal path planning. A* algorithm forms a weighted graph of nodes (e.g. the path through a grid in grid-based path planning). A* algorithm checks a tree of all possible paths in the formed graph to determine one path that has the smallest cost (e.g. shortest distance, shortest time). Thus, obstacles given by e.g. ENC can be considered in the graph for collision avoidance while planning safe and optimal path. We identified Xue et al. [29], Campbell et al. [30], Loe [31] and Blaich et al. [32] use robotic algorithms for maritime collision avoidance. For COLREGs-coverage requirements, Xue et al. [29] utilized the VFF approach to address the safe speed vector (rule 6, requirement (b)) considering several supplementary data sources e.g. wind, wave and current (implicit addressing of requirement (a) to maintain a proper lookout). Xue addressed the encounter situations rules for multiple ships, (part B-II 13, 14 and 15, requirements (c) and (d)). The responsibilities of stand-on and give-way vessels (part B-II rules 16, 17) are also addressed by Xue by defining four stages for checking potential collisions and determining responsibilities accordingly. According to A* based approaches, Campbell et al. [30], Loe [31] and Blaich et al. [32], the encounter situations rules (part B 13, 14, 15) were the main addressed rules (requirements (b), (c) and (d)). In addition, Loe [31] addressed explicitly the rule 8 in part B-I (actions to avoid collision). Similar to above mentioned categories, narrow channels and TSS rules (part B) and parts B- III, C & D are not addressed in robotics algorithms based approaches. 3.5 COLREGs-Coverage in Velocity Obstacle based Collision Avoidance Approaches [33-35] The Velocity Obstacle (VO) concept has been adopted by many maritime collision avoidance approaches [33-35] to ensure safe navigation. For two checked vessels, the VO defines a safe area for navigation outside a cone-shaped obstacle containing all risky velocity vectors which can lead to a collision between the two checked vessels, Kuwata et al. [33]. Several extensions to VO have been reviewed by Kuwata et al. [33], including a cooperative collision avoidance, probabilistic velocity obstacles, and crowd simulation. In addition to Kuwata et al. [33], we identified Svec et al. [34] and Stenersen [35] use VO based maritime collision avoidance.

6 For COLREGs-coverage requirements, Kuwata et al. [33] referred to a natural compliance with COLREGs due to the fact that VO specifies which side of the obstacle the vehicle will pass during the avoidance maneuver. Thus, the encountering rules in COLREGs (rules 13, 14 and 15, requirements (c) and (d)) were mainly addressed by Kuwata. In addition, rule 6 (safe speed, requirement (b)) is addressed implicitly by defining safe speeds outside the coneshaped obstacle. The responsibilities of stand-on vessel mentioned in rule (17) are addressed by applying hazard avoidance algorithm (requirements (c) and (d)). Svec et al. [34] addressed COLREGs in a similar way to Kuwata's approach by ensuring safe speed (rule 6) by VO implicitly without discussing the factors of rule 6. Part B-II as encounter situations is addressed in the cost function of Svec s approach by defining a cost penalty for breaching COLREGs encountering rules (13, 14 and 15). Similarly, Stenersen [35] addressed encountering rules, and utilized TCPA/DCPA with relative bearing to determine a risk of collision (rule 7, requirements (c) and (d)). Similar to above mentioned categories, narrow channels and TSS rules (part B) and parts B- III, C & D are not addressed in VO based approaches. 3.6 COLREGs-Coverage in Hybrid Systems based Collision Avoidance Approaches [36-39] The Hybrid systems utilize more than one technology to get more advantages and to overcome potential disadvantages when using only one technology. According to Statheros et al. [12], Hybrid systems look very promising but require a high level of intelligence to harmonically merge the different technologies together. One example is to combine between the machine learning capabilities of neural networks with the advantages of fuzzy logic systems in dealing with nonlinearities and uncertainties; thus, a neuro-fuzzy system incorporates the human-like reasoning (by fuzzy logic) and learning style (by neural networks). We identified Liu et al. [36] as an approach combines between fuzzy logic and neural networks, Lee et al. [37] use heuristic search reinforced by fuzzy relational products & COLREGs, Lee et al. [38] use a combination between fuzzy logic & modified VFF and Hwang et al. [39] use a combination between fuzzy logic, expert system and state space. For COLREGs-coverage requirements, Liu et al. [36] addressed only encounter situations rules (13, 14, and 15, requirements (c) and (d)). Whereas Lee et al. [37], [38] quantified key aspects in other rules as well, e.g. rule 8 which requires strict safety precautions in view of both the direction of motion of the vessels involved as well as their relative speed (requirements (a)-(d)). Hwang et al. [39] complied with COLREGs in a similar way to Liu et al. [36], i.e. by addressing COLREGs part B-II, and concretely encountering rules (13, 14 and15). Similar to above mentioned categories, narrow channels and TSS rules (part B) and parts B- III, C & D are not addressed in hybrid systems based approaches. 3.7 COLREGs-Coverage in Other Approaches [40-42] In this last subsection of COLREGs-coverage, we discuss some other approaches not categorized in one of the above categories. We identified a model predictive controller introduced by Johansen et al. [40] utilizes a cost function measures the predicted grounding and collision hazards in compliance with COLREGS, using velocity and line-of-sight vectors to express the COLREGS rules. We identified a spatio-temporal approach introduced by Kreutzmann et al. [41] as a specification language that allows verifying software solutions that address COLREGs. In addition, we identified a Behavior-based control approach introduced by Benjamin et al. [42] using interval programming technology. For COLREgs-coverage, Johansen et al. [40] addressed rule 6 (safe speed) and rule 7 (risk of collision) implicitly by checking the predicted trajectories of own and target ships to determine whether the target ship (obstacle) is close to own ship. Similarly, checking the

7 predicted trajectories of own and target ships is used to detect and address the encounter situations (rules 13-15). The rule 17 (actions by Stand-on) is also addressed by defining a cost-parameter in the controller giving a higher penalty on course offset commands to port than starboard. Collision avoidance with multiple encountering target ships (obstacles) is also addressed by this approach according to rules Thus, requirements (b-d) are addressed. Kreutzmann et al. [41] did not aim at complying with the rules in COLREGs, but he introduced a spatio-temporal based specification language to formulate the rules. As an example, he formulated the rule 12 (sailing vessels) in part B-II. Benjamin et al. [42] focused the attention on the four most challenging rules, from an autonomous navigation perspective, that cover head-on situations and crossing situation, rules and the rule 8(b), (d) which addresses collision avoidance generally. The COLREGs encountering situations in rules are addressed as behaviors by defining an objective function for each situation (behavior) mainly based on quantifying the risk (based on CPA/TCPA/DCPA) and the relative bearing between the two vessels, e.g. a relative bearing within 15 degrees means Head-on (requirements (b), (c) and (d)). Similar to above mentioned categories, narrow channels and TSS rules (part B) and parts B- III, C & D are not addressed in [40-42]. 4. COLREGs-Coverage Summary This section summarizes the COLREGs-coverage in all reviewed approaches [13-42] regardless of the technologies and concepts. COLREGs part A & B-I, which have concepts to be quantified e.g. safe speed and risk of collision, have been addressed by James [13] (by quantifying safe passing distance and early action), Smeaton et al [14], Lee et al [15] and Hwang et al [16], Tsou et al. [25] and [26], Stenersen [35], Johansen et al. [40], Benjamin et al. [42] (by using TCPA/DCPA as quantifying concept to detect a risk of collision), Perera et al. [17], Lee et al. [37], [38] (by using relative speed and relative course to detect a risk of collision), Banas et al [20] (by representing the risk of collision in his COLREGs-KB), Zeng [22], Smierzchalski et al. [23], [24] and [27] (by ensuring safe path planning concerning parts A & B-I concepts e.g. risk of collision and safe speed), Szlapczynski [28] (by estimating the risk of collision concept in an equation considering multiple ships), Xue et al. [29] (by ensuring safe speed in his VFF approach), Loe [31] (by explicitly addressing of actions to avoid a collision), Kuwata et al. [33] and Svec et al. [34] (by ensuring safe speed outside the VO). COLREGs part B-II, which addresses the conduct of vessels in sight of one another, discusses the encounter situations (head-on, overtaking and crossing) which are addressed by all the analyzed approaches [13-42]. Whilst most of the approaches in [13-42] address these rules (13, 14 and 15) explicitly, some approaches address them implicitly such as Zeng [22], Smierzchalski et al. [23], [24] and [27] who defined cost functions for safe path planning and did not discuss the rules (13, 14 and 15) explicitly. Only few approaches addressed the other rules rather than in part B-II, e.g. Perera et al. [17], Xue et al. [29], Kuwata et al. [33] and Johansen et al. [40] who addressed the responsibilities of give-way (rule 16) and stand-on vessels in case of absence of proper actions from the give-way vessel (rules 17), and Breitsprecher [21] who addressed the responsibilities between vessels (rule 18). COLREGs parts B-III, C & D have been not addressed by all approaches. Part B-III discusses the conduct of vessels in restricted visibility. Parts C & D define specific sound and light signals which should be issued by ships in specific situations (e.g. in restricted visibility). To satisfy COLREGs-coverage requirements, we introduce a concept as an extension to collision avoidance approaches to let them cover parts C & D by using additional sensors for capturing and understanding such sound/light signals. More details are explained in section 5.

8 5. Outlook: Usage of Additional Sensor Information For COLREGs-coverage requirements, collision avoidance systems have to consider sound and visual data described in part C & D. That can potentially be done by using computerized detection using visual and acoustic data, implemented e.g. as an Artificial Neural Networks (ANN) as used for environment detection in automotive domain. Given the description of sound and light signals and shapes from COLREGs, specialized sound/light sensors and cameras, supported with well-trained detection systems for signals classification, can significantly contribute to the ship s situational awareness and thus assist the crews understanding and estimating potential risks. In the following two scenarios are discussed for clarification: Vessel restricted in her ability to maneuver crossing another vessel The crew of a restricted vessel uses typically her AIS-transceiver to publish her restriction as a specific value in the Navigation status field in AIS messages to inform other vessels about such a restriction. However it can happen, that such important information (restricted vessel) may not be published at the right urgent time. Another vessel crossing the restricted one from her starboard side should be a stand-on vessel according to COLREGs rule 15, however, given that the give-way vessel is restricted in her ability to maneuver the stand-on vessel should keep out of the way according to COLREGs rule 18. The restricted vessel is obliged to issue specific blasts according to rule 35.(c) to warn other vessels about her restriction. At night, such a restricted vessel should exhibit specific lights mentioned in rule 27. These blasts/lights, in addition to others, can be observed using sensors supported with a classification system to classify the signals and to improve the situational awareness accordingly. Risky overtaking near to bend in narrow channels The rule 9 in COLREGs is about navigation in narrow channels. The overtaking in narrow channels is discussed in part 9(e) and approaching hidden vessels in a bend is discussed in part 9(f). In each part, specific sound signals are mentioned. Given that an overtaking vessel can be unware of an oncoming bend in the channel, its overtaking can be critical and can lead to a collision with hidden vessel navigating in the bend. Typically, the overtaken vessel may sound the warning signal of approaching a bend mentioned in rule 34(e). If the crew of the overtaking vessel is springy enough and distinguishes that such a sound (prolonged blast) means that there is a critical bend coming forward of the overtaken vessel, then the overtaking should be stopped. Such an important decision (Avoid overtaking because you will be approaching a hidden bend!) can be provided as recommendation by the proposed automatic recognition solution. 7. Conclusion This paper reviews several approaches in the state of the art of maritime collision avoidance. It discusses how COLREGs are considered in this work. It highlights that especially parts C & D in COLREGs are not addressed. Similar to approaches in the automotive domain, automatic recognition of sound/light signals issued by vessels is identified as a suitable extension for collision avoidance systems. Two scenarios are discussed to show the added-value of the proposed approach of automatic recognition of light/sound signals based on COLREGs parts C & D. The work presented in this paper has been done within the project MTCAS that is funded by the Federal Ministry of Economics and Energy, Germany. References [1] Contribution from the international maritime organization (imo) to the secretary general s report for the 2013 annual ministerial review on science, technology and innovation, and the potential of culture, for promoting sustainable development and achieving the millenium

9 development goals. (last visited: ), [2] COLREGS - International Regulations for Preventing Collisions at Sea, Lloyd s Register Rulefinder 2005 Version 9.4 [3] ColRegs Amendments Summary, (last visited: ) [4] European Maritime Safety Agency. Annual overview of marine casualties and incidents. (last visited: ), [5] Rothblum AM. Human error and marine safety. InNational Safety Council Congress and Expo, Orlando, FL 2000 Oct 13. [6] Jingsong, Z., W. G. Price, and P. A. Wilson. "Automatic collision avoidance systems: Towards 21st century." Department of Ship Science 1.1 (2008): 1-5. [7] Chen, Ge, et al. "Recent progress of marine geographic information system in China: A review for " Journal of Ocean University of China 11.1 (2012): [8] Baker, Clifford C., and Ah Kuan Seah. "Maritime accidents and human performance: the statistical trail." MarTech Conference, Singapore [9] Ćorović, Branislav M., and Petar Djurovic. "Marine accidents researched through human factor prisma." PROMET-Traffic&Transportation 25.4 (2013): [10] Knight, John C. "Safety critical systems: challenges and directions."software Engineering, ICSE Proceedings of the 24rd International Conference on. IEEE, [11] Tam, CheeKuang, Richard Bucknall, and Alistair Greig. "Review of collision avoidance and path planning methods for ships in close range encounters."journal of Navigation 62.3 (2009): 455. [12] Statheros, Thomas, Gareth Howells, and Klaus McDonald Maier. "Autonomous ship collision avoidance navigation concepts, technologies and techniques." Journal of navigation (2008): [13] James, M. K. "Modelling the decision process in computer simulation of ship navigation." Journal of Navigation (1986): [14] Smeaton, G. P. & F. P. Coenen, Developing an intellifent marine navigation system, March (1990), [15] Lee, Han-Jin, and Key Pyo Rhee. "Development of collision avoidance system by using expert system and search algorithm." International shipbuilding progress 48.3 (2001): [16] Hwang, Cheng-Neng. "The integrated design of fuzzy collision-avoidance and H [infty infinity]-autopilots on ships." Journal of Navigation (2002): [17] Perera, L. P., J. P. Carvalho, and C. Guedes Soares. "Fuzzy logic based decision making system for collision avoidance of ocean navigation under critical collision conditions." Journal of marine science and technology 16.1 (2011): [18] Iijima, Yukito, Hideki Hagiwara, and Hironao Kasai. "Results of collision avoidance manoeuvre experiments using a knowledge-based autonomous piloting system." Journal of Navigation (1991): [19] Coenen, F. P., G. P. Smeaton & A. G. Bole (1989), Knowledge-based collision avoidance, The Journal of Navigation, 42, [20] Banas, P., and M. Breitsprecher. "8. Knowledge Base in the Interpretation Process of the Collision Regulations at Sea." Methods and Algorithms in Navigation: Marine Navigation and Safety of Sea Transportation (2011): 59. [21] Breitsprecher, Marcin. "Methods of knowledge representation contained in COLREGS." Zeszyty Naukowe/Akademia Morska w Szczecinie (2012): [22] Zeng, Xiao-ming, Masanori Ito, and Etsuro Shimizu. "Collision avoidance of moving obstacles for ship with genetic algorithm." Advanced Motion Control, Proceedings. 6th International Workshop on. IEEE, [23] Smierzchalski, Roman & Andrzej Lebkowski, Intelligent ship steering system, Proceedings of the 7th IFAC Conference on Manoeuvring and Control of Marine Craft. (2006)

10 [24] Smierzchalski, Roman, and Zbigniew Michalewicz. "Modeling of ship trajectory in collision situations by an evolutionary algorithm." IEEE Transactions on Evolutionary Computation 4.3 (2000): [25] Tsou, Ming-Cheng, Sheng-Long Kao, and Chien-Min Su. "Decision support from genetic algorithms for ship collision avoidance route planning and alerts." Journal of Navigation (2010): [26] Tsou, Ming-Cheng, and Chao-Kuang Hsueh. "The study of ship collision avoidance route planning by ant colony algorithm." Journal of Marine Science and Technology 18.5 (2010): [27] Smierzchalski, Roman. "Evolutionary trajectory planning of ships in navigation traffic areas." Journal of marine science and technology 4.1 (1999): 1-6. [28] Szlapczynski, Rafal. "Evolutionary sets of safe ship trajectories: a new approach to collision avoidance." Journal of Navigation 64.1 (2011): [29] Xue, Y., B. S. Lee, and D. Han. "Automatic collision avoidance of ships. "Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment (2009): [30] Campbell, S., and W. Naeem. "A rule-based heuristic method for COLREGs-compliant collision avoidance for an unmanned surface vehicle." IFAC Proceedings Volumes (2012): [31] Loe, Øivind Aleksander G. "Collision avoidance for unmanned surface vehicles." (2008). [32] Blaich, Michael, et al. "Fast grid based collision avoidance for vessels using A search algorithm." Methods and Models in Automation and Robotics (MMAR), th International Conference on. IEEE, [33] Y. Kuwata, M. T. Wolf, D. Zarzhitsky and T. L. Huntsberger, "Safe Maritime Autonomous Navigation With COLREGS, Using Velocity Obstacles," in IEEE Journal of Oceanic Engineering, vol. 39, no. 1, pp , Jan [34] P. Švec, B. C. Shah, I. R. Bertaska, W. Klinger, A. J. Sinisterra, K. von Ellenrieder, M. Dhanak, and S. K. Gupta. Adaptive Sampling Based COLREGs-Compliant Obstacle Avoidance for Autonomous Surface Vehicles. ICRA 2014 Workshop on Persistent Autonomy for Marine Robotics (ICRA PAMR '14), Hong Kong, China, June 5, [35] Stenersen, Thomas. "Guidance System for Autonomous Surface Vehicles." (2015). [36] Liu, Yu-Hong, Xuan-Min Du, and Shen-Hua Yang. "The design of a fuzzy-neural network for ship collision avoidance." Advances in Machine Learning and Cybernetics. Springer Berlin Heidelberg, [37] Lee, Young-il, and Yong-Gi Kim. "A collision avoidance system for autonomous ship using fuzzy relational products and COLREGs."International Conference on Intelligent Data Engineering and Automated Learning. Springer Berlin Heidelberg, [38] Lee, Sang-Min, Kyung-Yub Kwon, and Joongseon Joh. "A fuzzy logic for autonomous navigation of marine vehicles satisfying COLREG guidelines."international Journal of Control Automation and Systems 2 (2004): [39] Hwang, Cheng-Neng, Joe-Ming Yang, and Chung-Yen Chiang. "The Design of Fuzzy Collision-Avoidance Expert System Implemented by H (subscript )-Autopilot." Journal of Marine Science and technology 9.1 (2001): [40] Johansen, Tor Arne, Tristan Perez, and Andrea Cristofaro. "Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment." (2016). [41] Kreutzmann, Arne, et al. "Towards safe navigation by formalizing navigation rules." TransNav: International Journal on Marine Navigation and Safety of Sea Transportation 7.2 (2013): [42] Benjamin, Michael, et al. "Protocol-Based COLREGS Collision Avoidance Navigation Between Unmanned Marine Surface Craft." Journal of Field Robotics 23.5 (2006).