Nautical safety and efficiency: simulation and reality

Safety

Science 19 (1995) 157-169

Nautical safety and efficiency: simulation and reality J. Perdok”, P.H. Wewerinke’ Maritime Simulation Centre (MSCN), P.O. Box 217, 7500 AE Enschede, The Netherlands

Abstract The paper deals with training and research using maritime simulation techniques to provide costeffective and safe solutions to maritime transportation problems. In order to reduce the probability of accidents, training and research is required in which the human factors are fully taken into account.

1. Introduction The investigation of marine casualties has concentrated so far mainly on technical malfunctions, ignoring the human factors. However, these human factors are in the majority of cases the main cause of the casualties. In addition, in most cases, there is not one single factor, but a combination of factors which makes every accident or incident a unique case. A famous example is the accident with the ‘Torrey Canyon’ which ran aground in the Stilly Isles in March 1967 and spillt all her oil, causing colossal pollution. Below follows a quote from the Board of Investigation (Marriot, 1987): “The Master was negligent in the following respects: He took the ship between the Seven Stones and the Scillies, rather than between the Seven Stones and Land’s End. Despite the presence offishing vessels and nets, he kept the ship on automatic steering, failing to put her in hand steering. He failed to reduce speed at any time prior to the stranding and especially at 08.40 when he reckoned he was nearer to the Seven Stones than he had previously thought and when a turn to 325” was prevented by the presence of a fishing vessel on his port side. He had not established any regular or routine practice for the operation of the steering wheel selection lever.’ ’ In addition the Master (Captain the report goes on: I Mr. P.H. Wewerinke

Rugiati)

is lecturer at the Technical

had not taken into account the strong current, so

University of Twente and par-time

0925-7535/95/$09.50 0 1995 Elsevier Science B.V. All rights reserved .SSDIO925-7535(94)00017-4

employed by MSCN.

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“It is interesting to note that Capt Rugiati was not the only seafarer to be deceived by the strong northeasterly set which put the ‘Torrey Canyon’ further to the north and east than he expected. The strong set is a well known phenomenon at certain times of the year. It runs between Ushant and the Scillies and has accountedfor many of the 257 known wrecks on the troublesome rocks and islands of the Scillies.” “The ‘Torrey Canyon’ had good visibility, modern navigational aids, daylight radar and there was no gale. Small wonder that the Board of Investigation found that only human error was to blame.” This is one of the many examples in which human error can be isolated as the main cause of a major marine casualty. Another more recent example is the stranding of the 125,000 m3 LNG Carrier ‘El Paso Paul Kayser’, which stranded on a pinnacle of the La Perla Shoal in the Strait of Gibraltar on 29 June 1979. After a careful analysis it was concluded that the following lessons could be learned (Chadwick, 1984) : “ 1. The preparation and execution of a passage plan is essentialfor safe navigation. 2. Adequate numbers of men on the bridge do not make an adequate bridge organisation. The bridge team must actively support the conning ofJicer. 3. Total reliance on a CAS radar can place a vessel at great risk.” The list of “famous” accidents in which human factors and human errors play dominant role can be extended with accidents as those with the ‘Exxon Valdez’ and the ‘Harald of Free Enterprise’. In order to reduce the probability of such accidents research and training is required. This is the area in which the Maritime Simulation Centre Netherlands (MSCN) is active. In the following chapters an overview is provided of activities in the areas of training and research with respect to nautical safety and efficiency.

2. Training 2. I. Introduction From incidents like the above mentioned, it can be concluded that communication and coordination in a bridge team is very important. Every member of the team has to know his tasks and responsibilities within the procedures for the various situations. Due to all kinds of reasons procedures are not always executed as they should. Training of bridge teams in the execution of the procedures can help to reduce the risks of loss of equipment, cargo (environmental dangers) and of course people. Nowadays, more demands are made upon the flexibility, skills and knowledge of the bridge crews and pilots. Some of the reasons are: - the tendency to reduce the size of the bridge crews; - the increasing number of tasks on the bridge (apart from navigation and communication also engine room monitoring and cargo handling) ;

1. Perdok, P.H. WewerinkeISafety Science 19 (1995) 157-169

159

TRAININQM0DlJl.E ESTABLISHED BASIS

Fig.

I. A training module.

the decrease of operational time on board (less practice) ; - the increasing emphasis on safety in relation to risk of environmental pollution; -the fact that about 80% of the accidents at sea are due to human error; - the increasing use of high technology equipment/automation on the bridge; - the increasing need of flexibility of ship crews and pilots in view of different levels and/ or standards of automation and different types of equipment; - the differences in procedures for different types of ships; -the increasing number of ‘mixed’ bridge crews with respect to culture and level of education. To attain optimal functioning of the bridge crews and pilots, simulation of various situations significantly contributes to the improvement of performance. However, in the field of full mission bridge simulators, the structured development of training is way behind the technical developments in that area. Therefore a structured approach to the development of training programs for the shipping industry and education is needed. -

2.2. A structured approach to training development The first step in the development of a sound training program is a thorough task, skills and knowledge analysis. The information gathered in these analyses, resulting in detailed learning objectives, form the basis on which further training development must take place. The next steps in the development process are concerned with the development of the training scenario’s and other training materials. All of the above mentioned must result in framework like basis training modules (see Fig. 1)

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From this figure can be seen that the starting point for a basis training module consists of an established basis of the analyzed tasks, skills and knowledge and the resulting learning objectives. At this moment, MSCN is developing basis modules for three types of technical simulator training programs: - procedure training to practise bridge procedures which should be executed in dangerous and/or various critical situations; - skill training which is aiming at specific skills like the docking of a ferry in difficult circumstances or piloting skills; - familiarisation training to get the pilot or bridge officer used to the behaviour of a new type of ships and/or modified ports and freeways. These basis modules again, form the starting point for the development of tailor made training programs, based on the specific needs and wishes of the customer. In this way quick and effective custom made training development can be realized. 2.3. Non-technical

training

The Bridge Crew Management Training course of MSCN has originally been developed by the Royal Dutch Airlines (KLM) to improve the non-technical skills of the cockpit crew. The course has been adapted for application in the nautical world by MSCN. The objective of the BCMT are promotion of team spirit and improvement of communication to create an effective and reliable organization with an optimal problem solving ability on board ships. In the training course the following skills are trained: Communication. Communication forms the basis for the effectiveness of an organization, the correctness of decisions and a good cooperation. During the course, attention will be paid to different styles of communication and their effects. Motiuating people. How can others be influenced positively? Due to the training course one becomes more aware of the effects that certain actions and communication (styles) have on work motivation. Rational decision-making. Taking and monitoring decisions is a complex process, in which many potential pitfalls are hidden. In rational decision-making a 7 step method for Rational Decision-making is used in which attention is dedicated to fact finding, distinguishing facts from assumptions, judgements and prejudice. Thinking under pressure. What happens to human information processing under (time) pressure? If one is aware of the effects which (time)pressure has on human information processing, one can take this into account, so that the ultimate quality of decisions increases. Speaking up. In preventing wrong decisions it is important that decisions and the decisionmaking processes are monitored by more than one person. If a lower rank notes serious mistakes in the execution of tasks on board, then he has to inform his superior. Also if the superior has initiated the wrong decision or procedure. Cultural, political and group differences. Working and team-building with people from different cultures makes high demands on the communication skills of the crew. Miscommunication and misunderstandings can easily lead to irritations. The same applies to group

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differences based on differences in education. How to deal with these situations is an important part of the training. Stress management. How can stress symptoms be recognized? When is stress harmful and when is it useful? How can stress be controlled and how can the resistance to stress due to working conditions be increased? These and related questions will be treated in depth during the training course. 2.4. The Training Evaluation System (TES) Since the early days of maritime simulation a lot of time has been devoted to the training of pilots and bridge officers in different tasks. Although nobody shall deny that actual learning took place during the simulation sessions there is (in most cases) no clear proof of this learning process. This, despite the fact that a lot of money has to be paid to the owner of the simulator facilities for use of the equipment and the activities of the instructor. For that reason MSCN has started with the design and development of a Training Evaluation System (TES, see Fig. 1.) which will be designed for the following reasons: - to obtain information on the quality of the different elements in the training process to optimize the overall quality of the training programs. TES will be part of the NEN IS0 9001 quality assurance procedures within the training department of MSCN; - to monitor the performance of the trainee to optimize the individual training course. - to provide the client with information on the effectiveness (value) of the training program. TES is integrated into the training design procedure which describes the development process of all the (simulator) training courses at MSCN. This means that TES covers the whole range from the first contact with the customer until the measuring of the transfer of the training after the execution of the training. In this way TES can also easily be integrated into the NEN IS0 9001 quality assurance procedures for training design and execution. Within TES, four types of informants are used to obtain the needed information about the training: - The customer; - The MSCN training experts; - The instructor; - The trainees. The customer is asked to describe his training needs as good as possible. These needs are translated by MSCN into the training profile which is the training blue print. After the execution of the training, the customer is asked to monitor the performance of the trainees who received the training in order to determine the transfer of the knowledge and skills from the training to the daily work routine. The MSCN training experts are conducting and monitoring the training design process and the execution of the training. They check whether the customer’s needs are correctly translated into the training profile and again if the training profile is correctly translated into the training products. During the execution of the training, they observe some training sessions to note whether the training is executed according the plan. The MSCN expert uses one of the most important instruments of TES: the instrument to measure skill and knowledge improvement. At this moment (October 1992)) this instrument is in a premature phase but the current design tells that the instrument will combine objective

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and subjective measures to be able to determine skill and/or knowledge improvement. The instructor is asked to give his opinion on the training: for example the objectives, the materials, the time schedule and the content. He is asked if there were any troubles during the training and what the causes were according to his opinion. Also, he gives his opinion on the skill and knowledge improvement of the trainees. The trainees are asked to give their opinion on the training: for example the objectives, the course materials, the instructor, the simulator and the time schedule. Also they are asked if they think that their skills and knowledge is improved during the training.

3. Nautical research Many designs and operational problems require a thorough analysis of these problems using appropriate research tools. Two research approaches can be distinguished to obtain a better understanding of the often complex nautical process. The first approach is based on data analysis techniques. This involves data reduction to obtain derived measures (e.g. for risk of safety) or extrapolation, generalization or prediction of new situations (often in statistical terms). The second approach is based on simulation of the complex process. This allows a systematic investigation of the effect of the many variables such as ship dynamics, environmental variables, navigational aids, human factors, regulations etc. Especially human factors can play a crucial role in the safety and efficiency of ship handling. 3.1. Real-time simulation These ‘man-in-the-loop’ problems can be studied utilizing real-time simulators with real human beings. This represents the reality to a very high degree especially as far as the human factors, his capabilities and limitations are concerned. This includes the variability due to differences in the skills of pilots and shipmasters (see before about training). Ship handling simulators consist of a bridge with bridge instruments and controls, an outside view and driven by a mathematical model of ship motions. MSCN capability consists of two full mission bridge simulators, including manoeuvring, engine room and cargo handling. In addition a Vessel Traffic Simulator (VTS) is available at MSCN, which can be linked to the full mission manoeuvring simulators. Although a simulator is a sophisticated tool to provide reliable answers to nautical safety and efficiency questions, its use can be relatively costly due to the vast number of conditions to be tested and the large number of test runs to be performed for each condition in order to arrive at a reliable answer. Therefore MSCN utilizes also fast-time simulation models, in which the role of the human operator(s) is described in mathematical terms. Especially early in the design stage, models can be used to analyze systematically all relevant factors of the complex process and to select design alternatives. This is discussed in the next section.

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3.2. Fast-time simulation models In this section the fast-time simulation models developed and/or used by MSCN are reviewed. The starting point of all models is that a planned route has to be realized, in terms of a given (number of) track(s). The models vary from a simple autopilot to a detailed description of the total navigator-ship system including explicitly human functions, such as visual perception, information processing, decisions making, planning and controlling. In addition simple ship operations are considered, as well as ship assistance by tug boats, and the total vessel traffic process. 3.2. I. SHIPMA model The SHIPMA model (Anon, 1990) is basically an autopilot based on conventional servosystem principles. It comprises several control modes (track keeping, zig-zag manoeuvring, making a turning circle and a tug control mode). In this paper only the (normal) track keeping mode will be discussed. The autopilot is designed to follow a user-specified reference track (in terms of way points and radii of bend for the track transitions) as well as possible. The rudder angle is basically determined from the following relationship: S=cAr+C,,Aq+C,,Ay,

(3.1)

where Ar, AT and Ay are deviations from a reference point on the track a given (to be specified) distance ahead. This way adaptive (i.e. track independent) dynamic response is obtained at the cost of computational effort to generate Ar, Aq and Ay. However, some trial and error might be required, for a specific case, to modify the nominal feedback gains. 3.2.2. FORCESIM model The FORCESIM model (Chadwick, 1984) can be used to compute optimal control settings, such as rudder angle and RPM and an optimal use of manoeuvring devices such as tug boats (tug boats are simply represented as force vectors), for executing a prescribed manoeuvre for a given vessel and environment. Also this model does not include the navigators with their variable behaviour. The (deterministic) model indicates the upper boundary ‘of the ship manoeuvring capability and shows if a desired manoeuvre could possibly be realized. The model includes a nonlinear, time-varying mathematical model of the ship dynamics, including the effects, of the control variables (rudder, RPM, tug forces, etc.) and of environmental disturbances such as wind, current, waves and bottom and bank effects. This can be represented by X(k) =f(X(k-

l), U(k-

l), W(k-

l), k),

(3.2)

where X(k) is the state vector (consisting of position, speed, heading, etc.) at time k, f is a vector function, U is the control vector and W is the disturbance vector. The task to be executed is sailing from A to B, possibly with predescribed intermediate positions, heading, speed, etc. This tracking task can be expressed as

J. Perdok, P.H. Wewerinke/Safety Science 19 (1995) 157-169

164

fG(i)-&(i))'Q,(i>CXCi)

--G(i))

i=l

+U’(i-

l)Q,(i-

l)U(i-

1)

1,

(3.3)

where JN is the resulting performance measure corresponding with a given interval of time [O,N] which will be minimized by the optimal control U, X, indicates the desired state trajectory and Q, and Q, are weightings. The approach is formulated in terms of Pontryagin’s maximum principle. Numerically, the procedure is based on the conjugate gradient method. In general FORCESIM can be used to -determining the manoeuvring devices needed for the execution of a manoeuvre under various environmental conditions for various vessels; - select critical situating and interesting conditions to be investigated, for example in realtime simulations; - develop manoeuvring strategies. 3.2.3. TUGSIM model While in FORCESIM tug boats are simply represented as force vectors the TUGSIM model (Wewerinke, 1991) explicitly deals with the manoeuvring with tug boats. So the model describes for a given ship to be assisted (with given speed and course) and for given commands of the ship pilot, in terms of tug force (percentage of power) and direction, how the tug boat captain is executing dynamics, the environment (current, wind) and the manoeuvring strategy. Basically the modelling approach of TUGSIM, which is being developed at MSCN, is the following. Several tug models (direct pulling), stand-by, etc., corresponding with specific tug commands of the pilot and boundary conditions of the tug power, cable direction and tug boat controls (thrust and direction or rudder angle). The model determines how each tug mode can be realized (stabilized) by the appropriate tug boat control. Basically, the model determines the most efficient tug boat control, corresponding with the maximum cable force, given the ship dynamics and other constraints. In addition it is described how the tug boat is manoeuvring to change from one mode to another. It may be expected that this leads to realistic tug boat behaviour and a useful simulation tool, although in reality the interaction between pilots and tug boat captains can be somewhat more complicated depending on the extent to which tug boat captains anticipate and take own initiatives. For the time being, only the control behaviour is modelled, assuming that the uncertainty of assessing the situation is of minor importance. Thus basically, the present modelling effort is aimed at the design of an autopilot. 3.2.4. NAVSIM model The NAVSIM model (Ten Hove et al., 1990; Wewerinke et al., 1988) is based on the fundamental hypothesis that the human operator (HO) behaves optimally subject to his inherent limitations and constraints ( ‘he does the best he can’). The result is both a normative

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16.5

model, starting from task objectives, and a descriptive model, including realistically HO functions and actions. NAVSIM provides a sufficiently detailed framework to describe systematically the complex interaction between the HO functioning and his task environment. The model components are: - ship dynamics and environmental variables as given by e.g. Eq. (3.2); the information that is available of the system from instruments and the outside world is given by the output vector Y, functionally related to the state and controls according to

Y(k) =gW(k),U(W,k);

(3.4)

- task definition as expressed by e.g. Eq. (3.3.); - HO functioning in terms of perception, information processing, decision making, planning and controlling; - model outputs in terms of statistical measures of system performance (providing all statistical information of the process) and HO workload measures. Perception of the present state and the future desired state (by looking forward) is associated with an inaccuracy (observation noise) which can be related to perceptual thresholds and the level and allocation of attention. The information perceived by the HO is used to estimate both the present state and the future desired state of the ship. This estimation process is modelled in terms of a Kalman filter. Based on the estimation process the sequential decision is made whether systematic changes in the desired state occur. This means that if, for instance, a turn must be executed this is envisaged in time so that the proper actions can be planned and executed. Once this decision is made, a pre-programmed manoeuvre is planned and executed to achieve the desired future state. In addition, deviations from the present desired state are compensated by means of a closed loop control to account for random effects. The NAVSIM model can be applied in port and fairway design, risk analysis, the evaluation of navigational aids and workload studies. 3.2.5. TRASIM model The TRASIM model describes the total vessel traffic control process. This implies a number of ships, with a given planned route, in a given confined area. The navigation of each ship is based on a planned route, which is updated via information of the visual scene, instruments and the vessel traffic services (VTS). Both normal operation and collision avoidance is modelled. The later implies the detection of a possible conflict by the navigator( s) and/or the VTS. Both the collision situations and the standard avoidance manoeuvres are strongly determined by procedures and rules. The ultimate criteria of the traffic process are safety and economy. Derived measures for these are collision risks (probabilities) and traffic flows. These are related to the following aspects, which are included in the model: ship dynamics, on board navigation instruments, visibility and environmental conditions, navigation aids, number of ships and their planned route, HO and VTS functioning. This involves visual perception, information processing, decision making and control (similar as in the NAVSIM model). The result is a stochastic, nonlinear, estimation and control problem.

166

1. Perdok. P.H. Wewerinke/Safety

“I ship

i

/

b /’

’

/

Science 19 (1995) 157-169

(relative

velocity)

/’

/

Tl j *“r

d /

Cl,

(closort

point

of approach) Fig. 2. Geometry of an encounter.

Normal operation amounts to steering the ship along the planned route (LQG control). The nonlinear dynamics of the (N) ships are modeled in a simplified form, assuming no drift, yet describing the main response characteristics, realistically. Based on perceived information the navigator estimates his own ship related state (Xi) and the state of other neighbouring ships (Xi) and the variables that are involved in the collision avoidance process Xij) .The latter variables describe the interaction between ships and are given by xij(k)

=.fij(Xi(k>,Xj(k)).

(3.5)

These nonlinear relationships imply a non-Gaussian probability distribution of X,. Instead of trying to find approximated filter equations based on the conditional probability distribution, in the model stochastic differential equations are derived for XVto obtain a minimum variance estimate of X, in terms of an extended Kalman filter. This is the same approach as taken for the estimation of the other ship states Xj. Collision avoidance is modelled by defining a dangerous encounter if the (estimated values of the) following three. iables are smaller than their corresponding criterion value: the distance aij between two ships, the closest point of approach cij (defined as the distance between the relative velocity vector and ship i) and the time Tij to reach the closest point of approach. This is clarified in Fig. 2. Thus. X, =col(aij,cv,Tv).

(3.6)

So we have an encounter if all elements of X, are smaller than the corresponding elements of the criterion X,. However, because X, is a stochastic process the navigator uses an estimate of Xti(X,). If all elements of X,j are smaller than their corresponding criterion

J. Perdok, P.H. Wewerinke/Safety Science 19 (1995) 157-169

values the decision (0,) is made that a collision by an action if ship i is burdened. Thus,

avoidance

161

situation is apparent followed

(3.7) Three types of encounters are distinguished each requiring a specific, pre-programmed, avoidance action: meetings, overtakings and crossings. The precise classification is depending on the relative positions and orientations of both ships. The evasive manoeuvre is characterized by a given lateral displacement and a given heading change. This standard manoeuvre is uniquely realized by a bang-bang control sequence wit a given maximum rudder angle. Various ways to model the VTS are possible. The simplest way is to assume that the navigator receives given (extra) observations from the VTS. A more advanced role of the VTS can be modelled assuming that the VTS will have information to estimate the total vessel traffic process, detect any conflict and advise or command the navigators (based on the same model concept as used for the navigators). The vessel traffic model is nonlinear because of the nonlinear equations of motion and the nonlinear estimation process. Therefore, no closed form expressions can be derived for statistical measures, such as collision probabilities. Thus the model must be used for time (Monte Carlo) simulations. For example, for typical (crucial or interesting) configurations time simulations can be made. The resulting trajectories can be considered and combined to obtain measures for collision probabilities and traffic flows. In addition, measures will be available for the effect of visual informational variables, or the effect of rules and procedures, on system performance and measures of navigator behaviour related to visual scanning, situation uncertainty and workload. The model can be applied to a variety of vessel traffic problems. It provides the structure to analyze the effect on safety and traffic handling of (among others) the following variables: ship dynamics, on board navigation instruments, visibility and environmental conditions, aids to navigation, navigator functioning, number of ships and routes in the traffic area, procedures and rules, role of the VTS, etc.

4. Model evaluation

and validation

In evaluating the use of simulation techniques in general, and of the foregoing models specifically, the starting point is which questions have to be answered, or which problems have to be solved. If these are related to human operator functions, such as perception and information processing of visual aids to navigation, of outside world cues and of instruments, then the NAVSIM model is required to simulate the corresponding tasks appropriately. If the questions are related to more complex manoeuvres than just track keeping with a constant forward speed, such as (un) berthing, mooring and turning, requiring tug boat manoeuvring in all possible directions, then the FORCESIM or TUGSIM model should be utilized.

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In addition, in case more advanced hydrodynamic ship models (than the Abkowitz model involved in SHIPMA) and more elaborate models of the environment and of the disturbances are required then a real-time simulator or the NAVSIM model, FORCESIM model or TUGSIM model should be used. In case it is not justified to assume that the deterministic disturbances are exactly known, the NAVSIM model is required to simulate such situations. In that case the disturbances (e.g. current) have to be estimated based on inaccurate measurements or other observations. The SHIPMA model can be used to get a first impression of manoeuvre capability. In case the ship dynamics and the environment are adequately modelled, SHIPMA can provide an upper bound on manoeuvring capability, i.e. if performance with SHIPMA is unacceptable the task has to be redesigned because in reality the performance will be equal or worse (because of human operator effects, etc.). However, in case the SHIPMA performance is acceptable, a more realistic simulation, is mandatory using NAVSIM or a real-time simulator. Validating complex simulation tools is the most important but also the most difficult issue: what is the meaning of the simulation results. Practically, it makes sense to show that the results are useful (to answer questions, etc.). The standard procedure for doing this is to analyze certain control tasks and to predict with the model system performance and other measures, which can also be measured in an (e.g. simulator) experiment. A certain agreement between model prediction and experimental results builds up some confidence one has in the model. Validating a real-time simulator is more?? A careful comparison with real-life experiments is difficult to perform. Typically a simulator is validated by checking simulator components and based on subjective opinion. Of the aforementioned models only the NAVSIM model results are supported by corresponding experimental results of 2 simulation programs (Wewerinke and Perdok,l990). In addition, parts of the model have been supported extensively in previous studies (Wewerinke et al., 1988). The SHIPMA model and the FORCESIM model are face validated, i.e. the results of several studies have been confirmed by nautical experts to be reasonable. The TRASIM and TUGSIM models have not been validated yet. 5. Concluding

remarks

In this paper training and research tools are reviewed to simulate ship handling. Real-time simulation with a real human being in the control loop comes closest to reality. It is a dynamic process in which the human factors, his possibilities and his shortcomings are fully taken into account. This includes the variability due to natural differences in the skills of pilots and ship masters. A real- time simulator is a standard tool for training purposes. One step further down the validity scale one finds man-machine models in which the ship dynamics and human functions are modelled. The models vary in the sense the different aspects of the manoeuvring task are modelled. The SHIPMA model is basically an autopilot to provide an upper bound on manoeuvring capability. The FORCESIM model describes more complex manoeuvring tasks utilizing tug boats. If tug boat manoeuvring per se is involved, the more advanced TUGSIM model should be used.

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The NAVSIM model deals extensively with human operator aspects of single ship operations. The TRASIM model involves human operator functions in the context of the complex vessel traffic process. Apart from normal ship operation (track keeping) this involves the interaction between ships (collision avoidance) and communication between ships and the vessel traffic services.

References Anon, 1990. Shipma4.30: A fast-time simulation program for ship manoeuvring. Manual Delft Hydraulics. Chadwick, Captain W.A., 1984. Marine casualties and how to prevent them, Trans IMarE( Vol. 96, Paper 46. Hove, D. ten, et al., 1990. Fast-time simulation models for the assessment of manoeuvring performance. Proc. 9th SCSS, Bethesda, USA. Marriot, John, 1987. Disaster at sea. Wewerinke, P.J. et al., 1988. Model of the human observer and controller of a dynamic system-theory and model application to ship handling. Proc. of the IEEE SMC Conference, Beijing, China. Wewerinke, P.H. and Perdok, J., 1990. Navigator-ship models for the assessment of manoeuvring performance and vessel traffic systems. Proc. MARSIM & ICSM 90, Tokyo, Japan. Wewerinke, P.H., 1991. A model of tug boat handling, MARIN report no. 53151-l-NP.