International Journal

on Marine Navigation

and Safety of Sea Transportation

Volume 4

Number 3

September 2010

265

1 NAVIGATIONAL KNOWLEDGE

1.1 Definitions

There is no consistent definition of both knowledge

in general and navigational knowledge. It is assumed

that knowledge is the total information about reality

and the capability to use it.

Intuitively, knowledge is understood as the ability

to behave in compliance with particular standards,

norms, regulations and good sea practice.

Navigational knowledge, in turn, is to be under-

stood as a set of data, facts, rules, procedures, strate-

gies and theories combined with the capability of

their interpretation and reasoning (Uriasz, 2008).

This knowledge allows the navigator to fulfill the

basic task of marine navigation, namely safe conduct

of a ship from one point to another in any situation.

This requirement also applies when the navigator’s

information is incomplete or unreliable.

1.2 Formal requirements

Navigational knowledge and associated competenc-

es are benchmarked and formally confirmed with

IMO-approved certificates. The International Mari-

time Organization, aiming at the global assurance of

the safety of navigation, sets forth minimum stand-

ards of professional competencies. These are con-

tained in the STCW Convention and the relevant

Code and constitute precise requirements for the

competencies including the real knowledge and

skills of seafarers and their task performance. The

Convention in detail defines certain areas of

knowledge, methods of its demonstration and as-

sessment. The provisions of the Convention are pe-

riodically revised and updated.

The defined areas of navigator’s competencies

make up a formal description that contains infor-

mation on the knowledge and its scope, its practical

use and methods of performing certain tasks and

methods of assessment.

1.3 Scope

Navigational knowledge can be considered from two

perspectives: competencies and tasks.

The former refers to the range of knowledge for

three levels as specified by the STCW Convention:

management, operational and support. The Conven-

tion itself, defining minimum competence standards

for performing various navigational tasks, specifies

knowledge standards for seven functions. These are

as follows:

– navigation,

– cargo handling and stowage,

– controlling the operation of the ship and care for

persons on board),

– marine engineering,

– electrical, electronic and control engineering,

– maintenance and repair,

– radiocommunication.

The minimum scopes of knowledge are thus de-

fined as necessary for the performance of these func-

tions.

Knowledge Representation in a Ship’s

Navigational Decision Support System

Z. Pietrzykowski & J. Uriasz

Maritime University of Szczecin, Szczecin, Poland

ABSTRACT: Supporting the navigator in decision making processes may substantially contribute to the en-

hancement of the safety in sea transport. The navigational decision support system supplements the existing

range of equipment and systems intended for sea-going ship conduct. One of the basic tasks of such systems

is an analysis of a navigational situation and solving collision situations. A well functioning navigational de-

cision support system should feature a decision-maker’s (navigator’s) knowledge representation. This refers

to both explicit knowledge - procedural, declarative, heuristic, and tacit knowledge - empirical associations.

The article presents assumptions of navigational knowledge base and its realization in the presently designed

navigational decision support system.

266

The latter perspective – task-based – simply re-

sults from the overall transport objective: carriage of

cargo and people (voyage planning, loading, passage

to the destination, unloading). To execute the above

tasks one needs formalized i.e. acquired knowledge

(defined, recognized facts, relationships, interrela-

tions etc.) and, the most important, empirical associ-

ation, that is knowledge acquired through practice

and professional experience.

2 SYSTEM OF NAVIGATIONAL DECISION

SUPPORT

2.1 Assumptions

The determination of navigators’ competencies is

strictly related with the assurance of minimum level

of safety in shipping. However, satisfaction of these

requirements does not eliminate the most common

cause of marine accidents – human error. The con-

struction of decision support systems broadens op-

portunities for the reduction of such errors. Apart

from a proper situation display, the function of deci-

sion support systems is to automatically analyze and

assess a situation and to work out (generate) ma-

noeuvres recommended to the navigator for perfor-

mance. One such solution comes from the Maritime

University of Szczecin, where a navigational deci-

sion support system is being developed (Pietrzykow-

ski et al. 2007).

The basic tasks for the system being designed in-

clude:

– automatic acquisition and distribution of naviga-

tional information,

– analysis of a navigational situation and avoidance

of collision situations,

– interaction with the navigator.

The system should allow for the following tasks:

– signaling dangerous situations and the present

level of navigational safety based on the criteria

used by expert navigators,

– automatic determination of one or more manoeu-

vres and trajectories of ship movement in colli-

sion situations,

– possibility of explaining (justifying) of the pro-

posed manoeuvre,

– display of a navigational situation clear for the

navigator.

The navigational decision support system is in-

tended as supplementary to the conventional ship-

board equipment. Its correct operation depends on

the compatibility with ship’s devices and systems.

The standard ship equipment includes: log, gyro-

compass, radar, echosounder, ARPA (Automatic

Radar Plotting Aids), GNSS (Global Navigational

Satellite System), e.g. GPS (Global Positioning Sys-

tem), DGPS (Differential Global Positioning Sys-

tem), AIS – (Automatic Identification System), EC-

DIS (Electronic Chart Display and Information Sys-

tem), GMDSS – (Global Maritime Distress and

Safety System).

There should be a possibility of adding naviga-

tional information from other sources, such as the

Vessel Traffic Service (VTS).

The idea of constructing a navigational decision

support system goes in line with current directions

of developments in marine navigation, including e-

navigation. As put in (IMO, NAV 53/13, 2007) E-

navigation is the harmonized collection, integration,

exchange, presentation and analysis of maritime in-

formation onboard and ashore by electronic means

to enhance berth to berth navigation and related ser-

vices, for safety and security at sea and protection of

the marine environment”. Therefore, navigational

system of decision support will be a component of

an e-navigation system.

2.2 System architecture

The system under design is one operating in real

time. Its tasks include observation of the ship and

the environment, registration of navigational infor-

mation, its selection, retrieval, verification and pro-

cessing. The navigator will be presented with the

outcome of system processing – information such

the identification and assessment of a navigational

situation and suggested solutions (decisions) provid-

ing for safe navigation.

The system’s general architecture is shown in

Figure 1 (Pietrzykowski et al. 2008).

Fig. 1. Architecture of the navigational support system on a sea

going vessel

For the implementation of the tasks mentioned in

section 2.1. we need to use the knowledge of expert

navigators.

Vessels in area Voyage data

Module of interaction with navigator

Detection

Module assessment

Situation assessment Knowledge base: COLREGs

Decision on manoeuvre

area traffic

data

voyage plan, navigator's

preferences, limitations

decisions situation info

trajectory

situation data

enquiry

rules

trajectory

voyage plan

situation

data, rules

assessment

267

2.3 Object of implementation

The system prototype is being tested onboard the re-

search/training vessel Nawigator XXI, operated by

the Maritime University of Szczecin. Its basic pa-

rameters are as follows:

– length overall – 60.21 m,

– beam – 10.50 m,

– draft – 3.15 m,

– service speed – 13 knots.

The vessel has the following navigational equip-

ment and systems :

– GPS:

• CSI MiniMax (DGPS),

• Koden KGP-913D,

• Trimble NT200D (DGPS),

– gyro: Anschutz STD22,

– AIS: Nauticast X-Pack DS,

– radar/ARPA:

• JMA 5300,

• Kelvin Hughes NINAS 9000,

– ECDIS: -AG Neovo,

– echosounder: -Skipper GDS 101,

– log: Sperry SRD-421 S.

The ship’s equipment provides navigational data

needed by the navigator to make the right decisions.

The data, after integration, make up a basis for the

decision support system operation, i.e. analysis and

assessment of a navigational situation and the sug-

gestion which collision avoiding manoeuvre should

be performed.

3 KNOWLEDGE IN THE NAVIGATIONAL

DECISION SUPPORT SYSTEM

3.1 Types and scope of knowledge

The requirements for the scope of navigators’

knowledge comprise procedural knowledge – proce-

dures formulated by experts – and declarative

knowledge – of descriptive nature, covering sets of

facts, statements and rules.

Procedural knowledge, referring to the principles

of behaviour, is mainly contained in all kinds of

rules and regulations.

Declarative knowledge, acquired by navigators in

the course of studies, training courses and on board

ship service, is related with both analysis and as-

sessment of situations and the principles of naviga-

tor’s behavior.

Both procedural and declarative knowledge is

based on theories of various fields and scientific dis-

ciplines, navigation in particular.

Taking the system assumptions into account (sec-

tion 2.1) as well as knowledge standards which are

to be fulfilled for various functions to be performed,

as defined under the STCW Convention (section

1.3), we decided to limit the knowledge implement-

ed in the system to the function of navigation (prob-

lem 1). This knowledge includes two basic layers:

1) planning of a voyage route based on shipowner‘s

shipping-related decisions – weather routing,

2) ship movement control accounting for the moni-

toring of the safety of navigation:

– determination of safe course and speed for a

present navigational situation bearing in mind

the goals defined in layer 1,

– performance of manoeuvres – rudder and en-

gine settings according to the determined val-

ues of the course and speed.

The planning of voyage route is aimed at meeting

shipowner’s goals. Such planning has to take into

consideration the present and forecast hydrological

and meteorological conditions (access to weather in-

formation) and the knowledge in this respect. Also,

the planning process is time-consuming as it requires

a lot of calculations. Although it can be done

onboard, the task is often ordered to specialized

land-based centres. Therefore, we assumed that the

planning task will be taken into consideration in fur-

ther stages of development of the navigational deci-

sion support system.

Safe conduct of a vessel following the determined

values of course and speed in a given navigational

situation is the process that may be divided into sev-

eral phases:

1 vessel detection and identification,

2 analysis and assessment of the situation,

3 defining the method of solving a collision situa-

tion – choice of a preventive manoeuvre – (ma-

noeuvres of course and/or speed alteration),

4 determination of manoeuvre parameters, includ-

ing the moment to start,

5 performance of a preventive (collision avoiding)

manoeuvre,

6 monitoring of the ship conduct process.

The execution of the phases by a navigator re-

quires that s/he has procedural and declarative

knowledge as well as the knowledge resulting from

the theories of scientific disciplines and fields mak-

ing up the principles of navigation. The knowledge

represented in the decision support system should

assure that each stage of safe ship conduct is ade-

quately performed. The implementation of this

knowledge requires that its sources, methods of ac-

quisition, representation and use are defined.

3.2 Sources of knowledge and methods of its

acquisition

Sources of knowledge for a decision support system

are scientific theories and declarative knowledge ac-

quired by navigators during their studies, additional

courses and sea service. These make up a basis for

systematic principles of behaviour developed in the

268

form of regulations, recommendations and proce-

dures (procedural knowledge).

Procedural knowledge is particularly useful for

such aim as knowledge implementation in the deci-

sion support system (Pietrzykowski, 2004). Supple-

mented with methods, tools and techniques offered

by scientific theories covering such areas as naviga-

tion, mechanics, hydrodynamics and control, it ena-

bles making right decisions to assure the safety of

navigation. However, the complex character of sys-

tems and real processes and inaccuracies or impreci-

sions in their description make it necessary to take

into consideration the knowledge resulting from

navigators’experience (declarative knowledge). It

mostly has a descriptive nature and is often ex-

pressed through sets of facts (premises and implica-

tions). In this approach the knowledge comes from

expert navigators.

Procedural knowledge, among others, is con-

tained in official regulations, such as the Collision

Regulations or local regulations – in many cases the-

se are very general and their scope of interpretation

can be wide indeed. A valuable source of this

knowledge are handbooks on seamanship or the the-

ory of ship handling, including information, recom-

mendations and procedures as well as interpretation

of regulations prepared on the basis of long time sea

service of mariners.

Navigators’ declarative knowledge is more diffi-

cult to be put into a formal framework. Its main

source are facts relating to a specific issue. Such

facts are obtained by a variety of research methods:

– field studies:

• observations (passive)

• experiments (active)

– model-based research:

• physical (based on material models),

• mathematical.

Model-based research is particularly useful when

combined with computer-aided simulation methods.

The advantage of such research is due to difficulties

of real field studies: high costs, limited possibility of

registration of varied situations, while in the case of

new projects there is no such possibility at all.

In knowledge acquisition, expert studies are an

important option. Expert studies can be performed in

the form of questionnaires or simulations with ex-

perts as participants.

The above mentioned methods have to be sup-

plemented with analytical, statistical and artificial

intelligence methods that are needed to identify rela-

tionships and dependencies in sets of facts collected

by the methods in question. For this reason, artificial

intelligence methods, tools and techniques are of

particular interest: machine learning, artificial neural

networks, fuzzy systems or evolutionary algorithms.

These techniques allows to work out a representation

of knowledge in the decision support system: direct-

ly (e.g. machine learning, artificial neural networks)

or indirectly (fuzzy systems, evolutionary algo-

rithms).

Various types of knowledge and the complexity of

problems connected with its acquisition make it nec-

essary to use a group or groups of methods.

The following sources and/or methods have been

defined for each phase of safe vessel conduct (see

section 3.2):

1) detection and identification of a vessel (including

parameters of its movement):

− analytical methods (verification, selection and

integration of navigational data),

− artificial intelligence methods (estimation of

the state vector of another vessel)

2) situation analysis and assessment:

− analytical methods (algorithmization of

COLREGs)

− analytical methods – closest point of approach

(CPA) and time to CPA

− expert methods – questionnaires, and statistical

methods (situation assessment criteria)

− simulation methods with experts’ participation

and statistical methods (situation assessment

criteria)

3) pointing out the method for collision situation

avoidance – choice of a preventive manoeuvre;

− analytical methods (algorithmization of

COLREGs, classical optimization algorithms)

− artificial intelligence methods (fuzzy systems,

genetic algorithms);

4) determination of manoeuvre parameters

− analytical methods (classical computational

algorithms, including optimization algorithms)

− artificial intelligence methods (fuzzy systems,

genetic algorithms)

5) performance of a preventive (anti-collision) ma-

noeuvre

− analytical methods (classical control algo-

rithms)

− artificial intelligence methods (fuzzy systems)

6) monitoring of ship conduct process:

− analytical methods (prediction of vessel

movement).

The use of the above methods allows to acquire

and implement (representation and use) of naviga-

tors’ knowledge in the decision support system for

safe vessel conduct.

269

4 REPRESENTATION AND USE OF

KNOWLEDGE IN THE DECISION SUPPORT

SYSTEM

4.1 Knowledge representation

The acquired knowledge should be recorded in

forms suitable to its purpose or method of utiliza-

tion. The following methods of representation can be

applied:

Database structures. Databases allow to gather

sets of data and to record them in a specified manner

for the adopted model. They enable efficient edition

of data, their updating, archiving and further pro-

cessing. Database applications in navigation get in-

creasingly wider as information technologies are

constantly being advanced. One such example is

VDR, voyage data recording. Various facts of a giv-

en voyage may be used in the process of knowledge

supplementing (situations and manoeuvres per-

formed by navigators). Another example is the con-

ception of WEND - Worldwide Electronic Naviga-

tional Chart Database (Hecht, 2007).

The electronic navigational chart represents a

basic source of knowledge on a given water area and

essentially complements the navigator’s knowledge.

Its database form enables a choice of the appropriate

layers of vector data for the execution of navigation-

al tasks (see 3.1)

Rules and decision trees. Rules represent the

knowledge defining the conditions for assigning reg-

istered facts to distinguished classes: they define

premises, implications and conclusions. Decision

trees execute a similar task. They enable solving a

classification problem for two or more classes.

Both rules and decision trees constitute such a

form of knowledge that is well implemented in ex-

pert systems. Decision trees allow to describe the

decision process – reasoning.

Decision tables. Another useful form of record-

ing knowledge is its representation as logical deci-

sion tables. The table contains a description of a de-

cision situation (DS), which is defined as a set of

ordered threes:

( )

udz

fHU ,,

(1)

where,

– set of possible actions,

H – set of possible results of actions,

– utility function defined on the Cartesian

product.

In marine navigation it is justified to use this

method of knowledge representation, as it enables

not only foreseeing the results of a particular deci-

sion but also, more importantly, adjusting the right

actions to the planned result.

Neural networks. These are mathematical struc-

tures able to process signals. Their operation is

based on the reproduction of processes taking place

in brains of living organisms. In the construction of

a neural network, one has to define the network

structure, then to carry out the learning process re-

sulting in the correct operation of the network, with

a maximum adopted error. Neural networks find ap-

plications in approximation problems, image recog-

nition, forecasts, selection, optimization etc.

Algorithms. An algorithm is a convenient and

clear-cut method of knowledge recording. In fact, it

is a detailed procedure for solving a problem. Recur-

rent algorithms in particular are very close to natural

behaviour of the human being by allowing to present

part of a problem instead of the whole. When in op-

eration, the algorithm refers to itself until a solution

to the problem is reached. Most problems in naviga-

tion are solved in a recurrent method, e.g. voyage

planning and passage, planning and performance of

a SAR operation, vessel detection and identification.

Typical computational algorithms, including optimi-

zation algorithms, are an important group. They rep-

resent theoretical knowledge that allows to solve

specific computation problems, e.g. determination of

ships encounter parameters or parameters for per-

forming a manoeuvre.

4.2 Utilization of knowledge in the decision support

system

The system supporting navigator’s decisions has to

have the right scope of knowledge indispensable for

its functioning. The knowledge recorded in the sys-

tem will be represented in forms mentioned in sec-

tion 4.1; these are in particular:

− database structures – in this form the system in-

cludes navigational cartographic information. The

information, satisfying IHO standards, will make

up a basis for presenting current navigational in-

formation. All manoeuvre recommendations will

account for the vicinity of dangers to navigation.

− rules and decision trees – the navigator keeping a

navigational watch does a number of actions: car-

ries out observations, assesses present naviga-

tional situations, plans and performs manoeuvres.

During these actions the navigator has to classify

surrounding conditions and encounter situations

by assigning them to various groups, which imply

the application of different rules provided by in-

ternationally recognized collision regulations

(COLREGs). The classification rules - principles

used for this purpose in decision support systems

may provide a relevant classification as well as

contribute to the development of comparable cri-

teria for classification used by navigators. This

refers to special cases when the classification is

based on incomplete or inaccurate information.

− decision tables – such record of knowledge will

contain information on manoeuvres – their pa-

rameters, starting moment and effects. The navi-

270

gator will be left to decide on which manoeuvre

to choose (its type and parameters).

− neural network – this will be used for the assess-

ment of navigational safety in an encounter with

other vessels; such assessment will take into ac-

count the parameters of vessels encountered. It al-

lows to determine an area around the ship that

should be maintained clear of other objects - ship

domain (Pietrzykowski & Uriasz, 2009). The

network will also be used for the determination of

collision avoiding manoeuvres. As a universal

approximating device, it will also be utilized in

the process of state vector estimation of other

vessels.

− algorithms – in the decision support system,

among others, the interpretation of COLREGs is

presented in the form of an algorithm. Based on

recurrent algorithms, such operations as vessel

acquisition or information decoding is executed.

Complex computational algorithms have been

used in the integration of navigational data from

various shipboard devices and systems. Standard

computational algorithms as well as complex op-

timization algorithms are used for selecting ma-

noeuvres and their parameters.

5 CONCLUSIONS

As the types and scopes of navigators’ knowledge

and the methods of its acquisition and representation

are varied, different forms were used for knowledge

implementation and utilization in the decision sup-

port system.

The created knowledge base has a distributed na-

ture. It includes the knowledge used in each stage of

the process of navigation, or ship conduct.

The decentralized structure of the knowledge

base make possible both supplements in terms of

scope and representation forms. It can be comple-

mented with navigators’ knowledge in the area of

voyage planning, and subsequently, it may cover the

other six functions (apart from navigation) specified

in STCW competence standards for enhanced per-

formance of specific tasks.

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