A study on the effects of e-navigation on reducing
vessel accidents

ABSTRACT
Title of Dissertation: A Study on the Effects of e-Navigation on Reducing
Vessel Accidents
Degree: MSc
The dissertation aims to evaluate how and to what extent e-navigation contributes
to reducing accidents for SOLAS ships as well as non-SOLAS ships, hoping that
the results are referred to IMO Member States when they are implementing enavigation along with the maritime sectors such as shipping companies, crews on
board ships and manufactures developing e-navigation related systems.
The study focuses on the potential effects of e-navigation based on tool kits of the
IMO e-navigation for SOLAS ships and services of SMART-navigation, which is
the Korean approach to implementing the e-navigation concept for both SOLAS
ships and non-SOLAS ships. The processes and the methodologies that are used by
the IMO to assess the effects of e-navigation are investigated. The vessel accidents
for all ships in Korean waters and all Korean-flagged ships worldwide during the 5
years from 2009 to 2013 are analyzed. The formula is proposed to calculate the
effects of e-navigation on reducing accidents, which can also be used by other
Member States of the IMO when they implement e-navigation in their waters. The
direct causes of accidents, which are reducible by the risk control options (RCOs),
and the RCOs, which are applicable to non-SOLAS ships, are identified.
Additionally, an expert questionnaire survey is carried out with a view to
supporting the validity of identifying the RCOs and the direct causes. The results
are collated and evaluated for the potential effects of e-navigation on reducing
accidents, in relation to type of accidents as well as type of ships, for comparison
with the results obtained by the IMO and for reference of other Member States.
The concluding chapter examines the results of analysis of e-navigation’s tool kits
and methodologies to assess their effects on reducing accidents, and discusses the
potential rate of accident reduction through e-navigation. A number of
recommendations are made concerning the need for further investigation in
quantifying the coefficient applied to the proposed formula for evaluating the
effects of e-navigation.
KEY WORDS : Bayesian Network, Human Error, E-navigation, Maritime Service
Portfolios, Navigational Accidents, Rate of Risk Reduction, Risk Control Options,
Safety of Navigation, SMART-navigation, Strategic Implementation Plan
v
TABLE OF CONTENTS
DECLARATION ii
ACKNOWLEDGEMENTS iii
ABSTRACT iv
TABLE OF CONTENTS v
LIST OF TABLES vii
LIST OF FIGURES viii
ABBREVIATIONS ix
1. INTRODUCTION 1
1.1 Background 1
1.2 Objectives 7
1.3 Scope of the Study 8
1.4 Methodology and Sources of Information 9
2. TOOL KITS OF IMO E-NAVIGATION TO REDUCE ACCIDENTS 11
2.1 Overview of IMO e-navigation 11
2.1.1 History of developing e-navigation 11
2.1.2 Strategic Implementation Plan (SIP) of IMO 15
2.1.3 Identifying user needs 19
2.1.4 Analyzing human errors that cause accidents 22
2.2 Main tool kits of IMO e-navigation 26
2.2.1 The e-navigation solutions 26
2.2.2 Risk Control Options (RCOs) 29
2.2.3 Maritime Service Portfolios (MSPs) 30
2.3 Conclusion of the tool kits of e-navigation 31
3. METHODOLOGY TO EVALUATE THE EFFECTS OF E-NAVIGATION 37
3.1 Introduction 37
3.2 Methodology used in the FSA for IMO e-navigation 37
3.3 Methodology to be used in the dissertation 43
3.3.1 Conclusion of the methodology 43
vi
3.3.2 Limitation in the methodology and Bayesian Network (BN) 45
4. ANALYSIS OF KOREAN-RELATED ACCIDENTS (2009-2013) 48
4.1 Introduction 48
4.2 Analyzing accidents 50
4.2.1 Historical trends of accident volume 50
4.2.2 Historical trend of accident types 51
4.2.3 Direct causes of accidents 52
5. DISCUSSION OF THE EFFECTS OF E-NAVIGATION 62
5.1 Development of the formula to evaluate the effects of e-navigation 62
5.2 The SMART-navigation concept 65
5.2.1 Background of SMART-navigation 65
5.2.2 Components of the SMART-navigation 66
5.2.2.1 Main services of the SMART-navigation 66
5.2.2.2 SMART-navigation Services for non-SOLAS ships 68
5.2.3 Architecture of SMART-navigation 68
5.3 Accident reducing effects of SMART-navigation 71
5.3.1 Discussion of detailed direct causes reducible by RCOs 71
5.3.2 Discussion of RCOs applicable to non-SOLAS ships 74
5.3.3 Expert survey by questionnaire 75
5.3.4 Effects of reducing navigational accidents by SMART-navigation 77
5.3.4.1 Rate of risk reduction 77
5.3.4.2 The effects of reducing accidents 81
6. CONCLUSION 84
REFERENCES 92
APPENDIX 99
vii
LIST OF TABLES
Table 1 Time framework for implementing SIP (MSC 85/26) 13
Table 2 Time framework for eighteen tasks to implement SIP 15
Table 3 Potential e-navigation users 20
Table 4 Number of events and loss of life 23
Table 5 Composition of events and loss of life 24
Table 6 Description of Solution and its Sub-Solutions 27
Table 7 List of the Maritime Service Portfolios (MSPs) 30
Table 8 Relation between Tool kits of e-navigation to reduce accidents 33
Table 9 Accident frequencies 38
Table 10 Risk estimations 39
Table 11 Total generic risk distributed among accident causes 40
Table 12 Risk reducing potential 41
Table 13 Estimated reduction potential of PLL per ship 42
Table 14 RCOs ranked by PLL 43
Table 15 Calculation process of risk reduction rate by the FSA team 44
Table 16 Ship types included in the dataset 49
Table 17 Historical trend of accidents by ship’s type 50
Table 18 Accident type distribution 51
Table 19 Direct cause distribution by accident type 53
Table 20 Direct cause distribution 54
Table 21 Human error cause distribution 55
Table 22 Technical failure cause distribution 57
Table 23 External factors distribution 59
Table 24 Inadequate handling machinery or cargo cause distribution 60
Table 25 Other Factors Distribution (Korea related) 61
Table 26 Main services of the SMART-navigation 66
Table 27 Communication networks around the Korean coastal water areas 70
Table 28 Identified detailed direct causes 73
Table 29 RCOs for non-SOLAS ships 75
Table 30 Rate of reduction of direct causes by RCOs 77
Table 31 Actual rate to reduce the direct cause of the navigational accidents 78
Table 32 Human error cause distribution 79
Table 33 Technical failure cause distribution 80
Table 34 External factors distribution 80
Table 35 Apparent effects on reducing accidents by the SMART-navigation 81
Table 36 SOLAS and non-SOLAS ship distribution among accidents ships 82
Table 37 Effects on reducing accidents by the SMART-navigation 83
viii
LIST OF FIGURES
Figure 1 Steps of FSA used in developing the SIP 17
Figure 2 Overarching e-navigation architecture 19
Figure 3 Methodology to identify the direct causes of accidents 23
Figure 4 Human error cause distribution 24
Figure 5 Technical failure cause distribution 25
Figure 6 External factor cause distribution 25
Figure 7 RCO identification process 29
Figure 8 Historical trend of accidents by ship’s type 50
Figure 9 Accident type distribution (2009-2013) 52
Figure 10 Methodology to identify the direct causes of accidents 53
Figure 11 Direct cause distribution by accident type (2009-2013) 54
Figure 12 Human error cause distribution of navigational accidents 56
Figure 13 Human error cause distribution of all accidents 57
Figure 14 Technical failure cause distribution 58
Figure 15 External factors distribution 59
Figure 16 Inadequate handling machinery or cargo cause distribution 61
Figure 17 Concept of service for non-SOLASe ships 68
Figure 18 Overall architecture of the SMART-navigation (MOF,2015) 69
Figure 19 Communication architecture for the SMART-navigation 71
ix
LIST OF ABBREVIATIONS
The following abbreviations are used in the dissertation:
ABS American Bureau of Shipping
AIS Automatic Identification System
AtoN Aids to Navigation
BN Bayesian Network
CG Correspondence Group
CMDS Common Maritime Data Structure
COMSAR Radio-Communications and Search and Rescue Sub-Committee
DMA Danish Maritime Authority
DNV Det Norske Veritas
EC European Commission
ECDIS Electronic Chart Display and Information System
EU European Union
FSA Formal Safety Assessment
GL Germanischer Lloyd
HEAP Human Element Analyzing Process
IALA International Association of Marine Aids to Navigation and
Lighthouse Authorities
IFSPA International Forum on Shipping, Ports and Airports
IHO International Hydrographic Organization
IHS Fairplay Database Provided by Information Handling Service Enterprize
IMDG International Maritime Dangerous Goods Code
IMO International Maritime Organization
ITU-R International Telecommunication Union Recommendation
KMST Korea Maritime Safety Tribunal
LTE M Long Term Assessment – Maritime Communication Network
MOF Ministry of Oceans and Fisheries, Republic of Korea
MSC Maritime Safety Committee of IMO
MSP Maritime Service Portfolio
NAV Sub-Committee on Safety of Navigation of IMO
NCSR Sub-Committee on Navigation, Communications and Search
NMA Norwegian Maritime Authority
NTSB National Transportation Safety Board
PLL Potential Loss of Life
PNT Data Position, Navigation and Time date
RDANH Royal Danish Administration of Navigation and Hydrography
TRANSNAV International Journal on Marine Navigation and Safety of Sea
x
Transportation
RCO Risk Control Option
SAR International Convention on Maritime Search and Rescue (SAR)
SIP Strategic Implementation Plan
SMART-Navigation Korean Approach of Implementing the e-Navigation Concept
SOLAS International Convention for the Safety of Life at Sea,1974
STW Standards of Training and Watch-keeping Sub-Committee
VDE VHF Date Exchange
VTS Vessel Traffic Service
WG Working Group
WWRNS World Wide Radio Navigation System
1
1. INTRODUCTION
1.1 Background
The International Maritime Organization (IMO), ever since it was established, has
focused on preventing vessel accidents by enacting minimum safety standards for ships
and crews on board. As a result, there are now very few accidents caused by technical or
machinery problems in the ship structure itself.
However, accidents still happen mainly due to human error, which is one of the most
important issues concerning global maritime communities. For example, Rothblum
(2012) demonstrated that more than 75 % to 96 % of maritime accidents are caused by
human error. Barsan, Surugiu and Dragomir also demonstrated that more than 80% of
maritime accidents are caused by human error (TRANSNAV, 2012). Further, these
accidents indicate a rising trend as examined in paragraph 2.2.2 of this dissertation.
Human error is mainly rooted in fatigue, the lack of situational awareness and the safety
culture of crews on board ship (Carter-Trahan, 2002)
1
. There have been limitations to
prevent human error in terms of quantity and quality of information, complexity, lack of
providing decision making support to help avoid dangerous navigational situations, and
lack of response to emergency situations in a timely and adequate manner. One of the
reasons of these limitations might be the quantitative limitation of the current analog-

1
The author, Alicia C, shows examples of human errors in his dissertations, An examination of the
human factors attitudes and knowledge of surface warfare officers (Chapter 4, page 10-14)
2
based maritime communication network and the different types of information used in
each piece of navigational equipment on board ships as well as between ships and shorebased stations. This assumption is clearly supported by the user needs, which reflect the
concerns that they experience most often during their work, according to a survey on enavigation as shown in the IMO document NAV 55/INF. 9.
With regard to human error, the other point that the author would like to recall is
Reason’s SWISS Cheese Model which visualizes a number of barriers between existing
hazards and a potential accident. However, the question why accidents occur – even
though many layers of safety barriers, including Helpance and decision support systems,
might be installed – remains. Of course, there are holes in each of the layers that, if
aligned, can allow an accident to occur (Hollnagel, Schröder-Hinrichs & Baldauf, 2012).
Obviously, it can be interpreted that an accident could be prevented if one of the holes
among the defense layers was blocked.
For example, this is clearly supported by Wagenaar W.A and Groeneweg J (1987)2
,
introducing that most accidents are caused by multiple reasons that are combined
together, ranging up to 58 types of reasons. They demonstrated that more than 96 % of
accidents involve human error, and more than 93 % of accidents involve the
combination of a number of human errors. The important point from the findings above
is that each human error in an accident acts as one of the conditions to cause the
accident, which means that an accident caused by combined multiple human errors
might be preventable if one of the errors had been eliminated in advance and the chain
had been blocked (Rothblum, 2012).

2 With regard to this, for detail information, see paragraph 4(p. 594) and Table 4, “Classification of
human errors in 100 accidents at sea, according to Feggetter’ s classification system” (p. 595) of the
article, “Accidents at sea: Multiple causes and impossible consequences” (Wagenaar W.A and
Groeneweg J., 1987)
3
With regard to this, IMO has also been making efforts to reduce human error (Etman &
Halawa, 2006)3
. As one of its latest efforts, IMO has been preparing for the introduction
of e-navigation. This initiative began in 2006, and IMO finally adopted the Strategic
Implementation Plan (SIP) for implementing e-navigation into the maritime sectors4
.
The concept of e-navigation is defined, in Annex 20 of MSC 85/26 Add.1 (para. 1.1), as
follows:
The harmonized collection, integration, exchange, presentation and analysis of
marine information on board and ashore by electronic means to enhance berth to
berth navigation and related services for safety and security at sea and
protection of marine environment.
This might mean that one of the global aims of e-navigation is to digitalize the current
analog-based navigational equipment on board ships in order to reduce human error by
providing much more safety information and reducing the burden on crews with regard
to handling paper work regardless of the safety of navigation. In addition, it may solve
the complexity 5
of navigational equipment and the lack of decision making by
supporting crew members to avoid the dangerous situation on the ship’s bridge.
In more detail, e-navigation is to enhance the safety of navigation by reducing these

3
They explained as “IMO gave attention to the human element of daily ship operation and ship
management” (para. 4), and, as examples for that, listed the human error-related documents developed
by IMO in their paper, “Safety culture, the cure for human error : A critique” (para. 4), such as Res.
A.850 (20), A.947 (23) and A.900 (21) as well as the STCW Convention, the ISM Code and the IMO
Casualty Investigation Code (para. 4)
4
With regard to maritime sectors, it might include the potential e-navigation users in Table 1 of this
dissertation. The users were identified and defined in the IMO document, MSC 85/26 Add.1 Annex 20.
5
With regard to this, the e-navigation solutions, which were identified based on user needs, for example,
solution 1 (improved, harmonized and user-friendly bridge design), solution 2 (means for standardized
and automated reporting), and solution 4 (integration and presentation of available information in
graphical displays) might contribute to solve this complexity. (See Table 4 in para. 2.2.3 for details).
4
kinds of human errors, or avoiding them in advance through its tool kits such as 7 kinds
of Risk Control Options (RCOs) and 16 kinds of Maritime Service Portfolio (MSPs).
With these tool kits of e-navigation on board ship or support from the shore-based
station, a dangerous situation, which might potentially lead to an accident, could be
prevented or corrected in advance by monitoring a ship’s routing, informing the ship of
much more safety information, and warning of dangerous situations.
In addition, because of the evolution in the communication network between ships and
the shore side, e-navigation could greatly improve the efficiency
6
of maritime activities.
For example, the more modernized and standardized information and communication
technology of e-navigation such as the globally standardized and automated ship-shore
reporting system7
and the seamless transmission of electronic information and data
between ship and shore, would allow the IMO to address the efficiency of maritime
related business as well as the safety of navigation. Thus, IMO is able to talk about the
safety and efficiency of navigation at the same time, which was generally not possible in
the past.
The effect of modernized and standardized communication technology as a tool to
increase efficiency is clearly supported by the European Commission’s (EC) e-maritime
project. The project was initiated in order to increase the efficiency of using the
resources and to promote the competitiveness of maritime sectors (e-maritime, 2012) by

6
The IALA (2011) introduces “the higher efficiency and reduced costs enabled is one of the main broad
benefits of e-navigation” (para. 6, p. 3, e-Navigation Frequently Asked, 2011) .
7
With regard to this, NAV 59/6 Annex 1 comments “An investigation undertaken by the MarNIS project
of 15 European ports found that around 25 documents had to be sent from the ship, or the ship’s agent,
in conjunction with a port call ” (p. 25, para. 7.2.4
5
the DIRECTIVE 2010/65/EU, and the DIRECTIVE emphasized8
smooth and effective
communication as the key element of the project.
Then, how and to what extent could e-navigation reduce such human error that causes
accidents? This would be an important question to the stake-holders involved in the
implementation of e-navigation such as Governments, shipping companies, shipyards
and the relevant equipment manufacturers, and even crews on board ships. It could also
contribute to maximizing the benefits of e-navigation in terms of effectiveness and
efficiency when it is introduced and applied to the existing business processes of the
maritime sector.
With regard to this, IMO’s formal safety assessment (FSA) was carried out by Det
Norske Veritas (DNV, Norway) and Germanischer Lloyd (GL, Germany) for the enavigation SIP before it was approved by the Maritime Safety Committee (MSC) at its
95th session in 2014, including the risk and cost-benefit analysis, as set out in the IMO
documents, NAV 59/6. Annex 1 (2013) and NCSR 1/28 (2014). Annex 7. According to
these documents, more than 65 % of the direct causes of ships’ navigational accidents,
including collisions and groundings, caused by human error (p15) could be reduced by 7
kinds of risk control options (RCOs) of e-navigation.
However, even though the IMO document NAV 56/9. Annex 1 and NCSR 1/28. Annex
7 provide the feasibility of introducing e-navigation in terms of the cost-benefit as well
as the effect on reduction of navigational accidents for SOLAS ships by up to 52.7%
9
,

8
With regard to this, the DIRECTIVE 2010/65/EU described as “The full benefits of electronic data
transmission can only be achieved where there is smooth and effective communication between
SafeSeaNet, e-Customs and the electronic systems for entering or calling up data” (para. 12).
9
65 % means the rate to reduce the percentage of each detailed direct cause, which is reducible by 7
kinds of risk control options (RCOs), involving navigational accidents, while 52.7% is the actual rate
6
which is 22.8% among total accidents including other accidents as well as navigational
accidents, the author assumes that the practices to introduce e-navigation would be
different among different countries in terms of their priorities, levels and methods of
applying it in their water areas. This is because the situation of each country’s maritime
safety would be different. Further, non-SOLAS ships might be important factors needed
to be taken into account implementation of e-navigation because SOLAS ships are
always interfaced with non-SOLAS ships in real maritime practices.
Therefore, it is important for a country to analyze its own specific data of vessel
accidents for all ships in its waters and its flagged vessels worldwide, and assess the
effects of e-navigation in terms of accident types and ship types, including non-SOLAS
ships as well as SOLAS ships. This would lead the country to maximize the benefits of
implementing e-navigation in its water areas by establishing an effective and efficient
National SIP.
For this reason, the author analyzes the vessel accident data for all ships in Korean water
areas and all Korean-flagged ships worldwide over the period 2009 to 2013, and
develops a formula to evaluate the effect of e-navigation, which can be also used by
other Member States of the IMO.
Then, the author evaluates the potential effects of SMART-navigation, which is the
Korean approach to implementing the e-navigation concept, on reducing accidents by
applying the formula with various approaches such as SOLAS ships and non-SOLAS
ships, fishing vessels and non-fishing vessels, and navigational accidents and nonnavigational accidents. The results could be an example to evaluate the effects of enavigation by other countries when they are introducing e-navigation to their waters.

to be reduced among navigational accidents, by implementing e-navigation tool kit application, the 7
kind of RCOs. See paragraph 5.1 for detailed calculation method.
7
1.2 Objectives
This dissertation researches the potential effects of e-navigation on reducing vessel
accidents. It mainly includes studies and discussion on how and to what extent enavigation could possibly reduce vessel accidents.
It is hoped that the result of this study might be referred to the maritime safety policies
of the Member States of IMO when they are introducing e-navigation, as well as to the
practices of the private maritime sectors such as shipping companies, crews on board
ships and the manufacturers of e-navigation related systems. Therefore, this dissertation:
 Identifies what kinds of tool kits the IMO e-navigation has, by examining the
SIP set out in NCSR 1/28 and NAV 59/6, as means to reduce accidents.
 Examines related IMO documents over the period from 2006 to 2015 in order to
determine methodologies to evaluate the effect of e-navigation.
 Develops a formula, which is applicable to other Member States of IMO as well
as the Republic of Korea, as a tool to calculate the effect of e-navigation on
reducing accidents in terms of both SOLAS ships and non-SOLAS ships
 Analyzes the vessel accident data for all ships in Korean water areas and all
Korean-flagged ships worldwide, during the 5 years from 2009 to 2013.
 Reviews the concept and the service scope of SMART-navigation, which is the
Korean approach to implementing e-navigation, in order to identify the RCOs
that might be applicable to both SOLAS and non-SOLAS ships.
 Verifies the validity of methodologies to be used in the dissertation through an
expert questionnaire.
 Discusses the potential effect of SMART-navigation on reducing accidents, and
provides the results as an example for other countries to evaluate the effects of
e-navigation when they are introducing it into their waters.
8
1.3 Scope of the Study
This dissertation includes 6 Chapters. Chapter 1 shows the background, objectives,
scope and methodologies of this paper.
Chapter 2 overviews the development of e-navigation, through examining and reviewing
its related documents developed by the IMO so as to identify what kinds of tool kits the
IMO’s e-navigation has as a means to prevent vessel accidents and how such tool kits
have been developed and finalized.
Chapter 3 determines the methodology to be used in this dissertation for determining the
effects of e-navigation, and especially the effects of SMART-navigation on reducing
accidents for all ships in Korean water areas and all Korean-flagged ships worldwide in
terms of non-SOLAS ships as well as SOLAS ships. To determine the methodologies,
this chapter reviews the risk and cost-benefit analysis that the FSA team carried out as
set out in the IMO document, NAV 59/6. Annex 1 and NCSR 1/28. Annex 7, in addition
to other e-navigation related documents developed by the relevant Sub-Committees of
IMO.
Chapter 4 shows the result of analyzing accident data for all ships in Korean water areas
and all Korean-flagged ships worldwide during the 5 years from 2009 to 2013. The
analysis is focused mainly on identifying the accident types in terms of navigational
accidents and others, the accident ship types in terms of SOLAS and non-SOLAS ships,
and the detailed direct causes of accidents in terms of human error, technical failures and
external factors, which are expected to be preventable by e-navigation.
The methods and formats analyzing the data were followed in the same manner as
carried out in the document, NAV 59/6. Annex 1 and NCSR 1/28. Annex 7, in order to
9
harmonize the level of the rate of risk reduction of accidents. However, the author
analyzes all kinds of accident data, including SOLAS and non-SOLAS, as well as nonfishing and fishing vessels, whilst the document NAV 59/6. Annex 1 and NCSR 1/28.
Annex 7 analyzed only SOLAS ships except non-SOLAS ships and fishing vessels.
Chapter 5 discusses the effect of the SMART-navigation on reducing accidents based on
the result of analyzing accident data in chapter 3. To compare and identify differences to
results obtained by the IMO, the chapter reviews the concept and services of SMARTnavigation, and defines the scope of the RCOs that are considered to have an effect on
reducing accidents for the non-SOLAS ships including fishing vessels. In addition, the
chapter develops a formula to calculate the effect of e-navigation, which can be used by
the other Member States of the IMO not only by the Republic of Korea. Then, the
chapter provides the results of evaluating the effects of SMART-navigation on the rate
of accident reduction as an example to be used by other Member States to assess the
effects of e-navigation when they introduce it to their waters.
Finally, Chapter 6 gives a summary of this dissertation and concludes the effects of enavigation on reducing vessel accidents.
1.4 Methodology and Sources of Information
The research question of this paper is “What percentage of vessel accidents could be
reduced by the introducing e-navigation?”. To answer this question, this paper uses two
methodologies, namely qualitative and the quantitative analysis.
For the qualitative analysis, an examination and review of the e-navigation related
documents developed by IMO and other related research papers are carried out in order
to define the analysis tools to calculate the rate of risk reduction of accidents, and
10
identify the tool kits of e-navigation that have an effect on reducing accidents. All of
these documents were collected from the IMO website, internet and WMU library.
An overview of SMART-navigation is also conducted by qualitative analysis through
examining and reviewing its components as described in the preliminary feasibility
study on SMART-navigation and the study of systems to prevent safety accidents in
maritime sectors, which were carried out by the Ministry of Oceans and Fisheries
(MOF).
On the other hand, the quantitative methodology focuses on calculating the rate of the
effects of e-navigation on reducing accidents. The calculation is carried out by the
formula developed by the author based on the methodology used in Annex 1 of NAV
59/6 (May 31, 2013). The detailed direct causes of vessel accidents and the RCOs,
which are applicable to non-SOLAS ships, are also identified by quantitative analysis
based on the statistics and law data-base that have been accumulated by the Korea
Maritime Safety Tribunal (KMST).
In addition, the expert questionnaire survey is carried out as one of the quantitative
analysis items in order to verify the validity of methodologies which were used in
calculating the rate of reducing accidents for non-SOLAS ships.
11
2. TOOL KITS OF IMO E-NAVIGATION TO REDUCE ACCIDENTS
The IMO document, NAV 59/6. Annex 1, demonstrates that e-navigation could reduce,
by more than 65 %, the detailed direct causes of ships’ collisions and groundings. What
kinds of main tool kits of e-navigation function as the tools to reduce such accidents, and
how? To answer these questions, the chapter is to examine in detail the process by which
those e-navigation tool kits were developed, and what these respective e-navigation tool
kits are. In addition, the chapter is to examine the user needs of e-navigation and the
detailed direct causes of navigational accidents, including collisions and groundings, in
terms of human errors, technical failures and external factors. It is because that user
needs and detailed direct causes are to be used as the basis to identify the tool kits.
In this chapter, the term “tool kits” cover all kinds of functional and technical, legal
“systems” and “services” related to e-navigation, for example, such as its solutions, risk
control options (RCOs) and maritime service portfolios (MSPs).
2.1 Overview of IMO e-navigation
2.1.1 History of developing e-navigation
E-navigation was initiated by a joint proposal, including Japan, the Marshall Islands, the
Netherlands, Norway, Singapore, the UK and the USA, to the MSC of IMO at its eightfirst session in 2006 (MSC 81/23/10). Those States suggested that :
12
E-navigation would contribute to reduce navigational accidents, errors and
failures by developing standards for an accurate and cost effective system that
would make a major contribution to the IMO’s agenda of safe, secure and
efficient shipping on clean oceans (page 1, executive summary, MSC 81/23/10).
Following this proposal, the NAV Sub-Committee developed a “Strategy for the
development and implementation of e-navigation (NAV 54/25 Annex 12)” and “Time
frame for implementation of the proposed e-navigation strategy (NAV 54/25 Annex 13)”,
in co-operation with the COMSAR Sub-Committee and with the relevant input provided
by other relevant organizations such as IALA and IHO, over a period of two years (2006
to 2008). The strategy and the time frame were submitted to the MSC of IMO at its
eight-fifth session (2009) and were approved by the Committee as set out in MSC 85/26
Add 1 (Annex 20) and MSC 85/26. Add.1 ( Annex 21), respectively. The MSC 85/26
Add 1 (Annex 20) explains the core objectives of e-navigation as follows:
(1) facilitate safe and secure navigation of vessels having regard to
hydrographic, meteorological and navigational information and risks; (2)
facilitate vessel traffic observation and management from shore facilities; (3)
facilitate communications, including data exchange, among users; (4) provide
opportunities for improving the efficiency of transport and logistics; (5) support
the effective operation of contingency response, and SAR services; (6)
demonstrate defined levels of accuracy, integrity and continuity appropriate to a
safety-critical system; (7) integrate and present information on board and ashore
through a human-machine interface which maximizes navigational safety
benefits and minimizes any risks of confusion10 or misinterpretation on the part

10
With regard to this, according to the report of e-navigation underway conference 2014, John Murray
(2014) emphasized that “the fault by watch-keepers causing accidents are mainly due to the distraction
or confusion, emphasizing the need to retain the skills of watch-keepers while simplifying displays”
(page 8).
13
of the user; (8) integrate and present information onboard and ashore to manage
the workload of the users, while also motivating the user and supporting
decision-making; (9) incorporate training and familiarization requirements for
the users throughout the development and implementation process; (10) facilitate
global coverage, consistent standards and arrangements, and mutual
compatibility and interoperability of equipment, systems, symbology and
operational procedures, so as to avoid potential conflicts between users; and
(11) support scalability, to facilitate use by all potential maritime users (p. 3).
The approved strategy, even though there were some points that were somewhat
overwhelming and included many issues to be solved (para. 11.19, MSC 85/26), became
the stepping stone for the MSC to move forward to further development of the strategy
for e-navigation. After this, the joint work done by COMSAR, NAV and STW
(Standards of Training and Watchkeeping) Sub-Committees were undertaken to develop
a coordinated approach to implement the approved e-navigation strategy according to
the time framework as set out in MSC 85/26. Add. 1 as shown in Table 1 below.
Table 1 Time framework for implementing SIP (MSC 85/26)
Source: Developed by the author by using data given on page 1 of MSC 85/26. Add.1. Annex 21. This
figure is to show the time framework more clearly.

14
The above tasks had been undertaken by 2012 and their results were submitted to the
MSC of IMO at its ninetieth session. However, the MSC of IMO at its ninety-first
session extended the target date for completing the SIP of e-navigation until 2014
because the Committee noted that the results needed further revision and finalization of
the work.
Then, the MSC, in its ninetieth and ninety-first sessions, instructed both STW 43 and
NAV 58 to progress further work by re-establishing the Correspondence Group (CG)
and endorsed the joint plan of work on e-navigation for the COMSAR, NAV and STW
Sub-Committees for the period 2012-2014.
Finally, based on the report submitted by the CG (NAV 59/6), the MSC of IMO at its
ninety-forth session on November 26, 2014, approved the e-navigation SIP, as set out in
document NCSR 1/28, Annex 7. According to the SIP, the e-navigation is expected to be
fully operational from 2020 if five prioritized e-navigation solutions as well as 18 kinds
of tasks are implemented over the period 2014 to 2019 according to the time
framework as shown in Table 2.
According to Hagen (2015), who is the chair of the Correspondence Group (CG) on
IMO e-navigation, the approved SIP would be continuously developed and supported
with IMO in the leading role, and included11 in the IMO High-level Action Plans for
2016-2019.

11
In line with this, interested Member States may submit proposals to the Committee for the inclusion of
new planned or unplanned outputs in the High-level Action Plan of the Organization based on the
identified tasks contained in this SIP (MSC 95/21, p 78, paragraph 21.2.17, MSC 95/22, p 88,
paragraph 22.2.10, MSC 95/22, p72, paragraph 19.12.6).
15
Table 2 Time framework for eighteen tasks to implement SIP
Source: p. 18, Annex 7 of NCSR 1/28. “T” means “Task to be done” (For details, see p. 13-16 Annex 7 of
NCSR 1/28).
2.1.2 Strategic Implementation Plan (SIP) of IMO
As examined in the history of developing e-navigation, for the time being, the SIP is a
master for the implementation of e-navigation, which was approved by MSC 94 in 2014,
as set out in the Annex 20 of NCSR 1/28. That is, the SIP could be said to include all
16
aspects with regard to the implementation of e-navigation. Therefore, it is necessary to
examine in detail the components of the SIP in order to understand what kind of enavigation tool kits reduce accidents and how.
The SIP was developed based on user needs according to 5 main steps from the
beginning stage as follows: (1) identifying user needs; (2) identifying the key elements
to meet them; (3) gap analysis between the key elements and the current technologies;
(4) identifying the tool kits of e-navigation to meet user needs, and (5) carrying out the
risk and cost-benefit analysis against the tool kits.
The steps from (1) to (4) above had been continuously conducted, reviewed and
finalized mainly by the NAV and COMSAR Sub-Committees and the MSC, including
the series of CGs and Working Groups (WGs) established by each committee, from
2006 when e-navigation was proposed jointly by several Member States until 2013.
All of these outputs were assessed and verified through the FSA (NAV 59/6, summary)
as shown in the Figure 1. The FSA12 is the standard risk assessment tool to be used for
the development of new rules and regulations of IMO as described in the Annex of MSC
83/INF.2, “Consolidated text of the Guidelines for Formal Safety Assessment (FSA) for
use in the IMO rule-making (MSC/Circ.1023−MEPC/Circ.392)” (p. 3).

12
Hermanski, G. & Daley, C. (2005) summarized the case of applying the FSA and commented that:
“Since IMO published its interim guidelines on FSA (MSC/Circ.829-MEPC/Circ.335) in 1997 many
FSA studies were conducted. Member governments, non-governmental observer organizations,
International Association of Classification Societies (IACS) and individual class societies carried out
variety of FSA studies” (p. 8)
17
Figure 1 Steps of FSA used in developing the SIP
Source: NAV 56/8 (page 17)
Through the processes above, the SIP was finally developed. The SIP is mainly
composed of 3 kinds of components with regard to the e-navigation tool kits as set out in
Annex 7 of NCSR 1/28 (p. 2-3, p27-34) as follows:
 The five prioritized solutions, including S1, S2, S3, S4 and S9,
 The seven RCOs with the sub-solutions related to, and
 The sixteen MSPs for 6 areas.
18
The SIP contains other components, which are to be undertaken in order to prepare and
provide these 3 kinds of tool kits from 2014 to 2019, as set out in Annex 7 of NCSR
1/28, as follows:
(1) 18 Tasks with expected deliverables, transition arrangements and
implementation schedule (p. 13-16),
(2) Examples of key enablers of e-navigation (p. 18, Annex 7 of NCSR 1/28),
(3) Examples of key messages to promote the benefits of e-navigation through
each solutions according to the stakeholders (p. 37-40),
(4) Identification of communication systems for e-navigation; Communications
are a key for e-navigation. Any communications systems used must be able
to the deliver appropriate MSPs in the 6 areas defined, as per S9, as well as
delivering reliable ship reporting as identified in S2 (p. 19), and
(5) Ship and shore architecture for solutions13
as shown in Figure 2 (p. 18-19).

13
With regard to the architecture, Annex 7 of NCSR 1/28 explains that :
The Figure 2 shows the principle of an information and data flow in the e-navigation
architecture. The figure shows the complete overarching e-navigation architecture, and defines
two additional important features: the CMDS that spans the whole of the horizontal axis; and
the World Wide Radio Navigation System (WWRNS) (page 18).
19
Figure 2 Overarching e-navigation architecture
Source: Annex 7 of NCSR 1/28 ( page 18)
2.1.3 Identifying user needs
Following the decision by both the Sub-Committees of NAV 53 and COMSAR 11 that
the e-navigation strategy should be user-driven rather than technology driven, the work
to identity the user needs was undertaken by the intersessional CG and the results
included in MSC 85/26 Add.1. Annex 20, “Strategy for the development and
implementation of e-navigation”.
The basic concept of user needs of e-navigation is to avoid system failures causing
delays because the ship is now deemed unseaworthy, loss of basic good seamanship by
20
crews, inappropriate substitution of the human element by technology and degradation
of bridge resource management and best practices by the crew (paragraph 7, page 5,
MSC 85/26 Add.1. Annex 20)
The documents MSC 85/26 Add.1 Annex 20 emphasized the importance of applying
ergonomic principles to the electronic systems of e-navigation, including the
presentation of information for users, so as to reduce single person errors and enhance
team operations (paragraph 8.2.5, p7). Further to this, the document also recommended
the concept of user needs in more detail as shown in Table 3 below.
Table 3 Potential e-navigation users
No Shipborne users Shore-based users
1 Generic SOLAS ships Ship owners/operators, safety managers
2 Commercial tourism craft VTM organizations
3 High-speed craft VTS centres
4 Mobile VTS assets Pilot organizations
5 Pilot vessels Coastguard organizations
6 Coastguard vessels Law enforcement organizations
7 SAR vessels National administrations
8 Law enforcement vessels (police, customs, etc) Coastal administrations
9 Nautical Helpance vessels (tugs, salvage, tenders) Port authorities
10 Counter pollution vessels Security organizations
11 Military vessels Port State control authorities
12 Fishing vessels Incident managers
13 Leisure craft Counter pollution organizations
14 Ferries Military organizations
15 Dredgers Fairway maintenance organizations
16 A to N service vessels A to N organizations
17 Ice patrol/breakers Meteorological organizations
18 Offshore energy vessel (supply, lay barges, survey) Hydrographic Offices/Agencies
19 Hydrographic & Oceanographic research vessels Ship owners/operator, logistics managers
20 News organizations
21 Coastal management authorities
22 Marine accident investigators
23 Health and safety organizations
21
24 Insurance and financial organizations
25 National, regional and local governments
26 Port authorities (strategic) Ministries
27 Marine environment managers
28 Fisheries management
29 Tourism agencies (logistics)
30 Energy providers
31 Ocean research institutes
32 Training organizations
33 Equipment and system manufacturers
sum 18 33
Source: MSC 85/26/Add.1. Annex 20 (p. 14-15)
The document MSC 85/26 Add.1 Annex 20 also identified 8 kinds of user needs as
follows: “(1) Common maritime information/data structure; (2) Automated and
standardized reporting functions; (3) Effective and robust communications; (4) Human
centred presentation needs; (5) Human machine interface; (6) Data and system
integrity; (7) Analysis; and (8) Implementation issues” (p. 15).
However, the identified user needs in the strategy were somewhat overwhelming (para.
11.18, p. 79, MSC 85/26) and based only on feedback from the high-level generic users
such as Member States, other maritime organizations, and interested parties, and limited
to the typical SOLAS ship and a generic shore authority (para. 8.2, p5, MSC
85/26/Add.1 Annex 20).
Therefore, the user needs needed to be identified in more detail and the identification
was undertaken again by the consecutively established CG and the WG over a period of
from 2008 to 2010. During this period, in the document NAV 55/ INF. 9, the user needs
were identified through a questionnaire with 353 persons responding in total, whose
average experience as a mariner was 16.6 years (p. 2). This document was further
developed by the CG and WG of the NAV Sub-Committee, which was chaired by Mr.
22
John Erik Hagen, as set out in the document NAV 56/WP.5/Rev.1 and NAV 56/20.
These two documents completed the comprehensive works related to the implementation
of e-navigation, including indentified tool kits and services to support user needs in a
harmonized and holistic manner (para. 8.3, p. 20, NAV 56/20).
Based on these results above, e-navigation user needs were finalized as set out in the
document COMSAR 15/11, including Annex 1(INITIAL GAP ANALYSIS – shipboard
users), Annex 2 (INITIAL GAP ANALYSIS – shore-based users) and Annex 3
(INITIAL GAP ANALYSIS – Search and Rescue).
2.1.4 Analyzing human errors that cause accidents
The objective of the FSA was to identify relevant hazards pertaining to navigation, to
quantify related safety risks, and to identify and prioritize a set of RCOs deemed to
reduce said risks. The result was submitted to NAV 59 (NAV 59/6), showing, in
conclusion, that e-navigation has effects on reducing by more than 65 %, the risk of
vessels’ collisions and groundings through providing the seven RCOs.
To achieve the objective, the FSA team applied the casualty database of the IHS
Fairplay14 for the period from 2001 to 2010, but also used it together with accident data
from the Norwegian Maritime Authority (NMA). For the purpose of analyzing the direct
causes of navigational accidents, the FSA team first classified the initial accidents, and
then identified the direct causes of accidents according to the structure given in Figure 3.

14
IHS Fairplay, which is belonging to the IHS (Information Handling Service) enterprise founded in
1959, provides maritime databases, evolved from the Lloyd’s Register of Ships books, such as ship,
vessel movement, casualty, ownership and port database. The enterprise has two headquarters; a global
headquarter based at Englewood, U.S.A, and a regional headquarter based at Bracknell, U.K.
23
Figure 3 Methodology to identify the direct causes of accidents
Source: Annex 1 of NAV 56/6 (p. 12)
Table 4 shows the statistics analyzed by the FSA team for accidents involving the
selected ship types over the time-span from 2001 to 2010, and Table 5 shows that more
than 43.2 % were navigational accidents, including 21.6% of collisions and 21.6% of
groundings, among the total 12,819 accidents and more than 21.9 % of losses of life
among the total 6,262 happened in navigational accidents.
Table 4 Number of events and loss of life
Source: Annex 1 of NAV 56/6 (page 9)
24
Table 5 Composition of events and loss of life
Ship
Type
Accidents Type Loss of Life
Navigational NonNav
Navigational Noncollision Grounding sum collision Grounding sum Nav
Cargo
ship
2336
(18.2%)
2286
(17.8%)
4621
(36.1%)
5133
(40.0%)
238
(3.8%)
200
(3.2%)
438
(7.0%)
1563
(25.0%)
Passenger
245
(1.9%)
321
(2.5A%)
566
(4.4%)
1543
(12.0%)
53
(0.8%)
836
(13.3%%)
889(
14.2%)
3166
(50.5%)
Others 194
(1.5%)
162
(1.3%)
356
(2.8%)
599
(4.7%)
41
(0.7%)
4
(0.1%)
45
(0.7%)
163
(2.6%)
SubTotal
2775
(21.6%)
2768
(21.6%)
5543
(43.2%)
7275
(56.8%)
332
(5.3%)
1040
(16.6%)
1372
(21.9%)
4892
(78.1%)
Total 12819 6264
Source: The author developed this to show data more clearly, by reassembling data given in Table 4.
The outcome of this analysis is that more than 65 % of all navigational accidents were
caused by human error, while 18% are caused by technical failure and 17% by external
factors (para. 5.1, Annex 1 of NAV 59/6). Figures 4, 5 and 6 show the detailed causes of
navigational accidents in terms of human error, technical failures and external factors.
Figure 4 Human error cause distribution
Source: Annex 1 of NAV 56/6 (page 13-14)
25
Figure 5 Technical failure cause distribution
Source: Annex 1 of NAV 56/6 (page 15).
Figure 6 External factor cause distribution
Source: Annex 1 of NAV 56/6 (page 15)
26
2.2 Main tool kits of IMO e-navigation
Up to now, the author has summarized the development of IMO’s e-navigation and its
SIP, and found that it has mainly 3 kinds of tool kits, including the five prioritized enavigation solutions, the seven RCOs and the sixteen MSPs in paragraph 2.1.2. There
are several reasons 15 for IMO to introduce e-navigation. With regard to this, the
document MSC 85/26/Add.1 emphasized that:
If e-navigation could Help in improving the reliability of the decision-making
process, both by well-designed onboard systems and closer cooperation with
vessel traffic management (VTM) instruments and systems, the risk of
navigational accidents and their inherent liabilities could be dramatically
reduced (p. 2).
These tool kits might contribute to improve the reliability of the relevant decisionmaking process, and reduce accidents as a result of that. The chapter examines the tool
kits of IMO’s e-navigation in more detail, involving its solutions, RCOs and MSPs.
2.2.1 The e-navigation solutions
Based on the identified user needs and analysis of accidents, the NAV 57 decided to
carry out a gap analysis in order to identify e-Navigation solutions to meet user needs,
taking into account the Human Element Analyzing Process (HEAP), and the document
NAV 58/6 was submitted as the result of gap analysis.

15 The document MSC 85/26/Add.1 summarized the reasons as follows: “the rising trends of navigational
accidents; the numerous examples of such accidents might have been avoided if there had been
suitable input to the navigation decision-making process; and the fact that 60% of collisions and
groundings are caused by human error” (para. 3.2)
27
Annex of the NAV 58/6 provides a list of practical e-navigation solutions in terms of 4
aspects; (1) the operational (procedural / automation), (2) the human element, the
technical (H/W, S/W, equipment), (3) the regulatory (regulation, standard), and (4) the
training (human element). Table 6 summarizes and describes the IMO agreed and
prioritized solutions and their sub-solutions.
Table 6 Description of Solution and its Sub-Solutions
Solutions and SubSolution Description
S1
improved,
harmonized and userfriendly bridge design
S1.1 Ergonomically improved and harmonized bridge and workstation
layout.
S1.2 Extended use of standardized and unified symbology for relevant
bridge equipment.
S1.3 Standardized manuals for operations and familiarization to be
provided in electronic format for relevant equipment
S1.4
Standard default settings, save/recall settings, and S-mode
functionalities on relevant equipment.
S1.5 All bridge equipment to follow IMO Bridge Alert Management
S1.6 Information accuracy/reliability indication functionality for
relevant equipment.
S1.6.1 Graphical or numerical presentation of levels of reliability
together with the provided information.
S1.7 Integrated bridge display system (INS) for improved access to
shipboard information.
S1.8 GMDSS equipment integration – one common interface.
S2
means for
standardized and
automated reporting;
S2.1 Single-entry of reportable information in single-window solution.
S2.2 Automated collection of internal ship data for reporting.
S2.3
Automated or semi-automated digital distribution/communication
of required reportable information, including both “static”
documentation and “dynamic” information.
S2.4
All national reporting requirements to apply standardized digital
reporting formats based on recognized internationally harmonized
standards, such as IMO FAL Forms or SN.1/Circ.289.
S3
improved reliability,
resilience and
integrity of bridge
equipment and
navigation
information;
S3.1 Standardized self-check/built-in integrity test (BIIT) with
interface for relevant equipment (e.g. bridge equipment).
S3.2 Standard endurance, quality and integrity verification testing for
relevant bridge equipment, including software.
S3.3
Perform information integrity tests based on integration of
navigational equipment – application of INS integrity monitoring
concept.
S3.4
Improved reliability and resilience of onboard PNT information
and other critical navigation data by integration with and backup
of by integration with external and internal systems.
28
S4
integration and
presentation of
available information
in graphical displays
received via
communication
equipment
S4.1
Integration and presentation of available information in graphical
displays (including MSI, AIS, charts, radar, etc.) received via
communication equipment.
S4.1.1 Implement a Common Maritime Data Structure and include
parameters for priority, source, and ownership of information.
S4.1.2
Standardized interfaces for data exchange should be developed to
support transfer of information from communication equipment to
navigational systems (INS).
S4.1.3
Provide mapping of specific services (information available) to
specific regions (e.g. maritime service portfolios) with status and
access requirements.
S4.1.4
Provision of system for automatic source and channel
management on board for the selection of most appropriate
communication means (equipment) according to criteria as, band
width, content, integrity, costs.
S4.1.5 Routing and filtering of information on board (weather, intended
route, etc.).
S4.1.6
Provide quality assurance process to ensure that all data is reliable
and is based on a consistent common reference system (CCRS) or
converted to such before integration and display.
S4.1.7
Implement harmonized presentation concept of information
exchanged via communication equipment including standard
symbology and text support taking into account human element
and ergonomics design principles to ensure useful presentation
and prevent overload.
S4.1.8 Develop a holistic presentation library as required to support
accurate presentation across displays.
S4.1.9 Provide Alert functionality of INS concepts to information
received by communication equipment and integrated into INS.
S4.1.10 Harmonization of conventions and regulations for navigation and
communication equipment.
S9
improved
Communication of
VTS Service Portfolio
S9
Improved communication of VTS service portfolio (not limited to
VTS stations)
Source: Solutions (para. 15, p. 5, NAV 59/6), Sub-Solution (Tables 1 to 5, Annex 7 of NCSR 1/28)
These five solutions shown in Table 6 above were finalized with a goal-based approach
based on the risk and cost-benefit analysis according to the FSA process and the
methodology of the HEAP (para. 19, p. 5, NAV 59/6). In addition, these solutions were
used as the basis for creating the SIP and the RCOs as well as for the further
implementation of e-navigation.
29
2.2.2 Risk Control Options (RCOs)
In order to identify the tangible and manageable RCOs, the FSA team used the process
as depicted in Figure 7, by merging the results of user needs, gaps analysis and
prioritized solutions with the accident data analysis. Through this process, the seven
RCOs with sub-solutions were decided as the RCOs to provide cost-effective risk
reductions in a cost-effective manner (p. 6, para. 24-26, NAV 59/6) as follows:
 RCO 1: Integration of navigation information and equipment including
improved software quality assurance (related to sub-solutions: S1.6, S1.7, S3.1,
S3.2, S3.3, S4.1.2, and S4.1.6);
 RCO 2: Bridge alert management (S1.5);
 RCO 3: Standardized mode(s) for navigation equipment (S1.4);
 RCO 4: Automated/standardized ship-shore reporting (S2.1, S2.2, S2.3, S2.4);
 RCO 5: Improved reliability and resilience of onboard PNT systems (S3.4);
 RCO 6: Improved shore-based services (S4.1.3 and solution S9);
 RCO 7: Bridge and workstation layout standardization (S1.1).
Figure 7 RCO identification process
Source: Annex 1 of NAV 59/6 (p. 20)
30
2.2.3 Maritime Service Portfolios (MSPs)
The concept of MSPs was first introduced at the fifty-seventh session of NAV SubCommittee (para. 23-26, NAV 57/6). MSP is a part of the improved provision of
services to vessels through e-navigation (NCSR 1/28 Annex 7, paragraph 17), and
defined and described as the set of operational and technical services and their level of
service, with the need for information and communication services, provided by a
stakeholder in a given area16 (para. 23, NAV 57/6).
The MSPs were finalized as in Table 7 below by the CG on e-navigation established by
NAV 58. The CG proposed 17 kinds of MSPs, in the document NAV 59/6. Annex 3
with detailed descriptions. However, through the discussion of the Working Group
established by NAV 59, one of them, “Remote monitoring of ships systems” was
deleted17
Table 7 List of the Maritime Service Portfolios (MSPs)
MSPs Services Responsible Service Provider
MSP1 VTS Information Service (IS) VTS Authority
MSP2 Navigational Helpance Service (NAS) National Competent VTS Authority/Coastal or
Port Authority
MSP3 Traffic Organization Service (TOS) National Competent VTS Authority/Coastal or
Port Authority
MSP4 Local Port Service (LPS) Local Port/Harbour Operator

16
With regard to this, the SIP defines 6 areas : “(1) port areas and approaches; (2) coastal waters and
confined or restricted areas; (3) open sea and open areas; (4) areas with offshore and/or
infrastructure developments; (5) polar areas; and (6) other remote areas” (para. 18, p. 11, Annex 7 of
NCSR 1/28).
17
During the discussion, this MSP was severely argued between delegations and deleted according to the
opinion, especially the strong suggestion by the representative from ICC, that it is not directly related
to the safety of navigation. The author participated in the Working Group as the delegation of the
Republic of Korea.
31
MSP5 Maritime Safety Information Service (MSI National Competent Authority
MSP6 Pilotage service Pilot Authority/Pilot Organization
MSP7 Tugs Service Tug Authority
MSP8 Vessel Shore Reporting National Competent Authority,
Shipowner/Operator/Master
MSP9 Telemedical Helpance Service (TMAS) National Health Organization/dedicated
Health Organization
MSP10 Maritime Helpance Service (MAS) Coastal/Port Authority/Organization
MSP11 Nautical Chart Service National Hydrographic Authority/
Organization
MSP12 Nautical Publications Service National Hydrographic Authority/
Organization
MSP13 Ice Navigation Service National Competent Authority Organization
MSP14 Meteorological Information Service National Meteorological Authority/WMO/
Public Institutions
MSP15 Rea-time Hydrographic and
Environmental Information Service
National Hydrographic and Meteorological
Authorities
MSP16 Search and Rescue Service SAR Authorities
Source : Annex 7 of NCSR 1/28
2.3 Conclusion of the tool kits of e-navigation
Up to now, the author has examined the tool kits of e-navigation, and their developed
processes and functions. As a result, the author has identified three kinds of main tool
kits of IMO e-navigation, including the five solutions, seven RCOs and sixteen MSPs.
They were finalized through a goal-based approach based on the cost-benefit and risk
analysis by the FSA team (para. 19, p. 5, NAV 59/6).
In brief, e-navigation, using these tool kits, might be able to enhance the capability of
shore-based stations to manage and Help the safety of navigation in an efficient and
timely manner. It also supports the decision making process and provides safety
information to crews on board ships, which might lead the crews to avoid or detect
32
human error in advance. This is clearly supported by the current definition and concept
of e-navigation. The concept of e-navigation was finally defined in Annex 20 of MSC
85/26 Add. 1, “Strategy for the development and implementation of e-navigation”, which
was submitted by the NAV Sub-Committee in 2009, as follows:
The harmonized collection, integration, exchange, presentation and analysis of
marine information on board and ashore by electronic means to enhance berth
to berth navigation and related services for safety and security at sea and
protection of marine environment (para. 1.1, p. 1).
This might mean that e-navigation is to enhance the safety of navigation and increase the
efficiency of maritime-related businesses by implementing its three kinds of tool kits.
The words “to enhance” here might mean to increase the quantity and quality of
managing safety of navigation by improving the maritime communication network, the
structure of information and services, and the relevant systems and equipment on board
ship and ashore. This is clearly supported by the vision of e-navigation, involving the
elements of communication, on board ship and ashore, as described in the MSC 85/26.
Annex 20 (para. 4.1, p. 2)
In other words, as the author mentioned in the background, the more modernized
information and communication technology of e-navigation such as the globally
standardized and automated ship-shore reporting system and the seamless transmission
of electronic information and data between ship and shore might provide crews on board
ship with more decision-making support and also to minimize their work-loads, enabling
them to focus on the safety of navigation. In addition, these electronic technologies of enavigation might increase the efficiency of the maritime-related businesses, as well. One
of the reasons why the IMO’s e-navigation strategy has been driven based on its user
needs is because of this.
33
In conclusion, the author concluded, based on the examination done in this Chapter, that
the tool kits of e-navigation reducing vessel collisions and groundings by 65% are the
five prioritized solutions, the sixteen MPSs, and especially the seven RCOs, and
summarized the relationships between these tool kits as shown in Table 8.
Table 8 Relation between Tool kits of e-navigation to reduce accidents
RCOs Functions and MSPs Relevant
Solutions
(RCO 1)
Integration of
navigation
information and
equipment
including
improved
software quality
assurance
to provide integrated and augmented functions to the
navigator, i.e. an improved basis for navigational decisionmaking, taken from the INS standard, as follows;
 Route planning and monitoring : the route check
against hazards based on the planned minimum under
keel clearance as specified by the mariner; overlaying
radar video data on the chart to indicate navigational
objects, restraints and hazards to own ship in order to
allow position monitoring Assessment and object
identification; determination of deviations between set
values and actual values
 Supporting decision making of collision avoidance
 Providing navigation control data : under keel
clearance (UKC), STW, SOG, COG, position, heading,
ROT (measured or derived from change of heading),
rudder angle, propulsion data; set and drift, wind
direction and speed (true and/or relative selectable by
the operator); the active mode of steering or speed
control; time and distance to wheel-over or to the next
waypoint; safety related messages e.g. AIS safetyrelated and binary messages, NAVTEX, SafetyNet or
other GMDSS information.
 Status and data display : ship’s static, dynamic and
voyage-related AIS data ; safety related messages, such
as AIS safety-related and binary messages, Navtex,
SafetyNet or other GMDSS information;
 Function editing AIS own ship’s data and information
to be transmitted by AIS messages.
 Redundancy of important equipment and Software
testing
S1.6
S1.7
S3.1
S3.2
S3.3
S4.1.2
S4.1.6
34
(RCO 2)
Bridge alert
management
To provide alert management in order to enable the bridge team
to devote full attention to the safe navigation of the ship and to
immediately identify any abnormal situation requiring action to
maintain the safe
 Danger of collision, Danger of grounding
S1.5
(RCO 3)
Standardized
mode(s) for
navigation
equipment
Safe navigation relies on the ability of key personnel to easily
operate navigational equipment as well as comprehend the
information that is presented to them. Lack of familiarity with
bridge equipment and/or slow response due to not finding correct
information/control/alarm is thus considered to adversely affect
safe navigation. Standard modes are to provide a standardized and
common display familiar to all stakeholders, reducing the need
for personnel to familiarize themselves with variations of HMIs in
order to safely navigate.
 Offer default display configurations for the ECDIS and
the radar to provide the bridge team and pilot with a
standardized display and a simple operator action.
 Provide operational modes for a set of predefined
operational areas such as open sea, coastal, confined
waters (pilotage, harbour berthing, and anchorage).
S1.4
(RCO 4)
Automated and
standardized
ship-shore
reporting
Forms are usually manually filled out and sent individually to
each authority requesting the information. Compliance with IMO
FAL forms normally takes about two hours to fill. For example,
around 25 documents had to be sent from the ship, or the ship’s
agent, in conjunction with a port call. The data requested in many
of these documents are fully or almost identical. Documents are
also often in paper or other non-computer-compatible formats,
which is a time-consuming and costly affair. The S-mode
provides followings in order to reduce workload due to filling
out and delivering reportable information is identified.
 The system would integrate relevant onboard systems
enabling collection and edition of information and data
needed for reporting.
 The system should allow for automated digital
distribution of required reportable information (single
window solution), including both static, dynamic,
voyage related and SAR information to authorized
authorities, with the least possible intervention required
by the ship during and/or before navigation.
S2.1, S2.2,
S2.3 and S2.4
35
(RCO 5)
Improved
reliability and
resilience of
onboard PNT
systems
Ensuring reliable and resilient PNT data, providing ship’s
position, velocity, and time data (PVT) for navigators and
navigational functions, is important for safe navigation. However,
for the time being, due to insufficient redundancy within single
sensors and unsupported exploitation of multi-sensor based
redundancy the classic approach is considered unable to meet enavigation user needs such as improvement dissertation writing helpof availability,
reliability and indication of integrity based on monitored and
assessed data and system integrity.
In order to improve reliability and resilience of position,
navigation, and timing data (PNT) an integrated and harmonized
utilization of PNT related systems and services is envisioned.
S3.4
(RCO 6)
Improved shorebased services
VTSs and other shore-based stakeholders gather and hold a lot of
information regarding navigational warnings, incidents,
operations, tide, AIS, traffic regulations, chart corrections,
meteorological conditions, ice conditions, etc., which often is
referred to as the Maritime Service Portfolio.
As per today this information is mostly communicated via voice
VHF and paper documents. Information transfer via voice
communication can be time-consuming and distractive as
navigators may need to make notes of information received and
possibly consult various written documentation on the bridge. The
voice communication procedure also holds a potential for
incorrect transfer and misinterpretation of information.
 Implementation of system for automatic and digital
distribution of shore support services would make
information more available, updated and applicable for
navigators.
 Maritime Safety Information (MSI) received by the ship
should be applicable to the ship’s specific voyage, i.e. it
should not contain information related to other areas
which is not relevant to that ship, and be presented on
one location, the ENC/ECDIS or AIS/RADAR display.
 Notices to mariners, ENC updates and corrections to all
nautical publications should be received electronically
without any delays in the delivery.
 All MSI to be sent out digitally and using a standard
such as the IHO S-100 data framework standard
enabling better visualization on board, for example,
Virtual Aids to Navigation (AtoN) for warning of new
S4.1.3 and
solution S9
36
navigational hazards, such as wrecks, obstructions or
floating debris, displaying on AIS/ECDIS
 In addition automatic updating and correction of
nautical charts via satellite is envisioned
(RCO 7)
Bridge and
workstation
layout
standardization
Cumbersome equipment layout on the bridge adversely influences
the mariner’s ability to optimally perform navigational duties.
Therefore, regulation, based on existing guidelines and standards,
regarding the physical layout of all bridge equipment regarded as
essential for safe and efficient navigation, is envisaged to
Workstation for navigating and maneuvering including;
 radar/radar plotting
 ECDIS
 information of AIS
 Indications of: rudder angle, rate-of-turn, speed, gyro
compass heading, compass heading and other relevant
information
 VHF point with channel selector
S1.1
Source: Summarized pages 20 to 31 of NAV 59/6 Annex 1
37
3. METHODOLOGY TO EVALUATE THE EFFECTS OF E-NAVIGATION
3.1 Introduction
This Chapter is to identify the methodology to quantitatively evaluate the effects of
SMART-navigation on reducing accidents for all ships in Korean waters and all Koreanflagged ships worldwide during the 5 years from 2009 to 2013.
With regard to this quantitative analysis, the author intends to apply same methodology
used by the FSA team for the IMO e-navigation strategy in order to increase the
objectivity of the study results. For that purpose, the methodology used by the FSA team
is to be examined as to how it was developed and how the rate of reducing navigational
accidents, “65 %”, was calculated.
3.2 Methodology used in the FSA for IMO e-navigation
According to Annex 1 of NAV 59/6, the FSA team put several conditions in its
methodology to estimate the risks and analyze the causes as follows:
 to define a generic risk model (paragraph 3, page 4)
 to select the ship types, excluding non-SOLAS ships (paragraph 3.3, page 5),
 to limit accident categories of collision and grounding (paragraph 3.3, page 5).
As the first step to quantify the rate of risk reduction of navigational accidents, the FSA
38
team calculated the frequencies for the accident categories as well as the potential loss of
lives (PLL) as shown in Table 9 below, by combining the numbers of accidental events
and losses of lives with the number of ship years for each ship category. The calculation
was based on the direct cause distribution of accidents, including human errors,
technical failures and external factors, as shown in Figures 4, 5 and 6, respectively (para.
2.2.2).
As a result, for example, for a generic ship, the distribution of accident types in terms of
frequency per ship-year is 44 % for collisions and groundings, and 56 % for other
accidents among all accidents per ship year as shown in Table 9 below.
Table 9 Accident frequencies
Source: Annex 1 of NAV 59/6 (page 10)
39
According to the document NAV 59/6, the risks are summarized to estimate the
individual risk and societal risks to crew members resulting from the operation of a
generic ship, and the FSA team extracted the total potential loss of lives (PLL) as the
risks by using a risk model “the frequency and consequence modeling” (para. 6.2, p. 16,
Annex 1).
The results of the risk estimation are presented in Table 10 below. For example, for a
generic ship, the risk distribution of accident types in terms of the PLL is 22% per ship
year for navigational accidents, including collisions and groundings, and 78 % for other
accidents among all accidents.
Table 10 Risk estimations
Source: Annex 1 of NAV 59/6 (p. 16)
40
For the purpose of producing an improved picture of where the highest risks originate,
the FSA team distributed the above estimated risks among the probable accident causes
as shown in Table 11 below, by applying findings from the hazard identification study
(para. 6.3, p. 17, Annex 1 of NAV 59/6).
Table 11 Total generic risk distributed among accident causes
Source: Annex 1 of NAV 59/6 (p. 18)
Based on the results above, the rate of risk reduction, according to each direct cause of
navigational accidents, by each RCO was estimated through a workshop composed of 5
41
experts from the USA, Netherlands, Denmark and Norway, who had a total of over 190
years of maritime experience (para. 8.3, p. 36, Annex 1 of NAV 59/6). The experts
estimated the potential rate of risk reduction against the detailed direct causes reducible
by RCOs, which are extracted among each direct cause, including human error, technical
failure and external factor. The estimation was revised through panel discussion and
refined by inputting the ideas of additional 4 experts after the workshop. Table 12 below
shows the rate of risk reduction of navigational accidents by each RCO, according to
each direct cause.
Table 12 Risk reducing potential

Source: Annex 1 of NAV 59/6 (page 37)
42
As the next step, the FSA team estimated the potential reduction of PLL frequency by
implementing each RCO as shown in Table 13 below. It was estimated by combining the
PLL frequency of 2.1E-03 presented in Table 11 and the percentages of risk reductions
given in Table 12 based on the cause distributions presented in Figures 4, 5 and 6.
Table 13 Estimated reduction potential of PLL per ship
Source: Annex 1 of NAV 59/6 (p. 38)
43
Lastly, based on Table 13 above, the RCOs were ranked by their respective rate of risk
reduction in terms of PLL reduction as shown in Table 14, and the rate of risk reduction
is estimated as 65% in total.
The FSA carried out cost-benefit (CB) analysis based on the above findings, resulting18
in the conclusion that RCO 1, RCO 2, RCO 3, RCO 5, RCO 6 and RCO 7 are all
beneficial in themselves in terms of economics; the costs of implementing the RCOs are
less than the economic benefits of implementing them.
Table 14 RCOs ranked by PLL
Rank RCOs PLL
reduction
PLL reduction
of total
1 RCO 7 Bridge and workstation layout standardization 2.1E-04 14%
2 RCO 1 Integration of navigation information and equipment
including improved software dissertation writing helpquality assurance 1.7E-04 11%
3 RCO 2 Bridge alert management 1.5E-04 10%
4 RCO 4 Automated and standardized ship-shore reporting 1.3E-04 8%
5 RCO 5 Improved reliability and resilience of on board PNT systems 1.2E-04 8%
6 RCO 3 Standardized mode 1.1E-04 7%
7 RCO 6 Improved shore-based services 1.1E-04 7%
Total 65%
Source: Annex 1 of NAV 59/6 (p. 37)
3.3 Methodology to be used in the dissertation
3.3.1 Conclusion of the methodology
The author examined, in Chapter 2, IMO e-navigation tool kits functioning to reduce
navigational accidents. As a result, the five e-navigation solutions, the seven RCOs and
the 16 MSPs were identified as the tool kits. Based on the result, this chapter examined

18
For details, see the document NAV 59/6. Annex 1 (page 42)
44
the methodology that the FSA team used to assess the effects of e-navigation on
reducing accidents. Table 15 shows the results, summarizing the process of developing
the methodology. As shown in Table 15, the rate of reducing accidents by each RCO is
developed in the 4th step, whilst the other steps from the 1st step to the 3rd-2 step are to
identify factors necessary for carrying out the cost-benefit analysis.
With regard to rate of risk reduction, 65% in total, estimated by the FSA team as shown
in Table 14, even though there is a limitation in the methodology to quantify the rate in a
quantitative way, the author concluded that the rate is reasonable and feasible. It is
because the rate has been developed based on reliable factors such as user needs, gap
analysis, three kinds of tool kits of e-navigation, the analysis of navigational accidents,
results of a generic risk model and verification by the competent experts through a
workshop as shown in Table 15. The next paragraph 3.3.3 examines the limitations in
more detail.
Thus, based on the examination up to now, the author decided to use the rate of risk
reduction by seven RCOs, 65%, which was estimated by the FSA team, as the
coefficient to develop a formula for evaluating the effects of SMART-navigation on
reducing accidents in Chapter 5.
Table 15 Calculation process of risk reduction rate by the FSA team
Steps Founding Methods,
Sources
(1st)
Identifying problems
in terms of safety of
navigation
User Needs
Direct Cause of Accidents, including human
errors, technical failures and external factors
Survey
Analyze Statistics
↓ ↓
(2nd)
Identifying tool kits
Five e-Navigation Solutions
Seven RCOs, and .
Experts opinions
based on user
needs and direct
45
of e-navigation to
reduce risk
Sixteen MSPs cause of accidents
↓ ↓
(3rd – 1)
Analyzing accidents
Statistics
Accident Trend (Table 4)
Accident Types (Collision, Grounding, and
Others) according to the ship’s type
IHS Statistics
Direct Cause (h NMA Statistics uman error, technical failures and
external factors); Figures 4,5 and 6
↓ ↓
(3rd – 2)
Estimating Risks of
Collisions and
Groundings
Accident frequency, PLL per ship year (Table 9)
Based on the
results of
analyzing
accident statistics
In terms of PLL
A generic risk
model
Frequency and
consequence
modeling
↓
Risk estimations in terms of PLL (Table 10)
↓
Total generic risk distributed among accident
causes (Table 11)
↓
Risk reducing potential (Table 12)
↓
Estimated reduction potential of PLL per ship
year (Table 13)
↓
RCOs ranked by PLL reduction per ship year
(Table 14)
↓ ↓
(4th)
Estimating the effect
of reducing risks
Rate of reduction of accident by each RCO
(Total : 65 % for SOLAS ships)
Experts opinions
& Frequency and
consequence
modeling
Source: The author summarized process based on the examination results in paragraph 3.2
3.3.2 Limitation in the methodology and Bayesian Network (BN)
The document NAV 59/6. Annex 1 (p. 47) and MSC 83/INF.2. Annex (p. 4) defines
“risk” as “the combination of the frequency and the severity of the consequence”,
“frequency” as “the number of occurrences per unit time”, and “consequence” as “the
outcome of an accident”. These definitions are similar to those of the American Bureau
of Shipping (ABS). The ABS (2000) defines “risk” dissertation homework help as “the product of the frequency with
46
which an event is anticipated to occur and the consequence of the event’s outcome: Risk
= Frequency × Consequence”.
Therefore, the rate of risk reduction of accidents by implementing e-navigation might be
the same as the rate of reducing frequency or probability. For example, Dr. Jens
Schröder-Hinrichs, who is a professor of the World Maritime University (WMU),
explained “risk” as the product of the probability with which an event is anticipated to
occur and the consequence of the event’s outcome; Risk = Probability × Consequence,
and “probability” as the average number of events, divided by time unit or other
adequate basis, during his lecture about risk equations in the common reliability
engineering approaches (class notes, February 6, 2015).
However, it is not easy to actually measure this rate because of the limitation of taking
into account the same situation with and without the tool kits of e-navigation. For
example, the Danish Maritime Authority (DMA) and the Royal Danish Administration
of Navigation and Hydrography (RDANH) carried out a risk analysis of navigational
safety in Danish waters in 2002. The report commented that “the risk reduction factor as
the effects of implementing the selected RCOs, including VTS, AIS and ECDIS, by the
expected number of spills after implementation of the RCOs, divided by the number of
expected spills before implementation of the RCOs” (p. 8, DMA & RDANH, 2002).
Like the above case, because of similar limitations, the coefficient as the rate of risk
reduction, which was estimated by the FSA team, was quantified in a qualitative way by
experts through a workshop as described in paragraph 3.2. With regard to this, the IMO
document MSC 83/INF.2. Annex also guides that “Quantification makes use of accident
and failure data and other sources of information as appropriate to the level of analysis.
Where data is unavailable, calculation, simulation or the use of recognized techniques
for expert judgement may be used” (para. 6.2.2).
47
However, even though it is difficult dissertation assignment helpto quantify the coefficient, it should be noted that
the coefficient acts as the most important factor to quantitatively evaluate the effects of
e-navigation on reducing accidents according to each detailed direct cause of the vessel
accident.
Therefore, further investigation in quantifying the coefficient by a quantitative
methodology might be necessary in order to provide a more reliable rate of reducing
accidents by implementing e-navigation. In other words, the coefficient needs to be
quantified based on a more quantitative relationship between accident types and
detailed direct causes as well as the relationship between the RCOs and their rate of risk
reduction. With regard to this, the Bayesian Network (BN) might be a tool to quantify
the coefficient.
For example, Li, Yin, Yang and Wang (2011)19 introduced the BN, in their research
“The Effect of Shipowners’ Effort in Vessels Accident: A Bayesian Network Approach”,
as “By taking into account different actors (i.e. age, size, etc.) and their mutual
influences, maritime risk assessment using the BN enables to identify the factors that
have the greatest impact on the accident occurrence” (p. 352, Chapter 5).
Besides the above case, there have recently been many cases to apply the use of BN as a
tool for modeling and analyzing vessel accidents, for example, “Analysis of Loss of
Position Incidents for Dynamically Operated Vessels” (Stenvågnes Hauff, 2014), and
“An Analysis on Incident Cases of Dynamic Positioning Vessels” (Chae & Jung, 2015).
Further, the FSA guideline, MSC 83/INF.2. Annex, also recommends BN as one of the
methods that could be used, if appropriate (p. 9).

19
With regard to calculation of the probability of accident, Li et al. (2011) criticized that “Traditional
and the most common way to estimate the prior probability of accidents is by expert estimation. There
are some typical problems associated with using the subjective probability, provided by expert, as a
measure of uncertainty in risk analysis” (p.337, Abstract).
48
4. ANALYSIS OF KOREAN-RELATED ACCIDENTS (2009-2013)
4.1 Introduction
This chapter analyzes the Korean investigation statistical accidents data20 for all ships in
Korean water areas and all Korean-flagged ships worldwide over the period of 2009 to
2013; this data having been collected from the KMST. The analysis is based on the
following:
 The trend of accident’ volume according to the accident types
 The types of accidents with direct causes according to each ship’s category;
SOLAS ships and non-SOLAS, non-fishing vessels and fishing vessels
– Accident types : collisions and groundings, and others
 The direct causes ; human errors, technical failures and external factors
 The statistics are analyzed by number of vessels, not in number of events.

20
There have been two kinds of statistics related to marine accidents; one of them is the statistics
provided by the KMST that are mainly based on vessel accidents, and the other one is the statistics
provided by the Korean Coast Guard that are mainly based on their rescue activities. Because of the
difference in the scope and purpose of producing the statistics between these two organizations, there
have been differences in the figures of their statistics respectively, causing some confusion to the
public in Korea because both statistics are seemed to be very similar each other to the common people.
Because of this, KMST had began to produce the incorporated statistics combining the both statistics
of from 2008 since 2014, while the former statistics that KMST had been producing until 2013 were
kept left. For the purpose of focusing on the vessel accident oriented data, this paper is to analyze the
statistics produced by KMST, which were produced based on the marine accident investigation code of
IMO.
49
With regard to the scope of a ship’s type, unlike the ones used by the FSA team, the
author includes all kinds of ships involved in accidents in Korean waters and all Koreanflagged ships worldwide. It is because the scope of SMART -navigation services
includes non-SOLAS ships that are engaged in domestic coastal areas, and fishing
vessels as well as SOLAS ships.
Thus, the author analyzes the effect of SMART-navigation on reducing all kinds of
accidents, unlike the IMO’s e-navigation analysis, which is limited to navigational
accidents, including collisions and groundings, of SOLAS ships. With regard to the
ship’s type, as shown in Table 16 below, the author categorized all ships into 2 groups,
non-fishing vessels and fishing vessels, and 6 sub-groups under the 2 groups. The group
of non-fishing vessels includes cargo ships, tankers, passenger ships, towing ships, and
others.
Table 16 Ship types included in the dataset
Group of Ship Type
Sub-Group of Ship Type
Ship’s Type included Size
Nonfishing
vessels
Cargo ships
All ships, which are not included in the ships below,
including general cargo carrying ships, semicontainer ships, coal carrying ships, car carriers,
refrigerated cargo ships, chilled carriers, etc
All ships
regardless of
size, including
SOLAS and
not-SOLAS
ships
Tanker
Dangerous cargo carriers, LPG and LNG carriers,
Chemical Tankers, Product Oil carriers, etc.
Passenger
ships
Car-ferries, Cargo-Passenger carriers, and other
ferries and passenger ships
Towing ships All kinds of tugs and towing ships
Other ships Barges, dredging ships, leisure boats, yachts, etc
Fishing vessels All kinds of fishing vessels
Source: Categorized based on the descriptions of KMST investigation statistics (2014)
50
4.2 Analyzing accidents
4.2.1 Historical trends of accident volume
Figure 8 and Table 17 below show the historical trends of vessel accidents based on the
KMST investigation statistics during the last 5 years from 2009 to 2013. The total
number of annual accidents during the last 5 years shows a rising trend until 2011, but
decreasing trend after that as shown in Figure 8. However, over the period from 2009 to
2013, non-fishing vessel accidents have a rising trend in general, while fishing vessel
accidents have a decreasing trend in general even though there was a fluctuation in 2011
due to the rapid rise in collisions as shown in Table 18.
Table 17 Historical trend of accidents by ship’s type
Ship Type 2009 2010 2011 2012 2013 Sum
NonFishing
vessel
Cargo 89 105 99 89 88 470 (9.6%)
Tanker 20 42 37 43 44 186 (3.8%)
Passenger 9 18 19 26 20 92 (1.9%)
Towing 61 117 126 122 80 506 (10.4%)
Others 20 13 38 35 30 136 (2.8%)
Total 199 295 319 315 262 1390 (28.5%)
Fishing 742 680 890 647 522 3481 (71.5%)
Total 941 975 1209 962 784 4871 (100%)
Source: KMST investigation statistics and data base (2014)
Figure 8 Historical trend of accidents by ship’s type
Source: KMST investigation statistics and data base (2014)
51
4.2.2 Historical trend of accident types
Table 18 and Figure 9 show the ratio of categorized types of accidents according to ship
type by percentage, for all ships in Korean water areas and all Korean-flagged ships
worldwide from 2009 to 2013. 64.1% of non-fishing vessel accidents involved
navigational accidents, including collisions and groundings. In more detail, 37.2% of
SOLAS ship accidents and 26.9% of non-SOLAS ship accidents were navigational
accidents. The figure for SOLAS ship navigational accidents, 37.2%, is 6% lower than
NMA’s statistics, 43.2%.
However, in the case of calculating all accidents by both SOAS and non-SOLAS ships,
more than 43.5 % were involved in navigational accidents, including 18.3% for nonfishing vessels and 25.1% for fishing vessels. This figure is similar to the statistic,
43.2% that the FSA team obtained based on IHS Fairplay.
Table 18 Accident type distribution
Accident Ship Type 2009 2010 2011 2012 2013 Sum
Collision
Non-Fishing 122 172 173 168 121 756
(15.5%)
Fishing 224 205 269 174 168 1040
(21.4%)
Subtotal 346 377 442 342 289 1796
(36.9%)
Grounding
Non-Fishing 21 33 26 24 31 135
(2.8%)
Fishing 27 36 46 38 40 187
(3.8%)
Subtotal 48 69 72 62 71 322
(6.6%)
Navigationa
l Accidents
Non-Fishing 143 205 199 192 152 891
(18.3%)
Fishing 251 241 315 212 208 1227
(25.2%)
Subtotal 394 446 514 404 360
2118
(43.5%)
Other Non-Fishing 56 90 120 123 110 499
52
(10.2%)
Fishing 491 439 575 435 314 2254
(42.3%)
Subtotal 547 529 695 558 424 2753
(56.5%)
Total
Non-Fishing 199 295 319 315 262 1390
(28.5%)
Fishing 742 680 890 647 522 3481
(71.5%)
Total 941 957 1209 962 784 4871
(100%)
Source: KMST investigation statistics and data base (2014)
Figure 9 Accident type distribution (2009-2013)
Source: KMST investigation statistics and data base (2014)
4.2.3 Direct causes of accidents
This study analyzed the distribution of accident causes based on the methodology
performed by KMST as shown in Figure 10: (1) the accidents are listed; (2) the direct
causes are identified; and (3) the root causes are identified.
The KMST statistics classify the accident causes into five groups, including human error,
technical failure, external factors, inadequate handling of machinery and cargo, and
others as shown in Table 19.
Non-Fishing and Fishing
53
Figure 10 Methodology to identify the direct causes of accidents
Source: KMST investigation statistics and data base (2014)
Table 19 and Figure 11 demonstrate that most of the navigational accidents were caused
by human error: 90.7 % of all navigational accidents (collisions and groundings) were
caused by human error, and also 35.1 % of other accidents were caused by human error.
The percentage for navigational accidents is greater than the one from NMA statistics,
65%, meaning that there would be more possibilities to reduce accidents caused by
human error in the case of Korea.
Table 19 Direct cause distribution by accident type
Direct Causes
Navigational Accidents
Others Sum
Grounding Collision Sum
Human Errors 273
(84.8%)
1647
(91.7%)
1920
(90.7%)
965
(35.1%)
2885
(59.2%)
Inadequate Handling machineries or
cargos
4 7 11 1236 1247
(25.6%)
Technical Failures 1 2 3 175 178
(3.7%)
External Factors 41 41 19 60 (1.2%)
Others 44 113 157 355 512
(10.5%)
Total 322
(100%)
1796
(100%)
2118
(100%)
2753
(100%)
4871
(100%)
Source: KMST investigation statistics and data base (2014)
54
Figure 11 Direct cause distribution by accident type (2009-2013)
Source: KMST investigation statistics and data base (2014)
Table 20 shows the distribution of direct causes in more detail: 88.1% among the
navigational accidents of non-fishing vessels and 92.0% of fishing vessel accidetns were
caused by human error. These figures are higher than the one from NMA statistics,
65%21
. However, in the case of calculating all kinds of accidents, including navigational
accidents and others involving all kinds of ship types, 59.2% were caused by human
error. This figure is more similar to the statistic, 65% that the FSA team obtained based
on IHS Fairplay.
Table 20 Direct cause distribution
Direct
Cause
Non-Fishing Fishing Vessels
Navigational Accident Non- Total
Nav.
SubTotal
Navigational Accident NonNavi
SubColl Gro Sum Grou Colli Sum Total
Human
Error
681
(90.1)
104
(77.0)
785
(88.1)
255
(51.1)
1040
(74.8)
169
(90.4)
966
(92.9)
1135
(92)
710
(31.8)
1845
(53)
2885
(59.2)
Technical
Failure 2 2 43 45 1 1 132 133 178
Inadequate
Handling 3 3 6 114 120 1 4 5
1122
(49.8) 1127 1247
External
Factors 25 25 7 32 16 16 12 28 60
Others 45 28 72 80 152 16 60 76 272 348 501
Total 756
(100)
135
(100)
891
(100)
499
(100)
1390
(100)
187
(100)
1040
(100)
1227
(100)
2254
(100)
3481
(100)
4871
(100)
Source: KMST investigation statistics and data base (2014)

21
see Annex 1 of NAV 59/6 (p. 14)
55
Table 21, and Figures 12 and 13 show the distribution of detailed causes of human errors
in the case of navigational accidents. Among them, “Inadequate observation” (70.4%),
“Inadequate ship maneuvering” (8.0%), “Inadequate actions to avoid collision” (8.0%),
and “Inadequate positioning” (5.2%) are shown as the most significant causes for human
errors.
Table 21 Human error cause distribution
Human error
Non-Fishing Vessel Fishing Vessel
Navigational Accident Total Non
–
Navi
SubTotal
Navigational Accident Non
–
Navi
SubTotal Colli
sion
Groun
ding Sum Colli
sion
Gro
undi
ng
Sum
Inadequate
observation
531
(78.0)
22
(21.5)
553
(70.4)
42
(16.5)
595
(57.2)
815
(84.4)
49
(29.0)
864
(76.1)
357
(50.3)
1221
(66.2)
1816
(62.9)
Over loading 1 1 3 3 4
Failure to
equipments 3 3 3
Other
Navigational
failure
19
(2.8)
5
(4.8)
24
(3.1)
38
(14.9)
62
(6.0)
10
(1.0)
11
(6.5)
21
(1.9)
165
(23.2)
186
(10.1)
248
(8.6)
Negligence of
duty
4
(0.6)
5
(4.8)
9
(1.1)
2
(1.3)
11
(1.1)
7
(0.7)
4
(2.4)
11
(1.0)
1
(0.1)
12
(0.7)
23
(0.8)
Pilot
error/violations 5
5
(0.6) 7 12 12
Inadequate
Anchoring 1 2
3
(0.4) 1 4 3 3 7
Inadequate safety
management
1 1
2
(0.3) 1 3 4 4 7
Not observing
safety manual on
board
1
(0.1)
1
(0.2)
70
(27.5)
71
(6.8)
1
(0.6)
1
(0.1)
93
(13.1)
94
(5.1)
165
(5.7)
Inadequate
positioning
41
(39.4)
41
(5.2) 16 57
(5.5)
1
(0.1)
90
(53.
5)
91
(8.0)
15
(2.1)
106
(5.7)
163
(5.6)
Inadequate
Maneuvering
52
(7.6)
11
(10.6)
63
(8.0)
45
(17.6)
108
(10.4)
17
(1.8)
4
(2.4)
21
(1.9)
34
(4.8)
55
(3.0)
163
(5.6)
Inadequate
departure
preparing
2 2 1 1 3
56
Inadequate actions
to avoid collision
63
(9.3)
63
(8.0)
63
(6.1)
96
(9.9)
96
(8.5)
96
(5.2)
159
(5.5)
Inadequate Course
plan and keeping
2
(0.3)
1
(1.0)
3
(0.4)
3
(1.2)
6
(0.6)
1
(0.1)
1
(0.6)
2
(0.2)
1
(0.1)
3
(0.2)
9
(0.3)
Violation of
COREG 7 1
8
(0.7) 8
8
(0.3)
Lack of sailing
plan 2
2
(0.3) 1 3 1
1
(0.1) 1 2
5
(0.2)
Lack of preparing
heavy weather
2
(0.3)
13
(12,5)
15
(1.9)
19
(7.5)
34
(3.4)
6
(0.6)
7
(4.1)
13
(1.1)
29
(4.1)
42
(2.3)
76
(2.6)
Inadequate
Management 1
1
(0.2) 7 8 6
6
(0.5) 6
14
(0.5)
Total 681 104 785 255 1040 966 169 1135 710 1845 2885
Source: KMST investigation statistics and data base (2014)
Figure 12 Human error cause distribution of navigational accidents
Source: KMST investigation statistics and data base (2014)
Non-Fishing Vessels & Fishing Vessels
Non-Fishing Vessels
Fishing Vessels
57
Figure 13 Human error cause distribution of all accidents
Source: KMST investigation statistics and data base (2014)
Table 22 and Figure 14 show the distribution of detailed causes of technical failures,
showing that few navigational accidents are caused by these causes; 1.1% for nonfishing vessels and 0.6% for fishing vessels. Totally, for all kinds of ships and accidents,
“Electronic facility deficiency” (38.8%), “Other machinery deficiency” (14.5%), “Main
Engine trouble” (14.0%), and “Deficiency in closing” (5.2%) are shown as the most
significant causes of technical failures.
Table 22 Technical failure cause distribution
Technical Failures
Non-Fishing Vessels Fishing Vessel
Total
(%)
Navigational
Accident NonNavi.
SubTotal
Navigational
Accident NonNavi.
SubTotal Col Gro sum Col Gro sum
Other machinery
deficiency 8 8 18 18 26
(14.5)
Fatigue of Hull 12 12 10 10 22
(12.4)
Electronic facility 8 8 61 61 69
Total
 Non-Fishing Vessels
 Fishing Vessels
 Others
58
deficiency (38.8)
Steering gear
related deficiency 4 4
4
(2.2)
Auxiliary
machinery
deficiency
1 1 7 7
8
(4.5)
Main Engine
trouble 2 2 2 4 21 21 25
(14.0)
Deficiency in
closing 10 10 10 10 20
(11.2)
Loading/Unloading
facility deficiency 2 2
2
(1.1)
Deficiency of Nav.
equipments 1 1 1 2
2
(1.1)
Total 2
2
(1.1)
43
(24.1)
45
(25.2)
1
(0.6)
1
(0.6)
132
(74.2)
133
(74.7)
178
(100)
Source: KMST investigation statistics and data base (2014). Unit of figures in blank: %
Figure 14 Technical failure cause distribution
Source: KMST investigation statistics and data base (2014)
Table 23 and Figure 15 show the distribution of detailed causes of external factors,
revealing that “Other ship’s errors” (85%) is the most significant cause. This cause was
accounted for 100% of navigational accidents among non-fishing vessels, and 68.3% of
navigational accidents among total accidents.
59
With regard to external factors, the cause “Other ship’s errors” could be argued as being
a human error cause. Adding it to the human error category brings the share of human
error up to 90.9% for navigational accidents of non-fishing vessels, 93.3% for
navigational accidents involving fishing vessels, and 60.2% for all kinds of accidents
involving both types of vessels.
Table 23 External factors distribution
External
Factors
Non-Fishing Vessels Fishing Vessels
Total Navigational
Accident
Non
–
Nav
SubTotal
Navigational
Accident
Non
–
Nav
SubTotal Col Gro sum Col Gro sum
Other ship’s
errors
25 25 25 16 16 10 26 51
(85%)
Deficiency
of shore
facilities
7 7 1 1
8
(13.3%)
Deficiency
of AtoN
facility
1 1
1
(1.7%)
Total 25 25 7 32 16 16 12 28 60
Source: KMST investigation statistics and data base (2014)
Figure 15 External factors distribution
Source: KMST investigation statistics and data base (2014)
60
Table 24 and Figure 16 show the distribution of detailed causes for the inadequate
handling of machinery or cargo, showing that “Lack of Engine Maintenance” (83.4%) is
the most significant cause. In more detail, the cause distribution of “Lack of Engine
Maintenance” was 63.1% among navigational accidents involving non-fishing vessels
and 80% among navigational accident involving fishing vessels.
Other significant causes in this category were “Lack of Maintenance of
steering/navigational gears” (8.4%), “Inadequate Fire machinery” (3.7%) and “Lack of
checking fuel oil, lubrication oil” (2.0%).
Table 24 Inadequate handling machinery or cargo cause distribution
Inadequate
Handling
Non-Fishing Vessels Fishing Vessels
Navigational Accide Total nt NonNav SubTotal
Navigational
Accident Non-Nav SubTotal Col Gra sum Other Col Gra Sum Other
Lack of Eng.
Maintenance
3
(100)
3
(100)
6
(100)
72
(63.1)
78
(65)
3
(75)
1
(100)
4
(80)
958
(85.4)
962
(85.4)
1040
(83.4)
Lack of checking
fuel oil, lubrication
oil
7 7 1 1 17 18 25
(2.0)
Inadequate handling
dangerous cargo 3 3 1 1 4
Self-ignition 1 1 4 4 5
Inadequate
Handling cargo 3 3 5 5 8
Lack of
Maintenance of
steering/nav.gears
9 9 96 96 105
(8.4)
Inadequate Fire
machinery 9 9 37 37 46
(3.7)
Inadequate Loading
Cargo 5 5 2 2 7
Explosion of cargo 4 4 4
Cargo shifted 1 1 2 2 3
Total 3
(100)
3
(100)
6
(100)
114
(100)
120
(100)
4
(100)
1
(100)
5
(100)
1122
(100)
1127
(100)
1247
(100)
Source: KMST investigation statistics and data base (2014)
61
Figure 16 Inadequate handling machinery or cargo cause distribution
Source: KMST investigation statistics and data base (2014)
Table 25 shows the distribution of detailed causes for other factors, showing two kinds
of causes: 75.4 % of irresistible causes such as natural disasters and typhoons, and
24.6% of the unknown and others. The “unknown” and “others” are 7.8% among the
total number of accidents. The direct cause “others” could also be argued as being a
human error because it is composed of inadequate management of a ship’s operation and
inadequate loading of cargo or passengers according to the KMST’s descriptions.
Table 25 Other Factors Distribution (Korea related)
Others
Non-Fishing Vessels Fishing Vessels
Navi. Accident Total
Other sum
Navi. Accident Other sum Col Gro sum Col Gro sum
Other 14
(31.1)
5
(17.9)
19
(26.0)
46
(57.5)
65
(42.5)
18
(30)
3
(18.8)
21
(27.6)
123
(45.2)
144
(41.4)
209
(41.7)
Unknown 25
(55.6)
5
(17.9)
30
(41.1)
18
(22.5)
48
(31.4)
41
(68.3)
1
(6.3)
42
(55.3)
79
(29.0)
121
(34.8)
169
(33.7)
irresistible
natural disasters
6
(21.4)
6
(8.2)
4
(5.0)
10
(6.5)
7
(43.8)
7
(9.2)
47
(17.3)
54
(15.5)
64
(12.8)
typhoon 6
(13.1)
12
(42.9)
18
(24.7)
12
(15.0)
30
(19.6)
1
(1.7)
5
(31.3)
6
(7.9)
23
(8.5)
29
(8.3)
59
(11.8)
Total 45
(100)
28
(100)
73
(100)
80
(100)
153
(100)
60
(100)
16
(100)
76
(100)
272
(100)
348
(100)
501
(100)
Source: KMST investigation statistics and data base
62
5. DISCUSSION OF THE EFFECTS OF E-NAVIGATION
5.1 Development of the formula to evaluate the effects of e-navigation
The author, in Chapters 2 and 3, examined the IMO’s e-navigation related documents,
and especially the SIP set out in NCSR 1/28. Annex 7 in order to determine the
methodology to discuss the effects of SMART-navigation on reducing accidents. As a
result, the author determined the rate of risk reduction of “65%” that the FSA team
calculated through a generic risk model and an expert workshop, as the coefficient to
calculate the effects of SMART-navigation as described in Chapter 3.
However, the rate of the risk reduction of “65%” does not mean the rate to reduce the
volume of accidents, but the rate to reduce the percentage of each detailed direct cause
reducible by RCOs, which is extracted from each direct cause, in terms of the potential
loss of lives (PLL) as described in Tables 13 and 14 in Chapter 3.
This means that the rate of “65%” should be converted into the actual rate of risk
reduction by RCOs for each direct cause as well as the total actual rate of risk reduction
to be reduced by RCOs for all direct cause in order to calculate the actual volume of
selected accidents to be reduced by RCOs in terms of percentage among total accidents.
Thus, the author developed the following formulas in order to calculate the effects of
SMART-navigation on reducing accidents in terms of the actual volume of the relevant
accidents by RCOs:
63
AVSA = ∑(RSADⅹ ARDCHF/TF/EF)
= ∑(RSADⅹcⅹ∑RDDCHF/TF/EF)
= cⅹ∑(RSADⅹ∑RDDCHF/TF/EF)
where is :
c = Coefficient (65% for SOLAS ships, 55% for non-SOLAS ships)
AVSA = Actual Volume of selected accidents to be reduced in terms of percentage
among total accidents
RSAD = Rate of selected accident distribution
ARDC = Actual Rate of risk reduction of each direct cause to be reduced
RDDC HE = Rate of risk reduction of detailed direct cause of Human Error to be reduced
RDDC TF = Rate of risk reduction of each detailed direct cause of Technical Failure to be
reduced
RDDC EF = Rate of risk reduction of each detailed direct cause of External Factor to be
reduced
In more detail, the above formulas are explained as follows :
 the actual rate of risk reduction to be reduced by RCOs for each direct cause
(ARDC) = the coefficient (65%)ⅹ ∑(each percentage of the detailed direct
causes of relevant direct cause to be reduced by RCOs)
 the total actual rate of risk reduction to be reduced by RCOs for all direct cause
(Total ARDC) = ∑(the percentage of each direct cause among total direct cause
ⅹ each actual rate of risk reduction to be reduced by RCOs for relevant direct
cause) = ∑(the percentage of each direct cause among total direct cause ⅹ ((the
coefficient (65%))ⅹ ∑(each percentage of the detailed direct causes of relevant
direct cause)))
 the actual volume of selected accidents to be reduced by RCOs in terms of
percentage among total accidents
= the percentage distribution of the selected accidents among total accidents ⅹ
total actual rate of risk reduction to be reduced by RCOs for all direct cause
64
= the percentage distribution of the selected accidents among total accidents ⅹ
∑(the percentage 22 of each direct cause among total direct cause ⅹ ((the
coefficient (65%))ⅹ ∑
23(each percentage of the detailed direct causes of each
direct cause)))
For example, in the case of the NMA investigation statistics that were used in the FSA,
the actual volume of navigational accidents, including collisions and groundings, to be
reduced by RCOs in terms of percentage among total accidents is calculated as 22.8% by
applying the above formula as follows:
 43.2% 24 (the percentage distribution of navigational accidents among total
accidents) ⅹ ∑(65% (the percentage of human error) ⅹ 61.1% ((the
coefficient (65%) ⅹ ∑(the percentage of the detailed direct causes of the human
error to be reduced by RCOs)) + 18% (the percentage of technical failures) ⅹ
53.3% ((the coefficient (65%)ⅹ ∑(the percentage of the detailed direct causes
of the technical failures to be reduced by RCOs)) + 17% (the percentage of
external factors) ⅹ 19.5% ((the coefficient (65%)ⅹ ∑(the percentage of the
detailed direct causes of the external factors to be reduced by RCOs))) = 43.2%
ⅹ ∑((65% ⅹ61.1%)+(18%ⅹ53.3%)+(17%ⅹ19.5%)) = 43.2%ⅹ52.6% =
22.8%

22 The percentage of each direct cause among total direct cause : 65% for the human error, 18% for the
technical failures and 17% for the external factors, respectively (see Table 29 in paragraph 5.3.4.1).
23
Each percentage of the detailed direct causes of each direct cause to be reduced by RCOs is 94% for
the human error, 82% for the technical failures and 30% for the external factors, respectively (see
Table 29 in paragraph 5.3.4.1).
24
see Table 3 in the paragraph 2.2.2
65
For the purpose of applying the above formula to non-SOLAS ships, this chapter
overviews SMART-navigation, which focuses on the services for non-SOLAS ships as
well as SOLAS ships as mentioned in the paragraph 1.1. The RCOs that are applicable
to non-SOLAS ships, including fishing vessels, are to be identified. Further, the author
discusses the effects of SMART-navigation on reducing accidents based on the results of
calculations by applying the above formula.
5.2 The SMART-navigation concept
5.2.1 Background of SMART-navigation
The Ministry of Oceans and Fisheries (MOF) established the SMART-navigation
strategy to implement IMO’s e-navigation concept in 2013, and finished the feasibility
study on developing necessary core technologies and infrastructures to implement the
strategy in 2014. The project to implement the strategy has been undertaken sparsely.
SMART-navigation is the Korean approach to implementing the IMO e-navigation
concept in both Korean waters and Korean-related ships. Beside the scope of IMO enavigation, SMART-navigation even includes services for non-SOLAS ships, including
fishing vessels as well as non-fishing vessels engaging in domestic coastal areas.
The strategic implementation plan for SMART-navigation was basically composed of 16
kinds of MSPs as adopted in the IMO’s SIP. Non-SOLAS ship are more vulnerable25 to
accidents than SOLAS ships. This is, among others, because of lack of capacity of
navigational equipment, higher workload on board and less safety information provided

25
According to the preliminary feasibility study to implement the IMO e-Navigation (MOF, 2014),
89.04% among all accidents for all ships in Korean waters and all Korean-flagged ships during last 5
years from 2009 to 2013 happened to non-SOLAS ships, while 10.06% were SOLAS ships (p. 5-44)
66
by shore based stations. Consequently, SMART-navigation concept even provides the
much more enhanced services for non-SOLAS ships.
5.2.2 Components of the SMART-navigation
5.2.2.1 Main services of the SMART-navigation
According to the preliminary feasibility study on implementing IMO’s e-navigation
(MOF, 2014), the strategy of this project was developed through the following steps: (1)
identifying the user needs of all stake-holders; (2) a gap analysis; (3) analyzing the direct
causes of accidents; (4) identifying target services based on the results of the former
steps; and (5) a risk and cost-benefit analysis. In addition to the study, the MOF
conducted “A fundamental study on maritime accident prevention systems” and
completed the definition of the main services of the SMART-navigation as summarized
in Table 26:
Table 26 Main services of the SMART-navigation
Service Groups and its concept Main Functions Relevant
MSPs

The Services to increase the safety
and efficiency of vessel traffics by
using safety information, which is
based on CMDS, to the vessel traffic
management and coordination
 Providing VTS information to ship : other
ships’ position, destination, and intention of
movement; any changes in safety
information of the VTS areas
 Monitoring the ship’s routing plan
 Supporting navigation decision-making
 Organizing vessel traffic
 Providing port information : local port; pilotage, berthing and un-berthing
– MSP 1
– MSP 2
– MSP 3

Serve to increase the efficiency of
maritime related businesses as well
as the safety of navigation by
 Maritime safety information (MSI) service
 Safety fishing related information service
 Pilot-age information service
 Single window service for automatic
reporting to shore for decreasing crews’
unnecessary work burden and making them
– MSP 4
– MSP 5
– MSP 6
– MSP 7
– MSP 8
– MSP11
67
improving their efficiencies through
automation of creating, delivering,
utilizing and inter-connecting the
maritime information.
focus on safety of navigation
 Transferring nautical charts and nautical
publications for supporting automatic updating them electronically
 Meteorological information service for
safety navigation and fishing activities
 Real-time hydrographic and environmental
information service
– MSP12
– MSP14
– MSP15 Service to prevent the potential
accident causes in advance by
proactively managing the ships and
areas, which are identified as being
vulnerable to accidents based on
utilizing the real time of relevant
statistics and local situation data
 Managing ships and areas, which are
identified as being vulnerable to accident, in
timely manner, based on real-time statistics
and information
 Supporting safety navigation decisionmaking for their proactive responding to
avoid accidents
 Analyzing maritime safety factors based on
Big-data
 Providing safety information to ships, which
are vulnerable to accidents, and supporting
their safety decision-making
 Providing service of streaming electronic
navigational charts (ENCs) to ships of
medium and small size
 Remote supporting and managing safety
training crews
Korean
version
of
special
services
for nonSOLAS
ships

Service to minimize loss of lives and
properties from accidents and
variable emergencies happened in
remote water areas by prompt and
comprehensive responding to them
 Remote telemedical Helpance in order to
prevent delaying in remedial treatment
 Helping ships’ emergency responding
 Supporting SAR operation
 Supporting maritime affairs, regarding MAS
 Helping remote crews’ training to increase
their competences
– MSP9
– MSP10
– MSP16

Service to increase maritime security
by real-time monitoring and
managing all maritime domains in
Korean water areas
 Comprehensive recognizing and responding
to all maritime domains over all Korean
water areas
 Providing information regarding the illegal
unreported unregulated fishing activities
 Providing information regarding oil spill
 Supporting activities preventing illegal
discharge of wastes/pollutants from ships
 Supporting the other activities related to
maritime security
Korean
version
of
service
Source: A fundamental study on maritime accident prevention systems (pages 162-163, MOF, 2015)
68
5.2.2.2 SMART-navigation Services for non-SOLAS ships
According to Table 26, SMART-navigation will introduce more enhanced special
services26 for non-SOLAS ships, which are designed as SMART-phone like services for
examples: (1) the service supporting ship’s routing for ships vulnerable to accidents such
as coastal ferries and dangerous cargo carriers as shown in Figure 17; (2) the service
supporting the safety of fishing vessels; (3) the electronic navigation chart (ENC)
streaming service for small coastal ships; (4) and the single window service.
Figure 17 Concept of service for non-SOLASe ships
Source : A fundamental study on maritime accident prevention systems (page 176, MOF, 2015)
5.2.3 Architecture of SMART-navigation
One of the most important prerequisites to implement e-navigation is the system
architecture for information exchange, so that, the SMART-navigation services can be
established as shown in Figure 18. The architecture was designed according to IMO enavigation philosophy, enabling the ship-borne and shore-based users to exchange

26 For detailed information on each special services for non-SOLAS ships, see page 175 to 179, A
fundamental study on maritime accident prevention systems (MOF, 2015)
69
information using S-10027 format and based on the maritime cloud service concept via
various communication networks.

Figure 18 Overall architecture of the SMART-navigation (MOF,2015)

27
It has been designated as the common maritime data structure (CMDS) for e-navigation as described in
the IMO e-navigation SIP.
70
The communications network might be the most important factor in realizing the aims of
e-navigation. There are a number of limitations in the current maritime communication
network, as shown in Table 27 below, which are based on analog communications with
the minimum capacity for essential communication and with regard to safety of
navigation and emergency situations.
Further, even Korean fishing vessels of less than 5 tons, which represent the majority, at
more than 87%, among all Korean fishing vessels, have yet to be equipped with
navigational or emergency communication equipment.
Table 27 Communication networks around the Korean coastal water areas
Source: A fundamental study on maritime accident prevention systems (MOF, 2015, page 36)
With regard to this, SMART-navigation is to provide the LTE-Maritime communication
network28
as a platform for non-SOLAS ships in order to implement the necessary enavigation services.

28
For LTE-Maritime service, MOF had been allocated the necessary digital communication frequency by
the Ministry of Science, ICT and Future Planning (MSIP) in 2014. According to the media, MOF
launched the project to establish LTE-M communication network in 2015, which is carried out by SKT
telecom (SK Telecom, 2015, August 2).
71
In addition, the relevant communication networks for e-navigation services are to be
provided with a data structure based on the CMDS29, including the VHF Date Exchange
(VDE), digital HF/MF and satellite-based communication, configuring their concept as
shown in Figure 19 below (MOF, 2015).
Figure 19 Communication architecture for the SMART-navigation
Source: A fundamental study on maritime accident prevention systems (MOF,2015,page 228)
5.3 Accident reducing effects of SMART-navigation
5.3.1 Discussion of detailed direct causes reducible by RCOs
The list of the detailed direct causes categorized in this dissertation and the NMA
statistics are different from each other as examined in Chapters 3 and 4. For example,
among human error, NMA statistics include detailed direct causes such as

29
M. Jonas and J.H. Oltmann (2013) regarded the CMDS as the most important pillar for e-navigation,
providing the “cement” to the other pillars, including (1) the overarching architecture of e-navigation
and generalities, (2) shipboard equipment fit for e-navigation, (3) MSPs, (4) communication
technologies, (5) resilient PNT, and (6) shore-based infrastructure.
72
“injury/sickness”, “intoxicated” and “Fatigue/work overload”, while KMST statistics do
not. Such causes are underlying factors rather than direct causes.
However, this does not mean that the accidents caused by these underlying factors were
excluded in the KMST investigation statistics. The KMST statistics were produced
based on the direct causes only, not based on the underlying factors. That is why the
author could not analyze and insert such causes in the detailed direct cause lists. In
contrast, there are many more detailed direct causes with different names that the KMST
statistics contain and the NMA statistics do not, and vice versa.
With regard to this, the author has identified the detailed direct causes of KMST, as
shown in Table 28, based on the description given in the instructions for the KMST
investigation statistics, in order to make conditions similar to the category of the NMA
statistics that the FSA team identified and used for the risk and cost-benefit analysis.
For example, the author includes some detailed direct causes, which have different
names but are considered to be reducible by RCOs, into the relevant group of the direct
cause as follows:
 among the detailed direct causes of the inadequate handling of machinery or
cargo, “Lack of checking fuel oil, lubrication oil”, “Lack of Maintenance of
steering/navigational gears” and “Inadequate Fire machinery” are included in
the list of detailed direct causes under technical failures; and
 among the detailed direct causes of the external factors, “Other ship’s errors”
and “Deficiency of Aids to Navigation facility External Factors” are included in
the list of the detailed direct causes under external factors.
73
In addition, the author excludes some of the detailed direct causes, which are not
considered to be reduced by RCOs as shown in Table 28. For example,
“Loading/Unloading facility deficiency”, “Main Engine trouble” of the technical failures,
and “Deficiency of shore facilities” of the external Factors were excluded.
As a result, the author extracted 3,366 accident vessels, which involved the detailed
direct causes preventable by the RCOs of e-navigation, from the total 4,871 accident
vessels.
Table 28 Identified detailed direct causes
List of Direct Causes by NMA Shuffled Direct Cause of KMST to match with NMA
Human
Errors
Inadequate observation/
inattention
Poor judgment of ship
movement
Fatigue/work overload
Poor judgment of other factors
Inadequate planning of voyage
Intoxicated
Failure to use navigational aids
Failure to give way /high speed
Lack of knowledge/skill/
training
Communication problems
Injury/sickness
Use of defective equipment
Human
Errors
(1) Inadequate observation
(2) Over loading
(3) Failure to equipments
(4) Other Navigational failure
(5) Negligence of duty
(6) Pilot error/violations
(7) Inadequate Anchoring
(8) Inadequate safety management
(9) Not observing safety manual
(10) Inadequate positioning
(11) Inadequate Maneuvering
(12) Inadequate departure preparing
(13) Inadequate actions to avoid collision
(14) Inadequate Course plan and keeping
(15) Violation of COREG
(16) Lack of sailing plan
(17) Lack of preparing heavy weather
(18) Inadequate Management
Technical
Failures
Technical failure (not related to
main engine)
Technical
Failures
(19) Other machinery deficiency
(20) Fatigue of Hull
(21) Electronic facility deficiency
(22) Steering gear related deficiency
(23) Auxiliary machinery deficiency
(24) Deficiency in closing
(25) Deficiency of Nav. equipments
74
Inadequate
Handling
machinery
or cargo
(26) Lack of checking fuel oil/lubrication
(27) Lack of Maintenance of
(28) Steering/navigational gears
(29) Inadequate Fire machinery
External
Factors
Strong currents
Severe heavy weather
External
Factors
(30) Other ship’s errors
(31) Deficiency of AtoN facility
The detailed direct causes among the lists
of the KMST, which are not
considered to be reducible by
RCOs
Technical
Failures
(32)Loading/Unloading facility
deficiency
(33)Main Engine trouble
External
Factors
(34) Deficiency of shore facilities
Inadequate
Handling
machineries
or cargos
(35) Inadequate handing IMDG
(36) Inadequate Handling cargo
(37) Inadequate Loading Cargo
(38) Lack of Eng. Maintenance
(39) Self-ignition, Explosion of cargo
(40) Cargo shifted
Others (41) Other, Unknown
(42) Irresistible natural disasters
(43) Irresistible natural disasters
(typhoon)
Source: Based on the NMA statistics and the KSMT statistics
5.3.2 Discussion of RCOs applicable to non-SOLAS ships
With regard to applying the rate of risk, the author selected the relevant RCOs based on
the scope of the SMART-navigation services related to the non-SOLAS ships as
examined in paragraph 5.2.2.1 and 5.2.2.2.
As a result, except for RCO 2 (Bridge alert management), the author identified another 6
kinds of RCOs that have the same rate of risk reduction as shown in Table 29. The rate
for non-SOLAS ship is 55% in total, which is 84.6% of the rate of risk reduction for
SOLAS ships, “65% in total”.
75
Table 29 RCOs for non-SOLAS ships
SOLAS Ships Non-SOLAS Ships
RCOs Rate of risk
reduction Remark
RCO 1 Integration of navigation information and equipment
including improved software quality assurance 11% 11% applied
RCO 2 Bridge alert management 10% – excluded
RCO 3 Standardized mode 7% 7% applied
RCO 4 Automated and standardized ship-shore reporting 8% 8% applied
RCO 5 Improved reliability and resilience of onboard PNT
systems 8% 8% applied
RCO 6 Improved shore-based services 7% 7% applied
RCO 7 Bridge and workstation layout standardization 14% 14% applied
Total 65% 55% (84.6% of 65%)
Source: Annex 1 of NAV 59/6 (pages 37-38) for SOLAS ships only.
5.3.3 Expert survey by questionnaire
The author carried out an expert survey by questionnaire30 through e-mail in order to
increase the validity of the decisions made in paragraphs 5.3.1 and 5.3.2. The survey was
focused on assessing the validity of selecting the RCOs as shown in Table 28, which are
applicable to non-SOLAS ships, and identifying the detailed direct causes as shown in
Table 29, which are reducible by the RCOs.
Seventeen persons responded in total, whose average experience working for the safety
of navigation was 14.3 years. The responders are currently working in maritime safetyrelated research and development institutes (41.2%, 7 persons), the safety management
departments of shipping industries (29.4%, 5 persons) and vessel accident investigation
agencies (29.4%, 5 persons). They were all involved in establishing the SMARTnavigation strategy directly as researchers, and indirectly as participants in the related
brainstorming sessions and workshops discussing the strategy.

30 The questionnaire was drafted according to the guideline on WMU research ethics committee.
76
With regard to the validity of Table 28, 13 persons (76.5%) supported the validity of
identifying the detailed direct causes as proposed. Among them, 4 persons (23.5%) were
of the opinion that items 33 to 38 and 43 were also partially reducible by e-navigation,
and suggested that the service of “remote monitoring ship’s systems31”, including main
engine, should be introduced to enhance the management of such items by shore side.
On the other hand, 4 persons (23.5%) pointed out that items 2, 4, 7, 17, 22 to 27, and 30
are somewhat limited in their ability to be reduced by RCOs. One person (5.9%) insisted
that the causes reducible by RCOs should be identified based on the conditions: (1)
exchanging information between ship and shore should be harmonized, and (2)
collecting, analyzing and presenting information should be harmonized between ship
and shore.
In the case of the validity of Table 29, 14 persons (94.1%) supported the validity of
selecting the RCOs that are applicable to non-SOLAS ships. Among them, 2 persons
(11.8%) even insisted that RCO 2 (Bridge alert management) should be also selected as
the RCO that is applicable to non-SOLAS ships, and, in particularly, small non-SOLAS
ships like fishing vessels need to be provided with it. On the other hand, only one person
(5.9%) was of the opinion that RCO 7 is not effective to non-SOLAS ships.
In brief, even though 23.5% of opinions differed with regard to the author’s proposals for
Table 28 and 5.9% with regard to Table 29, the majority of the respondents supported
the validity of the Tables. Further, the Tables were proposed based on reliable facts such
as the case that the FSA team selected the detailed direct causes for carrying out risk and
cost-benefit analysis of e-navigation, and the service scopes of SMART-navigation.
Therefore, the author decided to apply the Tables 28 and 29 as they are for Assessment of
the effect of SMART-navigation on reducing accidents.

31
This was one of the MSPs, but deleted. See para. 2.2.5 for the detail reason.
77
5.3.4 Effects of reducing navigational accidents by SMART-navigation
5.3.4.1 Rate of risk reduction
Table 30 Rate of reduction of direct causes by RCOs
RCOs
PLL reduction
of total
Scope of detailed direct causes
expected to be reduced by RCOs
RCO 7
Bridge and workstation layout
standardization 14%

Inadequate observation/ inattention
Poor judgment of ship movement
Fatigue/work overload
Poor judgment of other factors
Inadequate planning of voyage
Intoxicated
Failure to use navigational aids
Failure to give way /high speed
Lack of knowledge/skill/ training
Communication problems
Injury/sickness
Use of defective equipment

Technical failure (not related to main
engine)

Strong currents
Severe heavy weather
RCO 1
Integration of navigation
information and equipment
including improved software
quality assurance
11%
RCO 2 Bridge alert management 10%
RCO 4 Automated and standardized
ship-shore reporting 8%
RCO 5
Improved reliability and
resilience of onboard PNT
systems
8%
RCO 3 Standardized mode 7%
RCO 6
Improved shore-based services
7%
Total 65%
Source: Annex 1 of NAV 59/6 (pages 37-38)
Table 30 shows the rate of potential possibility to reduce the loss of lives (PLL) for
navigational accidents of SOLAS ships, including collisions and groundings, as
examined in Chapter 3. However, the rate of risk reduction, “65%”, does not mean the
rate to reduce volume of accidents, but the rate to reduce percentage of selected direct
causes of navigational accidents by RCOs in terms of PLL as described in paragraph 5.1.
78
Therefore, the author calculated the actual rate of the detailed direct causes to be reduced
by RCOs by using the formula described in paragraph 5.1. The result of the calculation
is 52.7% for SOLAS ships as shown in Table 31. The figure in blank, “( )”, is the rate for
non-SOLAS vessels. Based on Table 31, the author calculates the actual rate of the
volume of accidents to be reduced by RCOs for all ships in Korean water areas and all
Korean-flagged ships worldwide as shown in Tables 32, 33 and 34, in terms of human
error, technical failures, and external factors, respectively.
Table 31 Actual rate to reduce the direct cause of the navigational accidents
Percentage of direct
causes among
navigational
accident(%)
Selected detail direct causes
Percentage of
distribution
among direct
cause (%)32
Rate of
reduction
of risks by
RCOs
Actual rate to
reduce each
detailed direct
causes by
RCOs
Human Errors
(65%)
Inadequate observation/ inattention 28
65%
(55%)
18.2 (15.4)
Poor judgment of ship movement 17 11.2 (9.4)
Fatigue/work overload 13 8.5 (7.2)
Poor judgment of other factors 12 7.8 (6.6)
Inadequate planning of voyage 9 5.9 (5.0)
Intoxicated 3 2 (1.7)
Failure to use navigational aids 3 2 (1.7)
Failure to give way /high speed 3 2 (1.7)
Lack of knowledge/skill/ training 3 2 (1.7)
Communication problems 2 1 (1.1)
Injury/sickness 1 0.6 (0.5)
Use of defective equipment 0 0
Total rate to reduce each detailed human errors 61.1% (52%)
Total rate to reduce direct cause of Human Errors (65%*61.1% = ) 39.7% (33.8)
Technical Failures
(18%)
Technical failure (not related to main
engine)
82 65% 53.3% (45.1)
Total rate to reduce each detailed technical failures 53.3% (45.1)
Total rate to reduce direct cause of Technical Failures (18% * 53.3% = ) 9.6% (8.1)
External Factors
(17%)
Strong currents 16 65% 10.4% (8.8)
Severe heavy weather 14 9.1% (7.7)
Total rate to reduce each detailed external factors 19.5% (15.8)
Total rate to reduce direct cause of External Factors (17% * 19.5% = ) 3.3% (2.8)
Total rate to reduce navigational accidents 52.7% (44.7)
Source : Calculated based on Annex 1 of NAV 59/6 (Figures 9, 10 and 11 and Tables 11 and 12)

32 based on the Figure 4, 5 and 6 ( pages 29 to 30 of this dissertation)
79
Table 32 Human error cause distribution
Source: KMST investigation statistics and data base (2014)
80
Table 33 Technical failure cause distribution
Source: KMST investigation statistics and data base.
Table 34 External factors distribution
Source: KMST investigation statistics and data base
81
5.3.4.2 The effects of reducing accidents
Table 35, which combines Tables 32, 33 and 34, shows the apparent rate of reducing the
relevant accidents involving SMART-navigation, without classifying the ship types of
the SOLAS and Non-SOLAS ships. For example, 64.9% among total accidents,
including 22.9% for non-fishing vessels and 42.0% for fishing vessels, are expected to
be reduced by introducing e-navigation.
Table 35 Apparent effects on reducing accidents by the SMART-navigation
Accident Type Human
Errors
Technical
Failure
External
Factor
Total
Actual Effect
NonFishing
Vessels
Navigational
Accident
Actual % 803
(23.9%)
25
(0.7%)
828
(24.6%) Risk Reduction Rate 65.1% 65% 16.1%
Effect 15.6% 0.5
NonNavigational
Actual % 282
(8.4%)
64
(1.9%)
7
(0.2%)
353
(10.5%) Risk Reduction Rate 65.3% 64.9% 65% 6.8%
Effect 5.5% 1.2% 0.1%
Sum
Actual % 1,085
(32.2%)
64
(1.9%)
32
(0.95%) 1,181
(35.1%) 22.9%
Effect 21.1% 1.2% 0.6%
Fishing
Vessels
Navigational
Accident
Actual % 1,155
(34.3%)
2
(0.1%)
16
(0.5%) 1,173
(34.8%) Risk Reduction Rate 64.9% 65% 64.9% 22.5%
Effect 22.2% – 0.3%
NonNavigational
Actual % 740
(22.0%)
261
(7.8%)
11
(0.3%)
1,012
(30.1%) Risk Reduction Rate 64.8% 64.9% 65% 19.5%
Effect 14.2% 5.1% 0.2%
Sum
Actual % 1,895
(56.3%)
263
(7.8%)
27
(0.8%) 2,185
(64.9%) 42.0%
Effect 36.4% 5.1% 0.5%
Total
Actual % 2,980
(88.5%)
327
(9.7%)
59
(1.8%) 3,366
(100%) 64.9%
Effect 57.5% 6.3% 1.1%
Source: KMST investigation statistics and data base (2014)
82
However, in this table, both SOLAS and non-SOLAS ships accidents are combined, and
their rates of risk reduction are different as explained in paragraph 5.3.4.1 and as shown
in Table 31. Therefore, it is necessary to convert Table 35 again, by applying the
appropriate rates to the SOLAS and non-SOLAS ships, in order to discuss the exact
effects on reducing accidents. The converting conditions are as follow:
 The risk reduction rate for SOLAS ships by seven RCOs is 65%, while the risk
reduction rate for non-SOLAS ships by seven RCOs is 55%, which is 84.6% of
65%, as explained in paragraph 5.3.2.
 The accident distribution of SOLAS ship and non-SOLAS ship among total
accidents are 57.9% and 42.1% respectively, calculated based on Table 36.
Table 36 SOLAS and non-SOLAS ship distribution among accidents ships
Category 2009 2010 2011 2012 2013 Total
Q’ty of ships Distribution
Non
Fishing
SOLAS 119 177 171 156 163 786(57.9%) 16.27%
Non- SOLAS 71 112 138 132 119 572(42.1%) 11.83%
Total 190 289 309 288 282 1,358(100%)
Fishing Non- SOLAS 725 672 888 653 536 3,474 71.90%
Source: Preliminary feasibility study on e-navigation (p. 5-44), which was carried out by the Ministry of
Oceans and Fisheries (MOF) in 2014
Based on the above condition, the author finally calculates the effects of reducing
accidents involving SMART-navigation as shown in Table 3733
.
According to Table 37, SMART-navigation is expected to reduce more than the 56.6%
of total accidents of 3,366 vessels, including 13% of SOLAS ships and 43.6% of nonSOLAS ships, including fishing vessels.

33 To see each effect based on the total number of accidents, “4,871”, it is necessary to multiply 69.9 %
with rate calculated in these Tables: 69.9% is calculated by 3,366, divided by 4,871. This is because
that the Table 35 was calculated based on the accident vessels of 3,366 as described in the paragraph
5.3.1 and in the Table 29.
83
In the case of navigational accidents, including collisions and groundings, more than
33.9 %, composing 14.8% for non-fishing vessels and 19.1% for fishing vessels, are
expected to be reduced. Even the non-navigational accidents are expected to be reduced
up to 22.7%, including 6.2% for non-fishing vessels and 16.5% for fishing vessels. In
terms of the direct causes, 50.2% of the accidents caused by human error are expected to
be reduced, and 5.4% of the accidents caused by technical failures and 1% of the
accidents caused by external factors.
Table 37 Effects on reducing accidents by the SMART-navigation
Accident Type Human
Errors
Technic
al
Failure
External
Factor
Total
Actual Effect
NonFishing
Vessels
Navigational
accident
SOLAS
Actual % 465
(13.8%)
14
(0.4%)
828
(24.6%) 14.8%
Risk Reduction Rate 65.1% 65%
Effect 8.9% 0.3%
NonSOLAS
Actual % 338
(10.0%)
11
(0.3%)
Risk Reduction Rate 55.1% 55.0%
Effect 5.5% 0.1%
NonNavigational
SOLAS
Actual % 163
(4.8%)
37
(1.1%)
4
(0.1%)
353
(10.5%) 6.2%
Risk Reduction Rate 65.3% 64.9% 65%
Effect 3.1% 0.7% –
NonSOLAS
Actual % 119
(3.5%)
27
(0.8%)
3
(0.1%)
Risk Reduction Rate 55.2% 54.9% 55%
Effect 1.9% 0.4% 0.1%
Sum Actual % 1,085
(32.2%)
64
(1.9%)
32
(0.95%) 1,181
(35.1%) 21.0%
Effect 19.4% 1.1% 0.5%
Fishing
Vessels
Navigational
Actual % 1,155
(34.3%)
2
(0.1%)
16
(0.5%) 1,173
(34.8%) 19.1% Risk Reduction Rate 54.9% 55% 54.9%
Effect 18.8% – 0.3%
Non-Navigational
Actual % 740
(22.0%)
261
(7.8%)
11
(0.3%) 1,012
(30.1%) 16.5% Risk Reduction Rate 54.8% 54.9% 55%
Effect 12.0% 4.3% 0.2%
Sum Actual % 1,895
(56.3%)
263
(7.8%)
27
(0.8%) 2,185
(64.9%) 35.6%
Effect 30.8% 4.3% 0.5%
Total Actual % 2,980
(88.5%)
327
(9.7%)
59
(1.8%) 3,366
(100%) 56.6%
Effect 50.2% 5.4% 1.0%
Source: KMST investigation statistics and data base (2014)
84
6. CONCLUSION
This dissertation aimed to evaluate how and to what extent vessel accidents could be
reduced by introducing e-navigation application into the maritime sector. The questions
were examined by a comprehensive case study, especially investigating the Korean
shipping. Focus was laid on accidents in Korean waters and all Korean-flagged ships
worldwide as well.
For that purpose, the IMO’s methodological approach to establishing the e-navigation
SIP, and especially the methodology used for the risk and cost-benefit analysis of the
SIP has been studied and adapted to the Korean SMART-navigation project. The
SMART-navigation is reviewed, its scope of services and tool kits to be introduced, in
order to quantitatively evaluate its potential effects on non-SOLAS ships and SOLAS
ships as well.
Finally, this dissertation aims to provide a sample to IMO Member States for effectively
and efficiently introducing respectively prioritized e-navigation tool kits of e-navigation.
Member States may apply the methodology developed and applied in this dissertation to
their specific situation and especially taking into account potential effects on nonSOLAS vessels. This is suggested because the situation of maritime safety is different
from country to country while IMO’s e-navigation concept shows effects on reducing
accidents for SOLAS ships only.
85
For the mentioned purpose, the author proposed a set of formulas, to evaluate and
quantify the effects of e-navigation on reducing vessel accidents considering SOLAS but
also non-SOLAS ships. The proposed set of formulas is applicable to other Member
States of the IMO, and not only valid for the Republic of Korea.
In addition, the author provided results of evaluating the effects of SMART-navigation,
by applying the formula, as a kind of model case for other Member States references. It
is hoped that this study will be referred to the maritime safety policy bodies of the
Member States of IMO, as well as to the practices of the maritime sectors such as
shipping companies, crews on board ships and manufacturers developing e-navigation
related systems.
At the outset, in Chapter 2, the author examined IMO e-navigation tool kits, and
especially how they had been developed and how they are assessed to be able to reduce
the risks causing navigational accidents, including collisions and groundings, by up to
65%.
As a result, the author identified 3 kinds of tool kits, including 5 kinds of solutions, 7
kinds of RCOs and 16 kinds of MSPs. They are all included in the SIP of IMO enavigation concept.
E-navigation, among others, aims to increase the capability of shore based stations to
manage and Help in improving safety of navigation by supporting decision making and
provision of safety information to crews on board ships, so as to prevent or detect human
errors that might lead to accidents.
Human error that causes accidents is one of the most significant concerns of maritime
sectors. In fact, according to numerous sources most accidents happen mainly due to
86
human error, and such accidents even have a rising trend. Human error is considered to
be mainly rooted in fatigue, the lack of situational awareness and the safety culture of
crews on board ships.
There have been limitations to preventing human error in terms of quantity and quality
of information, complexity, lack of providing sufficient support to decision making and
to effectively help avoid dangerous navigational situations, and lack of response to
emergency situations in a timely and adequate manner. Further, this is clearly supported
by user needs, which reflect the concerns experienced most often during their work, as
surveyed for e-navigation as shown, e.g., in the IMO document NAV 55/INF. 9.
However, these problems are expected to be solved by e-navigation, through
implementation of its tool kits, by supporting a ship’s decision making to avoid accidents.
Moreover, e-navigation will allow for provision ships with safety information and
warning of dangerous situations, from shore based stations in a timely and adequate
manner. In addition, due to the digitalized and standardized e-navigation systems with
harmonized collection, integration, exchange, presentation and analysis of marine
information on board and ashore, e-navigation could greatly improve the efficiency of
maritime-related businesses. Thus, IMO is able to simultaneously address safety and
efficiency of navigation, which was generally not possible in the past.
This dissertation has analyzed the 3-step-methodology of the FSA team in order to
evaluate the effects of e-navigation on reducing accidents, and especially estimate the
rate of risk reduction. The FSA team determined the rate of risk reduction through
mainly 3 steps: (1) determining RCOs; (2) analyzing risks; and (3) determining the rate
based on the first and second results. This basic steps have been identified and prepared
for a more comprehensive assessment.
87
A case study of the extended Assessment of potential risk reduction of e-navigation has
been conducted in Chapter 4. For that purpose, vessel accident data for all ships in
Korean water areas and all Korean-flagged ships worldwide during the period 2009 to
2013, based on KMST investigation statistics were analyzed. This analysis was carried
out from several points of view: the categories of SOLAS ships and non-SOLAS ships,
fishing vessels and non-fishing vessels; the categories of navigational accidents,
including collisions and groundings, and others; as well as the direct cause categories of
human error, technical failure and external factors.
Finally, in Chapter 5, the author discussed the effect of SMART-navigation in terms of
to what extent it could reduce vessel accidents. The effects were calculated based on the
same methodology used by the FSA team for the risk and cost-benefit analyses of the
IMO e-navigation SIP, and the rate of risk reduction, 65%, as the coefficient of the
formula that the author proposed in the paragraph 5.1.
Additionally, the author identified the detailed direct causes of accidents based on the
KMST investigation statistics in order to make their scope similar to the IHS Fairplay
database and the Norwegian investigation statistics that the FSA team used. Further, the
author selected six RCOs, including RCO 1, RCO 3, RCO 4, RCO 5, RCO 6 and RCO 7,
which are applicable to non-SOLAS ships, among seven RCOs that the FSA team
identified for SOLAS ships. The selection of RCOs was based on the service scope of
the SMART-navigation plans for non-SOLAS ships.
With regard to the identified detailed direct causes and RCOs above, the author carried
out a spotlight questionnaire survey to experts in order to verify the validity of the
methodology. The questionnaire was responded by 17 in total, whose average
experience in working for the safety of navigation-related field was 14.3 years. Among
them, 76.5% supported the validity of identifying detailed direct causes and 94.1%
88
supported the validity of identifying RCOs.
The most important point from the findings in Chapter 5 is that the Assessment results
show that the situation of maritime safety is different among different countries as the
author assumed in the background.
For example, in the case of the Republic of Korea, 64.1% of non-fishing vessel accidents,
including 37.2% of SOLAS ship accidents and 26.9% of non-SOLAS ship accidents,
involved in navigational accidents. These figures are different from the statistic, 43.2%,
that the FSA team obtained based on IHS Fairplay and the NMA statistics. However, in
the case of calculating all kinds of accidents involving both SOLAS and non-SOLAS
ships, more than 43.5 % involved navigational accidents, including 18.3% for nonfishing vessels and 25.1% for fishing vessels, which is more similar to the statistic,
43.2%, that the FSA team obtained.
In brief, as outcome of this research is shown, the effect of implementing e-navigation,
SMART-navigation is expected to reduce accidents by more than 56.6% the total
accidents, including 13% of SOLAS ships and 43.6% of non-SOLAS ships (including
fishing vessels). In the case of navigational accidents, including collisions and
groundings, more than 33.9 %, including 14.8% for non-fishing vessels and 19.1% for
fishing vessels, are expected to be reduced, while the NMA statistics show 22.8% for
these accidents of SOLAS ships only.
Even the non-navigational accidents are expected to be reduced by up to 22.7%,
including 6.2% for non-fishing vessels and 16.5% for fishing vessels. In terms of the
direct causes, 50.2% of the accidents caused by human error are expected to be reduced,
and 5.4% of the accidents caused by the technical failures and 1% of the accidents
caused by the external factors.
89
With regard to the results above, however, it should be noted that the coefficient acts as
the most important factor in calculating the effect of e-navigation on reducing accidents
according to each detailed direct cause of vessel accidents. The author calculated the
effects in the case study by applying the coefficient, which was quantified by experts
through a somewhat qualitative methodology at a workshop during the FSA for the IMO
e-navigation strategy.
However, as former research pointed out the traditional method to quantify the rate of
risk reduction through estimation by experts, there might be problems related to using
the subjective probability as a calculation of uncertainty in risk analysis (Li et al, 2011).
Therefore, the author concluded that there is an urgent need for further investigation into
the determination of the coefficient and the set of formulas, which is proposed in
paragraph 5.1, as follows:
 To improve the result of this dissertation and make it more meaningful, it is
desirable to quantify the coefficient using a more quantitative methodology and
draft it into the result of this dissertation.
 For this, the quantitative relationship and dependencies between the accident
types and the detailed direct causes should be researched in more detail and
comprehensively.
 Further, the quantitative relationship between the RCOs and their rate of risk
reduction should be researched based on the research results above.
 The research recommended above might be done based on statistical
calculations using actual databases, for example, Bayesian Network (BN) as
mentioned in Chapter 3.
The other point that the author wishes to highlight as a rather general conclusion is the
importance of human error and especially non-SOLAS ships as follows:
90
First, one of the most important aims of e-navigation among others is to prevent human
error. The KSMT statistics show that more than 88.1% among navigational accidents
involving non-fishing vessels and 92.0% of navigational accidents involving fishing
vessels were caused by human error as analyzed in Chapter 4. Both of them are higher
than the 43.2% that the FSA team found based on NMA statistics as shown in Chapter 3.
This might mean that there are possibilities for the Republic of Korea to gain more
benefits by introducing SMART-navigation, by targeting its services to non-SOLAS
ships as well as SOLAS ships.
Second, it should be noted that the accidents caused by combined multiple human errors
might be preventable if one of them had been prevented or corrected in advance and
their chain had been blocked. This is clearly supported by the research conducted by
Wagenaar and Groeneweg (1987). They found that most accidents, 93%, were caused by
a combination of multiple reasons and each of the human errors in an accident acted as
one of the conditions to cause the accident.
This can be interpreted in a way that e-navigation has potential to reduce many more
accidents than the results shown in Chapter 5 because e-navigation aims to increase the
safety of navigation by reducing human error and its strategy was driven based on user
needs. The user needs reflect problems experienced most often that might potentially
cause human error and lead to an accident, during their work on board ships.
Third, the KMST investigation statistics show that more than 83.7% of all accidents
involved non-SOLAS ships including fishing vessels as shown in the Table 35 in
paragraph 5.3.4.2. The statistics show that non-SOLAS vessels are much more
vulnerable to accidents, and it is mainly due to lack of the navigational equipment on
board ships and workforce as explained in Chapter 5. This is clearly supported by
research of An (2011). He emphasized that non-SOLAS ships, including fishing vessels
91
and small non-fishing vessels, are more vulnerable to marine accidents compared to
SOLAS Convention ships, based on the fact that 72.2% of marine accidents involved
small-sized ships of less than 100 G/T and 67% of marine accidents occurred in coastal
waters among total Korea-related accidents during 2005 to 2010.
The fact above might mean that there is potential for SOLAS ships to face accidents due
to such vulnerable non-SOLAS ships because they interface with each other during their
operations nearby coastal waters and in port areas. Therefore, it is more urgent and
significant for non-SOLAS ships apply e-navigation in terms of reducing the
vulnerability to cause accidents as shown in the case of SMART-navigation.
Lastly, human error is related to the human element. Crews consist of individual human
beings living in a modernized society. They have families just like the people who live
and work ashore. In addition, many human errors, even though this dissertation did not
examine that, are caused by fatigue rooted in the work burden.
Therefore, the author would like to emphasize that it is time to change the environment
of maritime sectors. That is, with modern technologies and demands of the stake-holders
of maritime sectors, e-navigation will significantly contribute to reduce human error,
which is the main reason for vessel accidents as experienced by the maritime sectors. In
addition, the author hopes that e-navigation is able to provide crews with welfare such as
the opportunity to enjoy the internet and chatting, and even to quarrel with their husband
or wife ashore while reducing their work burden on board ship.
92
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APPENDIX
 Vessel accident investigation and e-navigation experts survey questionnaire
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