Published at : 10 Jul 2024
Volume : IJtech
Vol 15, No 4 (2024)
DOI : https://doi.org/10.14716/ijtech.v15i4.6384
Franka Hendra | 1 Razak Faculty of Technology and Informatics, Universiti Technology Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia 2 Industrial Engineering, Pamulang Univeristy, Jalan Surya Kencan |
Roslina Mohammad | Razak Faculty of Technology and Informatics, Universiti Technology Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia |
Astuty Amrin | Razak Faculty of Technology and Informatics, Universiti Technology Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia |
Nurazean Maarop | Razak Faculty of Technology and Informatics, Universiti Technology Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia |
Teuku Yuri Zagloel | Departement of Industrial Engineering, Universitas Indonesia, Depok 16424, Indonesia |
Railways are a mode of
public transportation that can carry large numbers of passengers and
commodities and can cover long distances quickly. Based on these advantages,
the railway is a mode of transportation that is in great demand by people as
their choice of transportation. Thus, this will increase the intensity and
frequency of departures, thereby triggering opportunities for errors to occur
that threaten passengers' safety. Currently, the paper needs to present risk
assessment activities in railways comprehensively. This paper will
systematically review the literature on risk management concepts, risk
assessment techniques, standards, and guidelines for risk management in
railways. It also groups the literature to provide directions and
recommendations for distances that future researchers can examine. This study
encompasses a review of 60 publications on risk management, risk assessment,
and risk analysis in railways from reputable and highly indexed journals over
the last ten years. Subsequently, an analysis was conducted on the
characteristics of models, methods, and techniques proposed in railway risk
assessment. Several countries' standards, regulations, and guidelines on
railway safety will also be described. The number of studies examining risk
assessment at level crossings is minimal, whereas most accidents occur in this
area. Many countries have legislation and guidelines but are still general and
do not detail risk assessment activities in areas with a high level of risk.
Guidelines; Risk assessment; Railway; Railways area; Standard; Techniques
Railways are a mode of public transportation that can carry large numbers of passengers and
commodities and can cover long distances in a short time. Thus, this will increase the intensity and
frequency of departures, thereby triggering opportunities for errors to occur
that threaten passengers' safety. Based on these advantages, the railway is a
mode of transportation that is in great demand by people as their choice of
transportation (Berawi
et al., 2015).
Railway accidents worldwide still need attention, even
though railway technology is already relatively high. However, the possibility
of a hazard that could result in the risk of an accident occurring remains an
essential concern for the authorities, the organizing
According to data
from Eurostat Statistics Explained since 2021, the number of train accidents in
the European Union is still relatively high. However, there is a tendency to
decrease, with 840 accidents spread across several countries, as shown in
Figure 1.
Figure 1 Railways accident rate in the European Union
in 2010 -2021
In Indonesia, based on data from the National Transportation Safety
Committee in the period from 2012 to 2021, there were 1,621 cases of train
accidents that occurred in all operational areas and operational divisions. The majority of accidents occurred at level crossings,
accounting for 1,590 cases, followed by 24 incidents involving sleds, and 7
collisions between trains.
This
systematic literature review included a thorough, transparent, and replicable
literature search and analysis process. This method is suitable because the
research objectives require a review of the existing terminology, approaches,
standards and laws, frameworks, and risk assessment techniques related to risk
management in railways. This paper focuses on grouping the literature to
provide directions and recommendations for distances that future researchers
can examine, as shown in Figure 2.
Figure
2 Article Search Process
3.1.
Overview Of Railway
Operational Activity
Most railway operations have a number of the same functions
of carrying local, long-distance, commuter, and freight passengers. It has a
variety of variations in different countries. Railways have two main
components: rolling stock such as locomotives, passenger cars, freight cars,
and others. The second aspect covers infrastructure, including tracks,
stations, shipping facilities, viaducts, tunnels, and other related components.
According to (Kumar, Parida,
and Katiyar, 2013) the
operating system is categorized into the first and second levels.
Assisting in the operation of railways is supported by
intrinsic and extracurricular factors. Intrinsic factors are supporting factors
that originate in the railroad environment, such as signaling, railroad
systems, railroad construction, vehicle types, passenger operations,
transportation operations, locomotive operations, maintenance, and feasibility.
In comparison, extrinsic factors are external supporting factors, such as the physical
geography of the environment, human geography, and historical factors.
3.2. Risk Management In Railway
Railways
are one of the most popular modes of public transportation worldwide, including
in Indonesia, as they can efficiently transport large quantities of passengers
or goods over long distances. According to
(Leitner, 2017), railway accident
scenarios that are included in hazardous events are into five classifications,
namely a) Railway collisions, b) Slipping railways, c) Railroad fires, d)
Intersections, and e) Railway accidents (traffic), which is built by
classifying the underlying cause according to the characteristics of each event
that causes a hazard.
Domin et al. (2016) ran a risk
assessment of railways that support rolling stock components, which may cause
delays and disruptions in transportation service and cause accidents. The
infrastructure supporting railway operations is a factor that is also a
critical doubt. The suggested framework involves several activities, including
hazard hazards identification, risk analysis, appraisal, administration, and
control. After describing the reserved framework, it illustrates how it may be
used systematically to reduce risk on the ranking trajectory (Sukma, Handayani, and Supriyono, 2023; Martani,
Papathanasiou, and Adey, 2016). It raised the
object of a railroad study in Europe that carried passenger numbers and the
number of goods consistent with the range of infrastructure built chiefly
between 1850 and 1950; the risks associated with infrastructure were high. Based
on information from several references, Figure 3 can be illustrated.
Figure 3
The Illustration of Railway Operation Component
In order to
determine whether there are acceptable risk-related stages to infrastructure,
it is necessary to have a process to assess the risks associated with each
object in the railway circuit consistently and consider the consequences of
service provided by the chain if there is an infrastructure failure (Sutalaksana, Zakiyah, and Widyanti, 2019; Martani,
Papathanasiou, and Adey, 2016). According to the
study, at this time, there was an evident lack of a process to assess risks
related to railroad infrastructure and to determine the interventions that
would be implemented to reduce these risks (Lidén, 2015). Most available
processes, methods, and tools provide a basis for budgeting risks associated
with objects or types of objects.
Figure 4 General Process for Risk Management
in the Railway Sector, Adapted from Leitner (2017)
Risk management involves the process of risk identification,
risk assessment, risk evaluation, risk response, and risk monitoring. Risk
identification allows the activities to be identified and the associated risks
to be defined. Risk assessment allows evaluating the likelihood of a risk
occurring together with its probable outcome or consequence. Risk assessment
aims to develop a rational basis for objective decision-making by
systematically using available information to estimate the risks involved (Krivolapova,
2017; Leitner, 2017). With this, the decision-makers forecast the effects of any
risk (Prakash, Soni,
and Rathore, 2017). The effectiveness of risk assessment depends on factors
such as the type of risk involved, the purpose of the analysis, and the
availability of data and resources (Girgin, Necci,
and Krausmann, 2019). Risk Assessment methods can be quantitative, qualitative,
or semi-quantitative. While the quantitative method uses numerical values for
probability and consequence analysis, the quantitative method is based on the
knowledge and judgment of the rater. The risk evaluation phase determines
whether a risk is tolerable, enabling decision-makers to take steps or actions
to control or monitor risks (Khorsandi and
Aven, 2017).
Railway
safety risk assessment is designed to assess risks arising from hazards/events
that may cause death, minor or major injury, and loss of private and public
property (Deivasigamani, de Lacy, and Toward, 2017). In the railroad
industry, risks are primarily related to safety and economic management. In an
ideal rail network, stakeholders collaborate to effectively convey their safety
responsibilities through safety management systems (SMS), reporting systems, safety
standards, common safety methods, techniques, and tools (Hadj-Mabrouk). As
the railroad industry encompasses various stages, including design,
construction, operation, and maintenance, adherence to multiple disciplines and
safety regulations is imperative. Each stage involves risks with distinct
magnitudes and characteristics.
Furthermore,
the real risk is affected by the probabilities and consequences of the
identified events. Considering the variability of the parameters governing
consequence, the range of conditions under consideration can be broad (Alawad, Kaewunruen, and An, 2020). In such an
approach, failures are predicted using various methods, and risks of predicted
failures are quantified, enabling preventive maintenance to be carried out and
prioritized (Dunsford and Chatzimichailidou, 2020).
In
England, there is an external regulator called the Railway Inspectorate (RI),
which carries out a regulatory function that prioritizes persuasion rather than
law enforcement, namely inspecting new infrastructure, conducting public
accident investigations, and reporting in detail on work safety (Zuraida and Abbas, 2020).
Liu et al. (2019) conducted
a study using the mathematical model to analyze risks that affect misfortune in
the five parts of railroad operations, such as in Figure 5. The study found
improvement in methods and tools for analyzing railroad operations risks. This
review model is a good example of analyzing misfortune risk using valid data,
and this data illustrates the proper situation for assessing risk. Generally,
the railway industry is safety-conscious. Hence, a significant aspect of risk
management in railways is directed towards preventing accidents caused by
derailments and system failure or degradation (Liu and Yang, 2023; 2022) argue that, in
addition to various legislative changes in the European rail industry,
technical changes have also created confusion, resulting in increased overall
accident risk. Various approaches to rail risk management have been developed
to address this challenge. A number of these approaches are summarized. From the description above, previous speakers' studies on
risk assessment in various areas of activity on the railway can be summarized
in Table 1.
Table 1 Author/ Year To Be Reference
Author / Year |
Area |
Jin and Junxiang (2019),
Liu et al. (2019), Lagadec et al. (2018), Zhang et al. (2018), Bertrand et al.
(2017), Leitner (2017), Feng et al. (2017), Jiang, Wang, and Xing
(2015) |
Operation |
Zhao et al., (2019), Hewings (2016), Li and Wen (2015), Shi et al. (2015), Lu et al. (2014) |
Signal |
Consilvio et al., (2020), Leitner
(2017) |
Maintenance |
Peng et al.
(2016), Yaghoubpour et al. (2016) |
Human Factor |
Otto et al. (2019), Tong et al. (2014) |
Management |
Lin, Feng, and Sun (2019), Liu et al. (2019) |
Power Source |
Schuitemaker and Bonnema (2019), Otto et
al. (2019), Zhang et
al. (2018), Zhao et al. (2017) |
Infrastructure |
Liang et al., (2018), Nedeliaková, Sekulová, and Nedeliak (2016) |
Level Crossing |
Based on previous research regarding railways risk
assessment in the last ten years in Table 1, most of it was carried out in the
internal areas of railroad operations such as operational areas, signaling,
maintenance, operators, power sources, management, and infrastructure. Risk
assessment on level crossings involves external factors that influence it, such
as highways, neighborhoods, and other vehicles.
3.1.
Railway Risk
Assessment Framework Based On Guidelines, Standards, and Regulations
Several countries or associations issue several standards,
regulations, and laws regarding risk management and railroad safety. Like in
the UK. There is an external regulator called the Railway Inspectorate (RI),
which carries out the regulatory function that prioritizes the way of
persuasion rather than law enforcement, namely checking new infrastructure,
conducting accident investigations in public, and reporting in detail on work
safety.
Figure 5 Safety Standard and Legislation
International Railroad
Figure 6 The Mindset of Increasing Railway Safety in Indonesia (adapted
from: Indonesian Railways)
The National
Economic Research Association (NERA) in London, UK, has established the Safety
Regulations and Standards for European Railways, contributing to enhanced rail
safety, improved risk management, and reduced risk ratings for European Union
railway infrastructure. Across most EU countries, railway infrastructure
management operates independently from railway operations. Under the Ministry
of Civil Works, a separate agency oversees infrastructure financing and
capacity allocation, extending its responsibility across the rail network.
A comprehensive
Railway Safety Management System has been implemented in Indonesia, covering
railway safety, occupational safety, and health. This system is regulated by
the Indonesian Railways Company (Persero) and is based on well-defined safety
policies, objectives, plans, procedures, and responsibilities at all
organizational levels. It follows a systematic approach to policy, planning,
implementation, monitoring, and improvement. Specific policies, such as drug
abuse prevention, align with government regulations. Figure 6 illustrates
Indonesia's progress in railway safety based on government policies. These policies
are conveyed to all workers, guests, contractors, service users, suppliers, and
other stakeholders to understand and implement. These policies are reviewed
annually to ensure adequate and relevant changes.
Creating a
comprehensive safety plan for railway operations involves identifying hazards
and assessing and managing risks associated with operational activities and
human resources. Every unit within the organization is responsible for hazard
identification and risk assessment, following established procedures.
Identified hazards inform risk assessments, categorizing risks as extreme,
high, medium, or low, guiding the development of risk control plans. The safety
directorate is accountable for staying updated on relevant laws and regulations
about railway safety and occupational health and sharing this information
across the organization. Compliance with these regulations is incorporated into
procedures, technical instructions, and work guidelines. Approval holders are
responsible for improving crossing safety and reporting results for inspection.
The regulation addresses safety equipment and infrastructure at level
crossings, detailing authority and responsibility for their implementation and
emphasizing periodic monitoring and corrective actions.
3.1.
Railway Risk Assessment Method And Technique
Many studies have been conducted from the past to the
present that discuss and apply various risk assessment methods (Lyukevich et
al., 2020). Some studies use both quantitative and qualitative methods
to conduct research. Here, the discussion briefly on researchers conducting
risk assessment studies uses the rules. Quoted from European Centre for Disease
Prevention and Control in 2019, who collected several sample papers conducting
risk assessments on several objects suggesting that the method used for risk
assessment by many researchers was to standardize the percentage; Hierarchical
Analysis (AHP) is the most commonly used 26% risk assessment method, followed
by Failure Mode and Impact Analysis (FMEA) 17%, TOPSIS 12% and VIKOR 5% and 14%
of the searched papers using no specific techniques or, in some cases, only
aggregation methods.
Follow the concept of
Reliability, Availability, Maintainability, and safety (RAMS), which is a tool
and methodology that combines reliability, availability, maintenance, and
security techniques in a way that is tailored to the goals of the system (Nugraha,
Silalahi, and Sinisuka, 2016). At railways, the RaMS concept integrates reliability,
availability, maintenance, and safety characteristics following the operational
objectives of the railway. A series of methods is employed in each RAMS
component discipline, including Fault Tree Analysis (FTA), Failure Mode Effect
Critical Analysis (FMECA), etc. (Hendra et al.,
2023; Hidirov and Guler, 2019; Al-Douri, Tretten, and Karim, 2016).
The researchers also predicted the occurrence of accidents
with accident prediction models and language. Abioye et
al. (2020) analyze
the common factors in the existing accident and hazard prediction formulas, and
this formula is used because of its accuracy in predicting the number of
accidents., Singh et al.
(2022), Pasha et al.
(2022),
Singh et al.
(2021), and
Mathew et
al. (2021) uses
a multi-objective mathematical model with an exact and heuristic solution
approach designed to predict accidents and hazards on level crossings, this
model shows the superiority of the exact optimization method because it obtains
Optimal Pareto Front within acceptable computation time, prioritize their studies on level crossings
that consider safety, economy, environment, and community.
Each of the above methods has its advantages and
disadvantages. The advantages and disadvantages of these methods can be seen in
the table 2:
Table 2 Advantages and Disadvantages of Methods
Techniques / Methods |
Advantages |
Disadvantages |
Failure Mode and Effect
Analysis (FMEA) (Boral et al.,
2020; Balaraju, Raj, and Murthy, 2019; Liu, 2016; Mawane and Muyengwa, 2018;
Sarkar and Bhavnani, 2014) |
Quickly
determine the most critical and quantitative and qualitative events. |
Unable to estimate the environmental impact
caused |
Fuzzy Logic ( Wang et al., 2021;
Hadacek et al., 2020; Sarkar and Singh, 2020; Jin and Junxiang, 2019; Andric,
Wang, and Zhong, 2019; Gul and Celik, 2018; Rahmatin
et al., 2018; Martin and Nilawati, 2018; Li, Tong, and Li, 2014) |
Can understand the correlation between
variables and their rational nature. |
It is challenging to determine the
parameters. |
Fault Tree Analysis (FTA)
(Yang, Chen, and
Wang, 2022; Zhang et al., 2020; Dindar, Kaewunruen, and An, 2018;
Dindar et al., 2017; Leitner, 2017; Baig, Ruzli, and Buang, 2013; Jafarian
and Rezvani, 2012) |
Deductive and provide qualitative views
quickly. |
There is no guarantee that early events
have been identified by |
Bow Tie (Huang et al.,
2022; Hughes et al., 2018; Parkinson, Bamford, and Kandola, 2016) |
It can show causal relationships in
high-risk and easy-to-understand scenarios, the relationship between the
causes of events. |
It does not provide a framework for
assessing risk control. |
This research makes a significant contribution to the field
of risk management in railway operations by addressing a notable gap identified
in the existing literature. While previous studies have extensively covered
risk assessments in various aspects of railways, including operations,
signaling, maintenance, human factors, management, resources, and
infrastructure, there has been a noticeable lack of focus on risk assessment at
level crossings. Despite level crossings being the locations with the highest frequency
of accidents, the number of studies specifically examining risk assessment in
this critical area is minimal. The scarcity of research in this specific domain
can be attributed to the absence of specific legislation and detailed
guidelines pertaining to risk management in railway operations. The existing
laws and guidelines, although applicable, are found to be general and lack the
necessary specifics required for conducting comprehensive risk assessments,
especially in high-risk areas such as level crossings. In response to this gap,
the current study recommends the use of the Failure Mode and Effect Analysis
(FMEA) technique as a suitable risk assessment approach for railways. FMEA is
highlighted for its ability to efficiently identify both the most critical
quantitative and qualitative events, providing a valuable tool for enhancing
risk management strategies in railway operations. However, it is crucial to
acknowledge the limitations within this study, which may pose challenges for
future researchers. These limitations include the need for further exploration
of additional risk assessment techniques to enhance effectiveness and a more
in-depth examination of critical areas posing risks to railways. Therefore,
this research not only identifies an existing gap but also offers a practical
recommendation for addressing it, thus contributing to the advancement of risk
management practices in the railway industry.
The Universiti Teknologi Malaysia funded the project (UTM) Fundamental
Research Grant with UTM Vote No: Q.K130000.3856.22H17, the Ministry of Higher
Education (MOHE) under the Fundamental Research Grant Scheme (FRGS) (grant
number: FRGS/1/2019/TK03/UTM/02/14 (R.K130000.7856.5F205)), Razak Faculty of
Technology and Informatics (UTM), Universiti Teknologi Malaysia (UTM).
Filename | Description |
---|---|
R1-IE-6384-20230710222114.pdf | Revision response |
Abioye, O.F., Dulebenets,
M.A., Pasha, J., Kavoosi, M., Moses, R., Sobanjo, J., Ozguven, E.E., 2020.
Accident and Hazard Prediction Models for Highway–Rail Grade Crossings: A
State-Of-The-Practice Review for the USA. Railway Engineering Science,
Volume 28, 251–274
Alawad, H., Kaewunruen,
S., An, M., 2020. A Deep Learning Approach Towards Railway Safety Risk
Assessment. IEEE Access, Volume 8, pp. 102811–102832
Al-Douri, Y.K., Tretten,
P., Karim, R., 2016. Improvement of Railway Performance: a Study of Swedish
Railway Infrastructure. Journal of Modern Transportation, Volume 24, pp.
22–37
Andric, J.M., Wang, J.,
Zhong, R., 2019. Identifying The Critical Risks in Railway Projects Based on
Fuzzy And Sensitivity Analysis: A Case Study Of Belt And Road Projects. Sustainability,
Volume 11(5), p. 1302
Baig, A.A., Ruzli, R.,
Buang, A.B., 2013. Reliability Analysis Using Fault Tree Analysis: A Review. International
Journal of Chemical Engineering and Applications, Volume 4(3), p. 169
Balaraju, J., Raj, M.G.,
Murthy, C.S., 2019. Fuzzy-FMEA Risk Evaluation Approach for LHD Machine–A Case
Study. Journal of Sustainable Mining, Volume 18(4), pp. 257–268
Berawi, M.A., Berawi,
A.R.B., Prajitno, I.S., Nahry, Miraj, P., Abdurachman, Y., Tobing, E., Ivan,
A., 2015. Developing Conceptual Design of High Speed Railways using Value
Engineering Method: Creating Optimum Project Benefits. International Journal
of Technology, Volume 6(4), pp. 670–679
Bertrand, S., Raballand,
N., Viguier, F., Muller, F., 2017. Ground Risk Assessment for Long-Range
Inspection Missions of Railways by UAVs. In: International Conference on
Unmanned Aircraft Systems (ICUAS), pp. 1343–1351
Boral, S., Howard, I.,
Chaturvedi, S.K., McKee, K., Naikan, V.N.A., 2020. An Integrated Approach for
Fuzzy Failure Modes and Effects Analysis Using Fuzzy AHP and Fuzzy MAIRCA. Engineering
Failure Analysis, Volume 108, p. 104195
Consilvio, A.,
Solís-Hernández, J., Jiménez-Redondo, N., Sanetti, P., Papa, F.,
Mingolarra-Garaizar, I., 2020. On Applying Machine Learning and Simulative
Approaches to Railway Asset Management: The Earthworks and Track Circuits Case
Studies. Sustainability, Volume 12(6), p. 2544
Deivasigamani, A., de
Lacy, A., Toward, M., 2017. An Overview of Structure-Radiated Noise And
Vibration Assessment For Elevated Rail Infrastructure. In: Proceedings
of ACOUSTICS 2017, p. 814
Dindar, S., Kaewunruen,
S., An, M., 2018. Identification of Appropriate Risk Analysis Techniques for
Railway Turnout Systems. Journal of Risk Research, Volume 21(8), pp.
974–995
Dindar, S., Kaewunruen,
S., An, M., Gigante-Barrera, Á., 2017. Derailment-Based Fault Tree Analysis on
Risk Management of Railway Turnout Systems. In: IOP Conference Series:
Materials Science and Engineering, Volume 245(4), p. 042020
Domin, R., Domin, I.,
Cherniak, G., Mostovych, A., Konstantidi, V., Gryndei, P., 2016. Investigation
Of the Some Problems of Running Safety of Rolling Stock on The Ukrainian
Railways. Archives of Transport, Volume 40(4), pp. 15–27
Dunsford, R.,
Chatzimichailidou, M., 2020. Introducing a System Theoretic Framework for
Safety In The Rail Sector: Supplementing CSM-RA with STPA. Paper Presented
at the Safety and Reliability, Volume 39(1), pp. 59–82
Feng, D., He, Z., Lin, S.,
Wang, Z., Sun, X., 2017. Risk Index System for Catenary Lines Of High-Speed
Railway Considering The Characteristics Of Time–Space Differences. IEEE
Transactions on Transportation Electrification, Volume 3(3), pp. 739–749
Girgin, S., Necci, A.,
Krausmann, E., 2019. Dealing With Cascading Multi-Hazard Risks In National Risk
Assessment: The Case Of Natech Accidents. International Journal of Disaster
Risk Reduction, Volume 35, p. 101072
Gul, M., Celik, E., 2018.
Fuzzy Rule-Based Fine–Kinney Risk Assessment Approach For Rail Transportation
Systems. Human and Ecological Risk Assessment: An International Journal,
Volume 24(7), pp. 1786–1812
Hadacek, L., Sivakova, L.,
Soušek, R., Zeegers, M., 2020. Assessment Of Security Risks In Railway
Transport Using The Fuzzy Logical Deduction Method. Komunikácie:
Communications (Scientific Letters of the University of Žilina), Volume
22(2), pp. 79–87
Hewings, D., 2016.
Application of Wide-Area Protection to Running-In Risk in Railway Protection
Systems. In: 13th International Conference on Development in
Power System Protection 2016 (DPSP), p.
0072
Huang, Y., Zhang, Z., Tao,
Y., Hu, H., 2022. Quantitative Risk Assessment of Railway Intrusions with Text
Mining and Fuzzy Rule-Based Bowtie Model. Advanced Engineering Informatics, Volume
54, p. 101726
Hughes, P., Shipp, D.,
Figueres-Esteban, M., Van-Gulijk, C., 2018. From Free-Text To Structured Safety
Management: Introduction Of A Semi-Automated Classification Method Of Railway
Hazard Reports to Elements On A Bowtie Diagram. Safety Science, Volume
110, pp. 11–19
Jafarian, E., Rezvani, M.,
2012. Application Of Fuzzy Fault Tree Analysis for Evaluation of Railway Safety
Risks: An Evaluation of Root Causes for Passenger Train Derailment. In:
Proceedings of the Institution of Mechanical Engineers, Volume 226(1), pp.
14–25
Jiang, P., Wang, D., Xing,
Y., 2015. Risk Analysis of General Accidents in China Railway Passenger
Transportation. In: 2015 Seventh International Conference on Measuring
Technology and Mechatronics Automation, pp. 950–953
Jin, Z., Junxiang, X.,
2019. Countermeasure Research on Sichuan-Tibet Railway Construction Based on
Safety Risk Assessment. In: the 2019 4th International
Conference on Intelligent Transportation Engineering (ICITE), pp. 54–58
Khorsandi, J., Aven, T.,
2017. Incorporating Assumption Deviation Risk In Quantitative Risk Assessments:
A Semi-Quantitative Approach. Reliability Engineering & System Safety,
Volume 163, pp. 22–32
Krivolapova, O., 2017.
Algorithm For Risk Assessment in The Introduction of Intelligent Transport
Systems Facilities. Transportation Research Procedia, Volume 20, pp.
373–377
Kumar, K., Parida, M.,
Katiyar, V., 2013. Short Term Traffic Flow Prediction for A Non Urban Highway
Using Artificial Neural Network. Procedia-Social and Behavioral Sciences,
Volume 104(2), pp. 755–764
Lagadec, L.-R., Moulin,
L., Braud, I., Chazelle, B., Breil, P., 2018. A Surface Runoff Mapping Method
for Optimizing Risk Assessment on Railways. Safety Science, Volume 110,
pp. 253–267
Leitner, B., 2017. A
General Model for Railway Systems Risk Assessment with The Use Of Railway
Accident Scenarios Analysis. Procedia Engineering, Volume 187, pp.
150–159
Li, M., Wen, Y., 2015.
Applying Risk Assessment Technique to Electromagnetic Compatibility Analysis in
Chinese High Speed Railway. In: the 2015 IEEE 6th International
Symposium on Microwave, Antenna, Propagation, and EMC Technologies (MAPE), pp.
441–445
Li, Y., Tong, S., Li, T.,
2014. Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain
Nonlinear Strict-Feedback Systems with Input Saturation. IEEE Transactions
on Cybernetics, Volume 45(10), pp. 2299–2308
Liang, C., Ghazel, M.,
Cazier, O., El-Koursi, E.-M., 2018. Analyzing Risky Behavior Of Motorists
During The Closure Cycle Of Railway Level Crossings. Safety Science,
Volume 110, pp. 115–126
Lidén, T., 2015. Railway
Infrastructure Maintenance-A Survey of Planning Problems and Conducted
Research. Transportation Research Procedia, Volume 10, pp. 574–583
Lin, S., Feng, D., Sun,
X., 2019. Traction Power-Supply System Risk Assessment for High-Speed Railways
Considering Train Timetable Effects. IEEE Transactions on Reliability,
Volume 68(3), pp. 810–818
Liu, C., Yang, S., 2022.
Using Text Mining to Establish Knowledge Graph From Accident/Incident Reports
In Risk Assessment. Expert Systems with Applications, Volume 207, p.
117991
Liu, C., Yang, S., 2023. A
Text Mining-Based Approach for Understanding Chinese Railway Incidents Caused
By Electromagnetic Interference. Engineering Applications of Artificial
Intelligence, Volume 117, p. 105598
Liu, H.-C., 2016. FMEA
Using Uncertainty Theories and MCDM Methods. Singapore: Springer, pp. 13–27
Liu, J., Schmid, F.,
Zheng, W., Zhu, J., 2019. Understanding Railway Operational Accidents Using
Network Theory. Reliability Engineering & System Safety, Volume 189,
pp. 218–231
Lu, Y., Peng, Z., Miller,
A., Zhao, T., Johnson, C., 2014. Timed Fault Tree Models of The China Yongwen
Railway Accident. In: The 2014 8th Asia Modelling Symposium,
pp. 128–133
Lyukevich, I., Agranov,
A., Lvova, N., Guzikova, L., 2020. Digital Experience: How to Find a Tool for
Evaluating Business Economic Risk. International Journal of Technology,
Volume 11(6), pp. 1244–1254
Martani, C.,
Papathanasiou, N., Adey, B.T., 2016. A Review of The State-Of-The-Art In
Railway Risk Management. In: The 1st Asian Conference on
Railway Infrastructure and Transport, pp. 9–17
Martin, M., Nilawati, L.,
2018. Model Fuzzy Mamdani Untuk Penilaian Tingkat Kepuasan Pelayanan Pengaduan
Masyarakat (Fuzzy Mamdani Model for Assessing the Level of Satisfaction with
Public Complaint Services). Jurnal Informatika, Volume 5(2), pp. 237–247
Mathew, J., Benekohal,
R.F., Berndt, M., Beckett, J., McKerrow, J., 2021. Multi-Criteria
Prioritization of Highway-Rail Grade Crossings for Improvements: A Case Study. Urban,
Planning and Transport Research, Volume 9(1), pp. 479–518
Mawane, Y.N., Muyengwa,
G., 2018. Evaluating The Impact of TPM In a Railway and Mining Component
Manufacturing Company. In: Proceedings of the International Conference
on Industrial Engineering and Operations Management Pretoria/Johannesburg,
South Africa, pp. 1–10
Nedeliaková, E., Sekulová,
J., Nedeliak, I., 2016. A New Approach to The Identification of Rail Risk At
Level Crossing. Procedia Engineering, Volume 134, pp. 40–47
Nugraha, H., Silalahi,
Z.O., Sinisuka, N.I., 2016. Maintenance Decision Models for Java–Bali 150-kV
Power Transmission Submarine Cable Using RAMS. IEEE Power and Energy
Technology Systems Journal, Volume 3(1), pp. 24–31
Otto, A., Kellermann, P.,
Thieken, A.H., Costa, M.M., Carmona, M., Bubeck, P., 2019. Risk Reduction
Partnerships in Railway Transport Infrastructure in an Alpine Environment. International
Journal of Disaster Risk Reduction, Volume 33, pp. 385–397
Papathanasiou, N., Adey,
B.T., Martani, C., 2016. Risk Assessment Process for Railway Networks With
Focus On Infrastructure Objects. In: The 1st Asian Conference on Railway
Infrastructure and Transportation (ART 2016), pp. 22–29
Parkinson, H.J., Bamford,
G., Kandola, B., 2016. The Development of An Enhanced Bowtie Railway Safety
Assessment Tool Using A Big Data Analytics Approach. In: The
International Conference on Railway Engineering (ICRE) 2016, pp. 1–9
Pasha, J., Dulebenets,
M.A., Singh, P., Moses, R., Sobanjo, J., Ozguven, E.E., 2022. Safety And Delays
at Level Crossings in The United States: Addressing the Need For
Multi-Objective Resource Allocation. Sustainable Rail Transport 4: Innovate
Rail Research and Education, Volume 2022, pp. 65–94
Peng, Z., Lu, Y., Miller,
A., Johnson, C., Zhao, T., 2016. Risk Assessment of Railway Transportation
Systems Using Timed Fault Trees. Quality and Reliability Engineering
International, Volume 32(1), pp. 181–194
Prakash, S., Soni, G.,
Rathore, A.P.S., 2017. A Critical Analysis of Supply Chain Risk Management
Content: A Structured Literature Review. Journal of Advances in Management
Research, Volume 14(1), pp. 69–90
Rahmatin, N., Santoso, I.,
Indriani, C., Rahayu, S., Widyaningtyas, S., 2018. Integration of the Fuzzy
Failure Mode and Effect Analysis (Fuzzy FMEA) and the Analytical Network
Process (ANP) in Marketing Risk Analysis and Mitigation. International
Journal of Technology, Volume 9(4), pp. 809–818
Sarkar, D., Bhavnani, G.,
2014. Risk Analysis of Elevated Corridor Project Using Failure Mode and Effect
Analysis (FMEA) and Combined Fuzzy FMEA. Journal of Construction Management,
Volume 29(2), pp. 5–22
Sarkar, D., Singh, M.,
2020. Risk Analysis By Integrated Fuzzy Expected Value Method And Fuzzy Failure
Mode And Effect Analysis For An Elevated Metro Rail Project Of Ahmedabad,
India. International Journal of Construction Management, Volume 22(10),
pp. 1–12
Sasidharan, M., Burrow, M.P.N., Ghataora, G.S.,
Torbaghan, M.E., 2017. A Review of Risk Management Applications For Railways. In:
14th International Conference of Railway Engineering-2017, pp. 1–11
Schuitemaker, K., Bonnema,
G.M., 2019. Modelling Integral Risk Assessment (MOIRA): Experiments on the
Dutch Railway Departure Process. In: The 2019 14th Annual Conference
System of Systems Engineering (SoSE), pp. 272–277
Shi, L., Ning, N., Zheng,
W., Wu, D., 2015. Quantitative Risk Assessment Method for the On-Board ATP of
High-Speed Railway. In: 2015 International Conference on Transportation
Information and Safety (ICTIS), pp. 764–768
Singh, P., Pasha, J.,
Khorram-Manesh, A., Goniewicz, K., Roshani, A., Dulebenets, M.A., 2021. A
Holistic Analysis of Train-Vehicle Accidents at Highway-Rail Grade Crossings in
Florida. Sustainability, Volume 13(16), p. 8842
Singh, P., Pasha, J.,
Moses, R., Sobanjo, J., Ozguven, E.E., Dulebenets, M.A., 2022. Development of
Exact and Heuristic Optimization Methods for Safety Improvement Projects at
Level Crossings Under Conflicting Objectives. Reliability Engineering &
System Safety, Volume 220, p. 108296
Sukma, F.H., Handayani,
E.T., Supriyono, S., 2023. Technological Capabilities Assessment By Using
Technometrics Models In Routine Maintenance Of Commuter Trains To Increase
Service Performance. Sinergi, Volume 27(1), pp. 57–64
Sutalaksana, I.Z.,
Zakiyah, S.Z.Z., Widyanti, A., 2019. Linking Basic Human Values, Risk
Perception, Risk Behavior and Accident Rates: The Road To Occupational Safety. Industrial
Engineering, Volume 10(5), pp. 918–929
Tong, B., Dou, F., Feng,
Y., Long, Z., 2014. Research On Risk Analysis of Suspension System in Maglev
Train Based on Fuzzy Multiple Attribute Decision-Making. In: The
Proceeding of the 11th World Congress on Intelligent Control and
Automation, pp. 751–754
Wang, Z., Shangguan, W.,
Peng, C., Song, H., 2021. Double-Layer Fuzzy enhanced Failure Mode and Effects
Analysis Method for Automatic Train Operation System. In: 2021 Global
Reliability and Prognostics and Health Management (PHM-Nanjing), pp. 1–7
Yaghubpour, Z., Esmaeily,
L., Piran, H.R., Behrad, A., 2016. Public Transport Risk Assessment through
Fault Tree Analysis (FTA) Case Study: Tehran Municipal District. Bulletin de
la Société Royale des Sciences de Liège, Volume 85, pp. 1039–1048
Yang, Y., Chen, G., Wang,
D., 2022. A Security Risk Assessment Method Based on Improved FTA-IAHP for
Train Position System. Electronics, Volume 11(18), p. 2863
Zhang, H., Yuan, M.,
Liang, Y., Wang, B., Zhang, W., Zheng, J., 2018. A Risk Assessment Based
Optimization Method for Route Selection of Hazardous Liquid Railway Network. Safety
Science, Volume 110, pp. 217–229
Zhang, Q., Zhuang, Y.,
Wei, Y., Jiang, H., Yang, H., 2020. Railway Safety Risk Assessment and Control
Optimization Method Based on FTA-FPN: A Case Study of Chinese High-Speed
Railway Station. Journal of Advanced Transportation, Volume 2020,
p. 3158468
Zhao, T., Liu, X. M., Ma,
Z. Y., Song, G., Liu, Y.Q., 2019. Safety Assessment of Railway Vehicle Antenna
Communication Management. Procedia Computer Science, Volume 154, pp.
531–536
Zhao, W., Martin, U., Cui,
Y., Liang, J., 2017. Operational Risk Analysis of Block Sections in The Railway
Network. Journal of Rail Transport Planning & Management, Volume
7(4), pp. 245–262
Zuraida, R., Abbas, B.S.,
2020. The Factors Influencing Fatigue Related to the Accident of Intercity Bus
Drivers in Indonesia. International Journal of Technology, Volume 11(2),
pp. 342–352