Railway Incidents Research Articles

The impact of railway incidents on train delays: A case of the Swedish Railway Network

A foreseeable challenge with a substantial increase in railway mode share will be how to uphold punctuality. Higher volumes of train traffic will result in timetables that are more sensitive to disruptions; whose severity and frequency is also expected to increase in light of greater asset utilization and climate change. This calls for a definitive understanding of the relationship between incidents and train delays as a prerequisite to developing robust timetables and disruption management strategies. In this paper we propose a novel framework for quantifying the impact of railway incidents on train delays. Using a case of the Swedish Railway Network, we compare the impact of different incidents on train delays. The impact of delay is defined as a factor of the incident rate, exposure rate, delay rate and historical average delay minutes per incident. A logistic model that estimates the probability of delay for any train, in the event of a failure, is also developed. Snow on track was established as most critical, resulting in the highest normalized delay minutes per train and the largest increase in the odds of delay for individual trains. The proposed framework & approach can be applied to other networks.

A RETROSPECTIVE STUDY OF RAILWAY FATALITIES BROUGHT FOR AUTOPSY AT JORHAT MEDICAL COLLEGE AND HOSPITAL, JORHAT, ASSAM

Background: Understanding the patterns of injuries sustained during railway accidents is crucial for developing effective preventive measures and improving safety protocols. A retrospective analysis was performed on a comprehensive database of medico-legal autopsy reports from railway accident cases brought for medico-legal autopsy spanning a period of three years. Materials & Methods: The study included victims of all age groups and demographics to ensure the diversity of injury patterns is adequately represented. Blunt trauma, lacerations, fractures, and organ damage were common. Results: In this study, railway incidents accounted for 2.2% of total deaths, with 78.3% of victims identified and 21.7% unidentified. Most victims were male (82.6%), aged 41-50, and incidents occurred mainly in summer, during August, and between 12 am and 8 am. Grease stains were found in 76.1% of cases, and most injuries included crush injuries (76.1%) followed by fractures and lacerations. The bodies of 60.9% victims were found in intact condition were as in 28.3% of the cases complete separation of the body parts were seen. Instantaneous death occurred in 50% of cases, while hemorrhage and shock was the second most common cause of death.

Human reliability and Organizational factors—How do Human Factors contribute to Signals Passed at Danger?

The majority of railway incidents happen due to human error. Historically, human error has been split into active and latent errors, both to be investigated. Active errors are linked to a specific individual, while latent errors tend to be associated with procedures and higher levels of automation and safety barriers. Active errors are analysed with Survival Analysis, fitting several functions and the Cox Proportional Hazards model. This used a train driver database and Signal Passed at Danger (SPAD) information. A translated surveying tool is used to study latent errors and organizational factors. After translation, this tool was validated with Confirmatory Factor Analysis. Results suggest that active errors, in the form of SPADs are influenced by factors as age, experience, average length of certified itineraries and previous SPADs. The mean time between failure for a train driver in such incident is between 1000 and 1200 days. At an organizational level, Job Satisfaction is related with experience, while General and Safety Culture is related with age, position, and employer. Occupational Stress seems to be independent of the factors presented as well as the geographical location. Findings of this study identify both personal and organizational factors of the occurrence of SPADs, improving ability for better resource allocation (in the case of training or train driver allocation) or implement risk control measures (for example stricter scheduling rules).

A machine learning and data analytics approach for predicting evacuation and identifying contributing factors during hazardous materials incidents on railways

An emergency evacuation order might be issued in response to a railway incident involving hazardous materials (hazmat), such as the February 2023 derailment at Palestine, Ohio. Due to the potential complexity of railway incidents involving hazmat, making an accurate and timely decision regarding evacuation orders can be very challenging. An appropriate framework is required to predict the need for evacuation after railway incidents and identify the contributing factors. This study aims to develop such a framework by incorporating machine learning techniques. First, various supervised machine learning models are implemented to analyze the effect of different factors on the prediction of evacuation immediately after railway incidents. Based on the factors considered in this study, the most accurate model is identified for predicting evacuation. This model is also used to identify the most significant factors affecting evacuation. The rules leading to the evacuation are then recognized along with the underlying causes of the evacuation. Second, natural language processing and co-occurrence network analysis are employed to analyze brief descriptions of railway incidents that resulted in the need to evacuate. This allows us to construct a network of causes and contributing factors to the evacuations and demonstrate a causal relationship between them. This study provides prediction models and conclusions that can be used to reduce the risks associated with the railway transportation of hazmat and enhance the effectiveness of safety intervention measures.

A text mining-based approach for understanding Chinese railway incidents caused by electromagnetic interference

The high-speed railway is a deeply coupled system with strong and weak electrical equipment, while complex electromagnetic interference (EMI) consequently brings potential risks and hazards to signaling safety. Since the incident reports on signaling failure intrinsically reflect the generation and evolution mechanism of equipment failures, relying on text mining technology, this paper tries to extract failure-related entities and constructs a knowledge graph to clarify the negative impact of the on-site electromagnetic environment. Firstly, based on convolutional neural networks (CNN), a supervised deep learning model for Chinese text classification is established to generate a corpus containing only railway failures caused by EMI. Then, the bidirectional long short-term memory (BiLSTM) and bidirectional encoder representations from transformers (BERT) algorithms are adopted to build the named entity recognition (NER) model. A NER algorithm more suitable for Chinese text features is proposed through ensemble modeling, training verification, and comparative evaluation. Finally, the knowledge storage and visualization of relational graph construction based on the Neo4j database are realized according to the obtained failure-related entities. This knowledge topology network effectively explores the inherent relationship between EMI factors and railway safety, as well as provides support for improving the safety assessment and enhancing the anti-interference performance of the equipment.

Human vulnerability modeling and risk analysis of railway transportation of hazardous materials

People who live in densely populated regions could be at risk of mishaps that occur during hazardous materials (hazmat) transportation. Population vulnerability assessment is an essential parameter for developing risk mitigation strategies to prevent negative consequences of hazmat transportation incidents. In this study, a procedure is developed to estimate the risk of hazmat railway incidents, focused on two parts. First, the most probable and the most dangerous meteorological variables (e.g., stability class, wind speed, solar radiation, etc.) are processed to simulate threat zones and prepare hazard maps using the ALOHA software. Second, sociodemographic characteristics (e.g., age, sex, education, household, income, employment, etc.) of the affected population are used to create vulnerability maps along with their weights. As risk is a function of hazard and vulnerability, risk maps are generated by superimposing the hazard and vulnerability maps using ArcGIS software. This procedure is tested in a city in Canada and confirms the significance of integrating population vulnerability in risk assessment by revealing that the areas with high hazards indicated on the hazard maps are not necessarily considered as the areas with high risk indicated on the risk maps. The risk maps generated in this study can be used to provide recommendations to improve land-use planning, enhance the safety of the people, living in higher-risk areas, and prioritize emergency response decisions. The procedure developed in this study can also be applied to different types of railway incidents and other potential incidents in the transportation industry when all the necessary information is available, such as regional meteorological conditions and the characteristics of the affected population.

"An Approach Based on Time-Series and Neural Networks for Safety Railway Incident Prediction"

"An Approach Based on Time-Series and Neural Networks for Safety Railway Incident Prediction"

중동철도 사건과 중소 갈등

이 논문은 중동철도 사건을 중심으로 중국과 소련의 갈등 상황을 분석하였다. 중동철도는 19세기 말 제정러시아가 시베리아철도의 연장으로 중국영토에 부설한 제국주의 시대의 산물이었다. 처음 명칭은 동청철도였으나, 1924년 중동철도로 이름이 바뀌었다. 1896년 청조의 전권대표로 니톨라이 2세의 대관식에 참가했던 리홍장(李鴻章)과 제정러시아의 제무대신 비떼(С. Ю. Витте)가 상호호조조약을 체결하고 이에 따라 러시아가 동청철도부설권을 획득하였다.<BR> 신생 소비에트 정권은 1919년 ｢제1차 카라한 선언｣(제1차 대중국선언)을 발표하여 제정 러시아가 중국과 맺은 모든 비밀조약을 폐지하고 중동철도를 포함한 중국에서의 모든 이권을 포기한다고 선언하였다. 그러나 1920년의 제2차 대중국선언에서는 동청철도의 부분을 삭제하고 별도의 협정을 통해 중동철도문제를 해결하겠다고 하였다.<BR> 당시 중국에서는 열강으로부터 이권을 회수해야 한다는 움직임이 일어나고 있었다. 이에 따라 중국정부도 철도를 회수하여 철도에 대한 권리를 일원화해야 한다는 뜻을 표명하였다. 1924년 베이징정부는 잠정적으로 중소 양국이 철도를 공동으로 운영하기로 하였으며, 추후 세부적인 논의를 하기로 하였다. 그러나 논의가 진행되지 못하면서 소련은 중동철도에 관한 장기적인 권리를 가지게 되었다. 소련은 같은 해 9월 중동철도가 운행되는 중국 동북지역 지방정권과도 조약을 체결하여 철도에 대한 실질적인 경영권과 만주지역에서의 영향력을 확보하였다.<BR> 중동철도문제는 소련과의 협상이 필요한 외교문제였으나 중동철도와 그 부속지 운영의 문제는 동북지역 내치와도 관련이 있는 복잡한 현안이었다. 중동철도 사건이 발발하자 소련은 중국에 국교단절을 선언하였고, 중국 중앙정부와의 교섭대신 동북지방정부와 문제를 해결하려고 하였다. 또한 무력대응으로 통해 중국을 압박하였다. 중앙정부의 군사지원이 따르지 않는 가운데 장쉐량의 동북군은 소련에 패하였고, 결국 소련의 요구에 따라 하바롭스크의정서를 체결하였다. 그리고 중동철도는 이전처럼 소련이 주도적으로 운영하는 시스템이 유지되었다.<BR> 소련은 정권 수립 후, 여전히 중앙과 지방 세력이 통합되지 않고 불안정한 정치상황을 보이고 있던 중국에서 제정러시아가 가졌던 중동철도의 철도권리를 계승하였다. 당시 중국의 중앙과 지방정부와 각각 철도관련 협정을 체결하여 자신들의 이권을 확실히 하였다. 그 후 난징정부가 전국을 통일한 후에도 중앙과 지방의 이원화된 시스템이 유지되는 중국 측이 일으킨 중동철도사건에 대해서도 물론 사건을 일으킨 당사자가 장쉐량의 지방정권이기는 했지만, 외교 교섭권을 가진 중앙정부가 아닌 지방정권을 교섭대상으로 삼아 철도를 통한 동아시아의 이권을 확실히 하였다.<BR> 중동철도 사건은 철도를 통해 동아시아의 세력범위를 뒷받침하려는 소련의 구상이 지속되는 가운데 발생한 사건이었다. 이 사건은 크게는 중소 양국의 갈등이었으나, 여기에서 말하는 중국은 각각 다른 시간 속에 중국을 대표하는 두 개의 정부, 그리고 이 두 정부와 같은 시각 속에 있었던 하나의 지방정부를 지칭한다. 따라서 사건은 각기 다른 시간 속에서 중앙과 지방의 통합에 모순을 보인 중국의 상황, 그리고 새롭게 중국을 대표하는 정권으로 인정 받기 위해 국제적 협조를 이끌어 내려고 했던 난징정부의 계산법도 사건처리에 주요하게 작용했음을 알 수 있다.

An estimation framework to quantify railway disruption parameters

Railway network operations form complex systems. Any disruption adversely impacts the operations, causing long delays. Many studies investigate the effect of a railway incident; however, a holistic quantification is lacking. This study aims to present an estimation framework for flexible traffic management systems, which can help reduce network delays and enable dispatchers to make better-informed decisions. An incident's impact on the network is estimated by creating a sequence of models, which predict two key variables. Firstly, the incident duration is predicted, which is used to predict the second variable: total delay caused by the incident. Various influencing attributes are examined, such as weather, network and railway-related attributes. Their relationship with the response variables is studied in order to understand the incident's impact. Using incident data from the Danish Railways, machine learning models are estimated. The results show that neural networks outperform other competing models for total delay modelling, resulting in improved prediction by the estimation framework, thus giving higher accuracy than the stand-alone models in the study.

Evaluation of the Implementation of a Railway Critical Incident Management and Support Protocol to Help Train Drivers Cope With Accidents and Suicides.

Railway accidents and suicides can have severe psychological consequences for train drivers. This study evaluates the implementation of railway critical incident management and support protocols (CIMSP) by employers. It also identifies environmental factors, characteristics of critical incidents, and types of work relations affecting implementation. A longitudinal study was conducted with 74 train drivers. Participants were interviewed 1 week, 1, 3, and 6 months after a critical incident. Correlational analyses were performed to identify factors associated with implementation and satisfaction. CIMSP are generally partially applied by employers when a railway incident occurs. Workers' satisfaction toward implementation of the protocol is moderate. Obstacles to implementation are: geographic isolation, severity of the incident, and poor quality of work relations. These obstacles should be addressed in CIMSP design and implementation strategies.

COGNITIVE FUNCTIONING AND SAFETY DETERMINANTS IN THE WORK OF A TRAIN DRIVERS

The reports of committees investigating the causes of rail accidents indicate the significance of the so-called human factor (e.g. UTK, 2019). In addition to issues related to perso nality functioning, the organization and culture of work, this also includes variables related to the cognitive functioning of train drivers themselves. These are significant factors that determine the occurrence of accidents that result from ignoring or not spotting railway signals and signs. The purpose of this study was to verify the relationship between cognitive functioning and safety determinants, which was measured using an eye-tracking technique. The application of this technique was intended to check its usefulness in the field of railway traffic safety and to achieve an approximate simulation environment of the real working conditions of a train driver. In the present study, the Vienna Test System was used as a me - thod for the determination of cognitive functioning. Based on the variables described in the subject literature, the following tests were applied: Determination Test, Visual Memory Test, Visual Pursuit Test, Reaction Time, Cognitrone, Signal Detection and Vigilance. In addition to computer cognitive tests, an eye-tracking test method was designed based on a film recorded in real train-driving situation. Measures describing areas of interest (AOI) that are crucial for safety were analysed. Due to the pilot nature of the research, only 10 passenger train drivers participated in the study. The results of the study showed a link between the cognitive functioning of the train drivers and visual security determinants. Significant correlations were found with stress tolerance resulting from cognitive overload, visual memory, alertness and concentration ability under time pressure. The study confirmed the significant role of the train driver's cogni- tive functioning in the analysis and perception of safety-critical signals. The use of an eye-tracking method has delivered results that are in agreement with studies based on other methods. This pro- vides a sound basis for the continuation of research using eye- tracking in the assessment of rail transport safety. In the future, the research should be extended to include an analysis of the effect of demographic and situational variables (types of signalling devices and signage) and a broader model of the relationship between cog- nitive functioning and the driver's visual attention. This will provide data that is crucial for the prevention of railway incidents and the development of training plans for train drivers.

Istraživanje mehanizama loma železničkih osovina

The paper gives a systematic overview of literature sources who consider impacts critical damage of mechanical, corrosive and thermal nature which may occur on railway axles during operation and which may be the causes of their fracture. The results of the research of the mechanisms that cause cracks, crack propagation and final fracture of the railway vehicle axle, such as material fatigue and the appearance of localized notches caused by paint (coating) separation, damage from ballast impact and pitting corrosion are presented. The influence of high temperatures and overheating on the axles was analyzed and an excerpt from the research published in one research report was given. Some significant suggestions for optimizing the design of the axles are highlighted which would take into account the analysis of time-varying axle stresses, stress spectrum in operation, axle tolerance to damage and the existence of residual surface stresses. The reliefs of the fracture surfaces of the axle after the railway incidents and the derailment of the rail vehicle from the rails are presented and explained.

Network topological approach to modeling accident causations and characteristics: Analysis of railway incidents in Japan

Railway networks are a critical infrastructure in today's society, and many efforts have been made to promote their safety. Even when safety measures are introduced, railway incidents still occur. Incident investigation can acquire facts about the causation factors and effects of incidents. In this study, we propose a network analytical framework to identify the factors and effects of railway incidents. This framework captures the complexity of interdependencies and delineates the causation of railway incidents in incident chains; the incident chains are then remodeled to study the topological characteristics of factors and effects in a network model. Reported railway incident cases in Japan are selected for analysis from three perspectives: local view analysis, global view analysis, and contextual view analysis. Statistics and network diagrams are developed from each perspective to analyze the relational railway incident data. The results show that most railway incidents are caused by more than one factor, and one factor tends to cascade into others. Each factor has its own role in the occurrence of an effect, but interdependencies can still be found among most factors. The significant factors in railway incidents are revealed in this study, and it is suggested that tackling the occurrence of the significant factors and their interdependent factors is effective for controlling and reducing the occurrence of railway incidents. The network analytical framework can be used to forward estimate the effect specifically caused by a factor and its propagation exposure, as well as to backward determine the possible causes of an effect from its interdependent intermediates and factors.

Practicing What You Preach

Introduction:During a mass casualty incident (MCI) seminar in Rome, Italy a survey was used to gauge the self-efficacy and confidence of the participants in managing an MCI. Following the course, a follow-up presentation was held by the Torino EMS Medical Director to evaluate and debrief the Torino Railway incident that occurred one day prior. Students partook in a seminar on MCI management, as well as a debriefing of the Turin Railway accident in which they evaluated the skills used by teams on the scene to manage the incident.Methods:Medical students partook in a seminar to learn to manage an MCI scene, as well as a debriefing of the Turin Railway accident. Following both seminars, the students were given a survey to assess their sense of self-confidence in managing such a situation.Results:The mean level of self-efficacy prior to the MCI training (M=3.43, SD+0.42) increased after the training (M=3.71, SD+0.37) and remained at the same higher level (M=3.71, SD+0.51) after the medical students were exposed to the details of the Turin train accident. The overall difference between the mean self-efficacy scores in the three time frames was not found to be significant. The mean level of confidence in managing MCIs prior to the training (M=2.83; SD+0.89) increased after the training (M=3.56; SD+0.53) and remained higher following the presentation of the Turin train accident, despite a slight decrease (M=3.52, SD+0.63).Discussion:The participants’ surveys showed an increase in their self-efficacy and confidence following the course and follow-up presentation. It is our professional recommendation that real-life events be used in such seminars to increase self-efficacy and confidence. The topic will continue to be evaluated further.

The indirect costs assessment of railway incidents and their relationship to human error - The case of Signals Passed at Danger

The majority of railway incidents result neither in passenger nor operators harm, nor they lead to any severe damage on the rolling stock or the infrastructure. Nevertheless, such incidents result in financial loses, broadly known as indirect costs, which are difficult to identify, isolate, evaluate, and quantify. This paper introduces a framework to quantify the indirect costs in railway operations. Furthermore, as degraded human performance remains a major contributor to operational errors and railway incidents, this study explores for associations between the indirect costs and the factors that affect and contribute to degraded human performance. The framework was implemented in the calculation of the Category A1 Signals Passed at Danger (SPADs) indirect costs. Data was obtained from two UK train operators, while the associated human performance was analysed using the Railway-Performance Shaping Factors (R-PSFs) taxonomy. Employing Spearman's rank order correlation and Fisher's exact statistical tests the associations between R-PSFs and indirect costs were reviewed. Results show significant correlations between the R-PSFs and indirect costs, but only if the importance and severity of every individual R-PSFs is considered. We expect our findings to aid the relevant stakeholders on their efforts to make better decisions on improving safety performance of railway operations.

A Preliminary Review of Fatigue Among Rail Staff.

Background: Fatigue is a severe problem in the rail industry, which may jeopardize train crew's health and safety. Nonetheless, a preliminary review of all empirical evidence for train crew fatigue is still lacking. The aim of the present paper is, therefore, to provide a preliminary description of occupational fatigue in the rail industry. This paper reviews the literature with the research question examining the risk factors associated with train crew fatigue, covering both papers published in refereed journals and reports from trade organizations and regulators. It assesses the progress of research on railway fatigue, including research on the main risk factors for railway fatigue, the association between fatigue and railway incidents, and how to better manage fatigue in the railway industry.Methods: Systematic searches were performed in both science and industry databases. The searches considered studies published before August 2017. The main exclusion criterion was fatigue not being directly measured through subjective or objective methods.Results: A total of 31 studies were included in the main review. The causes of fatigue included long working hours, heavy workload, early morning or night shifts, and insufficient sleep. Poor working environment, particular job roles, and individual differences also contributed to fatigue.Conclusion: Fatigue in the rail industry includes most of the features of occupational fatigue, and it is also subject to industry-specific factors. The effect of fatigue on well-being and the fatigued population in the railway industry are still not clear. Future studies can consider associations between occupational risk factors and perceived fatigue by examining the prevalence of fatigue and identifying the potential risk factors in staff within the railway industry.

Biomarkers in patients admitted to the emergency department after exposure to acrylonitrile in a major railway incident involving bulk chemical material.

A railway incident with victims of exposure to the cyanogenic substance acrylonitrile (ACN). We retrospectively (i)built an inventory of the clinical characteristics of individuals admitted to surrounding emergency departments (ED's) and (ii)studied the correlation between N-2-cyanoethylvaline (CEV), a biomarker used in a population study for evaluating exposure to ACN, with lactate and thiocyanate (SCN), biomarkers determined during emergency care. 438 patients from 11 ED's were included and presented with known symptoms of ACN poisoning but also with concern about the risks. A comparison of CEV with lactate or SCN was possible in 108 and 73 patients respectively. CEV was very high in a critically ill patient with a high lactate. There was no correlation with CEV in the patients with normal or slightly elevated lactate concentrations. A correlation of CEV with SCN was only observed in smokers. First there is a lack of data in some clinical files concerning the time and duration of exposure and the smoking-status. A second limitation is that blood samples for biomarkers were not taken systematically in all patients, which may have induced bias. A third limitation is that blood sampling was possibly done outside the correct time window related to the delayed toxicity of ACN. Finally the number of severely-intoxicated patients was low and ACN exposure may not have taken place e.g. in individuals consulting with psychological symptoms. These aspects may have contributed to the below detection limits' analyses of biomarkers. CEV was markedly elevated in a severely-intoxicated patient with high lactate, a sensitive marker for CN intoxication. We found no correlation of CEV with normal or slightly elevated lactate concentrations but clinicians should consider the possibility of subsequent rises due to the delay in ACN toxicity. CEV correlated with SCN in smokers, which may be explained by ACN in tobacco smoke and deserves further exploration. Further studies are necessary to evaluate the correlation between biomarkers in acute chemical exposures to ACN and these should be carried out prospectively using a preplanned template.

철도사고 대응매뉴얼 과부하에 대한 진단과 개선방안 연구

철도사고 대응매뉴얼 과부하에 대한 진단과 개선방안 연구

A Ten year review of alcohol use and major trauma in a Canadian province: still a major problem

BackgroundAlcohol plays a significant role in major traumatic injuries. While the role of alcohol in motor vehicle trauma (MVT) is well described, its role and approaches to prevention in other injury mechanisms is less defined.MethodsA 10 year retrospective examination of Alberta Trauma Registry (ATR) data was conducted on all major trauma patients (age ≥ 9 and ISS ≥ 12) from 2001–2010. The role and prevalence of alcohol is examined.ResultsOf 22,457 patients included in our study, only 60 %(n = 13,552) were screened for alcohol use. Of those screened, 38 %(n = 5,170) tested positive for alcohol with a mean blood alcohol concentration (BAC) of 39.4 ± 21.1 mmol/L. Of the positive screening tests, 82.3 % had BAC levels greater than the common legal driving limit of 17.4 mmol/L (0.08 %). Testing positive was associated with male gender (p < 0.001) and younger age (p < 0.001). The rate of positive alcohol use in major trauma increased from 20.3 % in 2001 to 24.3 % in 2010, corresponding with a screening rate increase from 51.3 % to 61.2 % over the same period. Railway incidents have the highest rate of alcohol involvement (65 %), followed by undetermined-if-accidental/self-inflicted (53.5 %) and assault (49 %); motor vehicle traffic (MVT) incidents had a frequency of 25.4 %.ConclusionsThe prevalence of alcohol use in major trauma appears to be increasing in Alberta but the true extent is still underappreciated. Furthermore, the role of alcohol in non-MVT injuries is significant and deserves further attention. The vast majority of patients involved in alcohol-related trauma are legally intoxicated. Alcohol use continues to be a substantial contributor to major trauma in Alberta, and represents an important opportunity to reduce preventable injuries.

Data based framework to identify the most significant performance shaping factors in railway operations

Human performance is a major contributor to railway incidents and accidents. The literature shows that it is operators, i.e. train drivers, signallers and controllers, who mainly affect the railway system in terms of safety. Numerous studies have investigated the influence of such operators on the railway system, but are usually based on studies from other domains and cannot be reliably applied to railway specific operations. This paper presents a framework to identify the most significant human performance factors, known as Performance Shaping Factors (PSFs), which influence the performance of railway operators. These Railway-Performance Shaping Factors (R-PSFs) are derived from an extensive literature review, together with an analysis of 479 railway operational incidents and accidents over the past 15years worldwide. Subject Matter Experts in the railway domain subsequently validated the identified factors. Statistical analysis of the railway operational incidents and accidents is subsequently conducted, following data quality checks. Based upon the Pareto principle, 12 R-PSFs account for more than 90% of the accidents and incidents, regardless of the severity of the event. Results from the analyses indicate the contribution of each individual R-PSF to the occurrence of a railway incident or accident, and highlight the importance of specific R-PSFs either individually or in combination for features related to specific types of accidents and incidents. The findings of the analysis can be used to direct resources more efficiently towards the development of sound solutions for improving the performance of railway operators. In addition, based upon the R-PSFs, a checklist of human performance factors is developed which can be used for investigation purposes and to collect human performance measures in a consistent and logical manner. The proposed checklist and its usage can greatly improve safety management systems of railway organisations.