Railway accident causation analysis: Current approaches, challenges and potential solutions

Hong, Wei-Ting; Clifton, Geoffrey; Nelson, John D.

doi:10.1016/j.aap.2023.107049

Cited by 9 publications

(2 citation statements)

References 94 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both methodologies have been extensively employed in the process of comprehending the causes of human mistakes in the railway sector. Hong et al (2023)Causation extraction in railway accident analysis is crucial for identifying cause-andeffect relationships between events, enabling a structured description of accidents. Baysari et al (2008) summarize relevant accident causation research regarding human errors.…”

Section: Discussionmentioning

confidence: 99%

Risk Assessment of Human Error in Orange-line Metro Depot Operation

2023

JDSS

View full text Add to dashboard Cite

This research paper employs a comprehensive risk matrix approach to analyze the potential risks associated with the Orange Line Metro Rail Transit System (OLMRTS). The major focus of this study revolves around two critical safety variables: human error and equipment failure, with a particular emphasis on human error as the most significant contributing factor. The research methodology involves the development of risk assessment models based on various incident scenarios. To identify potential hazards and assess their severity, historical incident data from a range of sources was collected and analyzed. This data made it possible to identify a number of potentially hazardous circumstances that could have an adverse impact on OLMRTS depot operations. The frequency and severity of each hazardous event were carefully evaluated based on the historical incident data, providing valuable insights into the potential risks faced by the system. The key findings of this investigation highlight that human-related activities emerge as the most significant potential cause of risk within the context of OLMRTS. The data analysis indicates a high level of risk associated with human error, underscoring the importance of addressing and mitigating these risks to enhance the overall safety and reliability of the OLMRTS system.

show abstract

Section: Discussionmentioning

confidence: 99%

Risk Assessment of Human Error in Orange-line Metro Depot Operation

2023

JDSS

View full text Add to dashboard Cite

show abstract

“…The number of traffic accidents at railway crossings is still quite high, especially at crossings without guards/doorstops (Hong et al, 2023;Johnson, 2015). Accidents at railway crossings occur not only in Indonesia or other developing countries but also in developed countries.…”

Section: Introductionmentioning

confidence: 99%

Redesign roadmap to support driving awareness at level railway crossings

Sugiono,

Wiryawan,

Rahayudi

et al. 2024

J. Infras. Policy. Dev.

View full text Add to dashboard Cite

The number of accidents at level railway crossings, especially crossings without gate barriers/attendants, is still very high due to technical problems, driving culture, and human error. The aim of this research is to provide road maps application based on ergonomic visual displays design that can increase awareness level for drivers before crossing railway crossings. The double awareness driving (DAD) map information system was built based on the waterfall method, which has 4 steps: defining requirements, system and software design, unit testing, and implementation. User needs to include origin-destination location, geolocation, distance & travel time, directions, crossing information, and crossing notifications. The DAD map application was tested using a usability test to determine the ease of using the application used the System Usability Scale (SUS) questionnaire and an Electroencephalogram (EEG) test to determine the increase in concentration in drivers before and immediately crossing a railway crossing. Periodically, the application provides information on the driving zone being passed; green zone for driving distances > 500 m to the crossing, the yellow zone for distances 500m to 100m, and the red zone for distances < 100 m. The DAD map also provides information on the position and speed of the nearest train that will cross the railway crossing. The usability test for 10 respondents giving SUS score = 97.5 (satisfaction category) with a time-based efficiency value = 0.29 goals/s, error rate = 0%, and a success rate of 93.33%. The cognitive ergonomic testing via Electroencephalogram (EEG) produced a focus level of 21.66%. Based on the results of DAD map testing can be implemented to improve the safety of level railroad crossings in an effort to reduce the number of driving accidents.

show abstract