Statistical Causal Analysis of Freight-Train Derailments in the United States

Liu, Xiang

doi:10.1061/jtepbs.0000014

Cited by 24 publications

(12 citation statements)

References 24 publications

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“…Many methods for analyzing the relationships among the causes that may lead to accidents and the corresponding possible consequences are available, which can be categorized as statistic regression models (i.e., multivariate regression and multinomial logit) [1,[14][15][16][17][18] and machine learning methods (typical as Bayesian network and decision tree) [19][20][21][22][23]. Desai et al [1] presented a sequence of statistical models (i.e., partial least squares, spline regression, and Box-Cox transformations) to estimate the population affected and the impact of the cost incurred as a result of hazmat accidents.…”

Section: Cause-consequence Analysismentioning

confidence: 99%

Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management

Zhou

Guo

Cui

et al. 2020

IJERPH

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The accidents caused by hazardous material during road transportation may result in catastrophic losses of lives and economics, as well as damages to the environment. Regarding the deficiencies in the information systems of hazmat transportation accidents, this study conducts a survey of 371 accidents with consequence Levels II to V involving road transportation in China from 2004–2018. The study proposes a comprehensive analysis framework for understanding the overall status associated with key factors of hazmat transportation in terms of characteristics, cause, and severity. By incorporating the adaptive data analysis techniques and tackling uncertainty, the preventative measures can be carried out for supporting safety management in hazmat transportation. Thus, this study firstly analyzed spatial–temporal trends to understand the major characteristics of hazmat transportation accidents. Secondly, it presented a quantitative description of the relation among the hazmat properties, accident characteristics, and the consequences of the accidents using the decision tree approach. Thirdly, an enhanced F-N curve-based analysis method that can describe the relationship between cumulative probability F and number of deaths N, was proposed under the power-law distribution and applied to several practical data sets for severity analysis. It can evaluate accident severity of hazmat material by road transportation while taking into account uncertainty in terms of data sources. Through the introduction of the as low as reasonably practicable (ALARP) principle for determining acceptable and tolerable levels, it is indicated that the F-N curves are above the tolerable line for most hazmat accident scenarios. The findings can provide an empirically supported theoretical basis for the decision-makers to take action to reduce accident frequencies and risks for effective hazmat transportation management.

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Section: Cause-consequence Analysismentioning

confidence: 99%

Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management

Zhou

Guo

Cui

et al. 2020

IJERPH

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“…Research on the analyses of train accidents in the United States has focused primarily on freight train derailments, 30–39 hazardous material releases, 40–48 and grade crossing incidents. 49–56 Relatively few studies have focused on the quantitative analysis of the safety of U.S. passenger trains.…”

Section: Literature Reviewmentioning

confidence: 99%

Quantitative causal analysis of mainline passenger train accidents in the United States

Lin

Saat

Barkan

2019

Proceedings of the Institution of Mechanical Engineers, Part F:

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The need for shared freight and passenger rail corridors in the United States is increasing due to the growing demand for regional and intercity passenger transport. Several researches have been conducted on reducing the risk of freight train accidents, but little research has been done on the risk of passenger train accidents. The accident rates of passenger trains have declined in the past two decades; however, faster and more frequent passenger train services require even higher safety standards, and therefore further reduction to the risk of passenger train accidents is needed. The research presented in this paper analyzed the passenger train accidents in the United States using the Federal Railroad Administration train accident database to understand the trend of passenger train accident rates, the frequency and severity of different types of accidents, and to explore the major factors that cause them. Derailments and collisions were identified as the most significant types of passenger train accidents, and track failures and human factors, respectively, were the primary causes of those accidents. Accidents caused due to human factors and train operations such as train speed violations and failure to obey signals are often high-consequence accidents and therefore pose the greatest risk. Higher risk infrastructure-related factors include track geometry defects and broken rails or welds. This study on passenger train accidents provides a solid foundation for further research on improving the safety of passenger rail and shared-use rail corridors.

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“…A railway vehicle derails when its wheels run off the rails and, in effect, the rails no longer provide the guidance of the vehicle in the lateral direction. Since the risk of derailment is of the ultimate safety concern in the operation of railway vehicles, it has been a subject of many studies in the past (for example, [12]) as well as the topic of ongoing researches [6,10,15,16,19,20,24]. While various scenarios of derailment are possible and the respective criteria have been proposed and are in use [18], one of the earliest relevant works was published by Joseph Nadal in 1896 [17].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of Dynamical Quantities Related to Running Safety and Ride Comfort of a Railway Vehicle

Kardas-Cinal¹

2020

SJSUT.ST

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This paper investigates the variation of track geometrical parameters that lead to a local increase of specific dynamical quantities of a railway vehicle, possibly beyond their acceptable values. In particular, the changes of track geometry are investigated near track points where the running safety or ride comfort are significantly decreased during the vehicle motion due to track irregularities. The investigated dynamical quantities include the lateral and vertical forces at the wheel-rail contact as well as the acceleration of the vehicle body. The vehicle motion has been simulated using a non-linear model of a passenger car moving along a nominally tangent stiff track with random geometrical irregularities. The relationship between the local track condition and the maxima of the dynamical quantities was investigated with the statistical method proposed by the author. The performed analysis clearly identifies the characteristic variation of track irregularities that leads to a large increase of the investigated dynamical quantities at some track points.

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Statistical Causal Analysis of Freight-Train Derailments in the United States

Cited by 24 publications

References 24 publications

Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management

Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management

Quantitative causal analysis of mainline passenger train accidents in the United States

Statistical Analysis of Dynamical Quantities Related to Running Safety and Ride Comfort of a Railway Vehicle

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