Applying Data Mining Approaches for Analyzing Hazardous Materials Transportation Accidents on Different Types of Roads

With the increase in the demand for and transportation of hazardous materials (Hazmat), frequent Hazmat road transport accidents, high death tolls and property damage have caused widespread societal concern. Therefore, it is necessary to carry out risk factor analysis of Hazmat transportation; predict the severity of accidents; and develop targeted, extensive and refined preventive measures to guarantee the safety of Hazmat road transportation. Based on the philosophy of graded risk management, this study used a priori algorithms in association rule mining (ARM) technology to analyze Hazmat transport accidents, using road types as classification criteria to find rules that had strong associations with property-damage-only (PDO) accidents and casualty (CAS) accidents under different road types. The results indicated that accidents involving PDO had a strong association with weather (WEA), traffic signals (TS), surface conditions (SC), fatigue (FAT) and vehicle safety status (VSS), and that accidents involving CAS had a strong association with VSS, equipment safety status (ESS), time of day (TOD) and WEA when urban roads were used for Hazmat transportation. Among Hazmat transport incidents on rural roads, the incidence of PDO accidents was associated with intersections (IN), SC, WEA, vehicle type (VT), and segment type (ST), while the occurrence of CAS accidents was associated with qualification (QUA), ESS, TS, VSS, SC, WEA, TOD, and month (MON). Strong associations between the occurrence of PDO accidents and related items, such as IN, SC, WEA and FAT, and the occurrence of CAS accidents and related items, such as ESS, TOD, VSS, WEA and SC, were identified for Hazmat road transport accidents on highways. The accident characteristics exemplified by strongly correlated rules were used as the input to the prediction model. Considering the scarcity of these events, four prediction models were selected to predict the severity of Hazmat accidents on each road type employing four analyses, and the most suitable prediction model was determined based on the evaluation criteria. The results showed that extreme gradient boosting (XGBoost) is preferable for predicting the severity of Hazmat accidents occurring on urban roads and highways, while nearest neighbor classification (NNC) is more suitable for predicting the severity of Hazmat accidents occurring on rural roads.

Hit-and-run: a Swedish nationwide cohort study of serious transport accidents and convictions due to traffic offenses in obsessive–compulsive disorder

Purpose Individuals with obsessive–compulsive disorder (OCD) often report driving-related obsessions, such as fears of causing accidents, but the risk of transport accidents in OCD is unknown. We investigated whether individuals with OCD have an increased risk of serious transport accidents and convictions due to traffic offenses and explored the role of psychiatric comorbidities. Methods We included all individuals ≥ 18 years living in Sweden between 1997 and 2013 (N = 5,760,734). A total of 23,126 individuals had a diagnosis of OCD in the National Patient Register. We also identified 16,607 families with full siblings discordant for OCD. Cox proportional hazards regression models estimated hazard ratios (HRs) with 95% confidence intervals (CIs) for the risk of three outcomes in individuals with OCD, compared to unexposed individuals and their unexposed full siblings: injuries or deaths due to transport accidents, injuries or deaths due to motor vehicle accidents, and convictions related to traffic offenses. Psychiatric comorbidities were systematically adjusted for. Results Women, but not men, with OCD had a marginally increased risk of serious transport accidents (adjusted HR = 1.20 [95% CI 1.13–1.28]) and motor vehicle accidents (adjusted HR = 1.20 [95% CI 1.09–1.31]), compared to unaffected individuals. Neither women nor men with OCD had a significantly increased risk of convictions. The sibling comparisons showed no significant associations. When psychiatric comorbidities were adjusted for, several observed associations became non-significant or inversed (HRs and 95% CIs below one). Conclusion The risks of serious transport accidents and driving-related criminal convictions in OCD are negligible and heavily influenced by psychiatric comorbidity.

Effect of the New Zero-Tolerance Drinking and Driving Law on Hospital Admissions Due to Road Traffic Accidents in Brazil: an Interrupted Time Series Study From 2008 to 2019 Short Title New Zero-tolerance Drinking and Driving Law on Hospitalization in Brazil

We investigated the effect of the new zero-tolerance drinking and driving law (Law 12760) on hospital admissions due to road traffic accidents in Brazil by using interrupted time series from 2008 to 2019. We used ICD-10 codes for land transport accidents (V00-V89). The hospitalization rate was calculated per 100,000 inhabitants. The sources were the Hospital Information System and the Brazilian Institute for Geography and Statistics. For Brazil, the hospitalization rate decreased by 0.400841 (p=0.052; 95% CI -0.8060128 to -0.0043307) in the first month of the intervention (December 2012), followed by a significant change in the hospitalization trend. Compared to the period prior to the intervention, the monthly trend was reduced by 0.048215 (p<0.01; 95% CI 0.0614524 to 0.0349775) in the post period. These results stand in agreement with subgroup analyses for the Brazilian regions, although North and Northeast regions did not immediately reduce hospitalization rates (level change). Our results suggested that 436,581 hospitalizations for land transport accidents were averted by the new zero-tolerance drinking and driving law from Dec. 2012 to Dec. 2019 in Brazil.

Radiological Risk Assessment of Vehicle Transport Accidents Associated with Consumer Products Containing NaturallyOccurring Radioactive Materials

Natural and artificial ionizing radiation can be harmful to human health when they come into contact with people and the environment. Transport of naturally occurring radioactive materials (NORMs) and consumer products containing NORM in the public domain is inevitable owing to their potential applications. This study evaluates the dose and risk to the public from transport accidents of NORM and consumer products. Radiological and physical data were obtained from previous literature. The median and maximum values of radioactivity concentration were applied to consumer products and NORM data, which serve as an input. An external dose rate at 1 m from a transported shipment was calculated using MicroShield® Pro version 12.11 code, which serves as input to RADTRAN 6 code. Based on developed transport accident scenarios, a RADTRAN 6 code was used to estimate collective dose and risk. The sensitivity analysis was conducted by considering the variation of release, aerosol, and respirable fractions of radionuclides at 0.1%, 1%, 10%, and 100% from the transported shipment during an accident, respectively. The results of dose and risk to the general public because of the damage of the shipment container following a fire accident are below the annual regulatory limits of 1 man-Sv recommended by IAEA transport regulation of 2018. The sensitivity results of all NORMs and associated consumer products are also below the regulatory limits. Therefore, radiological safety can be ensured in the event of a transport accident involving the transit of NORM and consumer products containing NORM.

Assessment of the possible amount of harm in case of emergency discharges of bulk cargo from ships

При прогнозировании последствий аварий с участием транспортных судов существует необходимость в получении оперативных оценок размера вреда и длительности воздействия загрязняющих веществ в водных объектах для определения уровня реагирования и разработки защитных мероприятий. Наибольшую экологическую опасность представляют сбросы следующих грузов: удобрений, нефтепродуктов, соли, соды, серы, угля. В статье решается задача по определению возможного размера вреда при аварийных сбросах не нефтеналивных грузов с судов в Волжском бассейне внутренних водных путей. Для этого создана база данных по транспортным происшествиям с участием сухогрузных судов за период наблюдения с 2007 по 2018 гг., выполнено определение гидрологических условий распространения загрязняющих веществ и оценка их концентраций в воде для расчета длительности воздействия. Методика оценки возможного размера вреда водным объектам при сбросе сыпучих грузов при транспортных происшествиях основывается на учете агрессивности ингредиентов различных видов грузов и условных вероятностей их сброса, времени и места сброса, длительности воздействия. В результате выполненных исследований разработано математическое описание для оценки возможного размера вреда водным объектам от сбросов сыпучих грузов при транспортных происшествиях; создана классификация участков концентрации транспортных происшествий по уровню возможного размера вреда водным объектам при сбросе сыпучих грузов; получено уравнение связи размеров вреда при сбросе сыпучих грузов и грузоподъемности судна (массы сброса). When predicting the consequences of accidents involving transport vessels, there is a need to obtain operational estimates of the amount of harm and the duration of exposure to pollutants in water bodies to determine the level of response and develop protective measures. The greatest environmental hazard is posed by the discharges of the following cargoes: fertilizers, oil products, salt, soda, sulfur, coal. The article solves the problem of determining the possible amount of harm in case of emergency discharges of non-oil cargo from ships in the Volga basin of inland waterways. For this, a database on transport accidents involving dry cargo vessels was created for the observation period from 2007 to 2018, the hydrological conditions of the spread of pollutants were determined and their concentrations in water were estimated to calculate the duration of exposure. The methodology for assessing the possible amount of harm to water bodies during the discharge of bulk cargo in transport accidents is based on taking into account the aggressiveness of the ingredients of various types of cargo and the conditional probabilities of their discharge, the time and place of discharge, and the duration of exposure. As a result of the research carried out, a mathematical description was developed to assess the possible extent of damage to water bodies from discharges of bulk cargo during transport accidents; a classification of areas of concentration of traffic accidents was created according to the level of possible damage to water bodies during the discharge of bulk cargo; an equation was obtained for the relationship between the size of damage during the discharge of bulk cargo and the carrying capacity of the vessel (discharge mass).

A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.

MORTALITY DUE TO TRANSPORT ACCIDENTS IN THE CITY OF SÃO PAULO: 2005-2015

ABSTRACT Objective: To characterize cases of land transport accidents in the macro-regions of city of São Paulo in 2005, 2010, and 2015. Methods: This is a population-based, longitudinal and retrospective study of time series, based on a quantitative survey of land transport accidents that occurred in the city of São Paulo in 2005, 2010 and 2015 using data from the Mortality Information System of the City of São Paulo. Results: A total of 1,343, 1,567 and 1,088 deaths by accident recorded in the city’ population in the years 2005, 2010 and 2015 respectively. The highest occurrences were in the age groups 15 to 24 years and 24 to 34 years. The highest number of deaths due to accidents was among males. The mortality rates observed in the macro-regions were South (23.8%), East (22%), North (21.6%), West (7.1%), and Center (3%). In comparing the years examined, there was a decline in the mortality rate per 100,000 inhabitants in most macro-regions. Conclusion: Despite the decrease in overall accident mortality in most macro-regions, it still deserves attention on preventive traffic actions focused on young males living in peripheral neighborhoods, since they represent the most susceptible group. Level of evidence II; Retrospective Study.

METHOD OF OPERATIONAL INVESTIGATION OF ROLLING STOCK DERAILMENT

The article presents the principles of the method of operational investigation of rolling stock derailment. This method is intended to identify the most significant mechanical reasons for transport accidents in order to find directions to further improving the safety requirements for the state of maintenance of freight cars and tracks on the basis of the data. The developed method establishes a general methodological order of conducting computer simulation of the dynamics of rolling stock of multivariate studies on calculating the safety indicators of train’s motion, and shows the significance of technical factors that provoked a certain event. By this method, the operational investigation of rolling stock derailment is based on the development of adequate computer models of dynamics of cars in trains. In this case, in detail, all the features of the car, which descended from the rails, are first. The presented method is based on the principles of factor analysis, where the intervals of varying events are presented in natural units of measurement. In this case, the assessment of security indicators for each research of the experiment plan is also carried out taking into account their dimension. As a result, the function of multiple regressions on the chosen indicator of motion safety allows not only to determine the significance of the factor of the ascent, but also to establish the level of factors, with exceeding the criteria for motion safety, that is, to determine the boundaries of the region with an acceptable level of motion safety.