Accident Record Research Articles

TIME SERIES MODELLING OF ROAD TRAFFIC ACCIDENTS IN WEST ARSI, ETHIOPIA

The aim of this research is time series modeling of road traffic accidents in the west Arsi zone, Ethiopia, it focused on monthly traffic accidents from January 2016 to December 2020. The goal of this study was to explore the number of traffic accidents to fit a time series model for the monthly number of road traffic accidents and to forecast a tow year ahead of the number of road traffic accidents. The analysis was done by using statistical software packages using this software and knowledge of time series analysis, trend, ACF, PACF, and Box-Jenkins analysis were computed. From the trend plot, the road traffic accidents was fluctuate from month to month as well as from year to year. There was total accident fluctuation from month to month (not stationary) a total of 1010 RTA were observed. The mean of 16.83 and standard deviation of 5.764 for the total accident was served the minimum and maximum record of road traffic accidents is 4 and 33 respectively. By differencing data one time, (2, 1, 3) model was fitted for making a two-year ahead forecast. Proper model adequacy checking was done. Two-year ahead forecasts showed that October, January, and April 2021 are the months with the most prominent values. Even if the trend in total accidents was decreasing there is still a need to pay more attention in order to prevent the occurrence of accidents related to road traffic accidents.

The Spirit of the Service: Dash, Discipline, and Flying Accidents in the Royal Australian Air Force, 1921–48

From its establishment in 1921, the Royal Australian Air Force (RAAF) attracted political and public critique for flying accidents. This article explores how its nascent institutional ethos developed in relation to a problematic safety record. Military aviators were expected to balance airborne “dash” against obeying flying orders, risking castigation if they proved either too timid or too reckless. Despite vigorous attempts to isolate their service from scrutiny, Air Force leaders were forced to adapt the RAAF's safety culture in response to civilian expertise, media pressure, political machinations, and comparisons with other air arms — particularly Britain's Royal Air Force. Through the 1930s and the Second World War, responsibility was increasingly channelled toward individual personnel. Tactics included severe punishments, signed attestations that confirmed compliance with orders and an “endorsement” system that permanently recorded infractions in errant flyers' log books. These measures risked producing timorous and inadequately skilled pilots, unprepared to exploit their aircraft's capabilities to the full. In 1945, the establishment of a Directorate of Flying Safety profoundly changed the RAAF's institutional safety culture, but its accident record remained problematic. Over 1921–48, the “sweet spot” between initiative and dependability eluded the RAAF's quest to inculcate an enduring “spirit of the service”.

Traffic Accident Severity Prediction Based on Data Cleaning and Machine Learning (Random Forest / Xgboost)

Traffic accidents have increasingly become a global concern, significantly affecting lives and economic sustainability. The US Accidents dataset from 2016 to 2023 provides an extensive record of accidents across the United States, containing detailed data and environmental data of these accident. This study aims to harness the potential of this rich database to predict severity level of accidents. Our research predominantly revolved around meticulous data cleaning, ensuring that the dataset's integrity was uncompromised. After preprocessing, the cleaned data was subjected to sophisticated Machine Learning techniques, primarily focusing on the Random Forest and XGBoost algorithms. These models were chosen due to their renowned capability in handling complex datasets and rendering accurate predictions, especially in scenarios laden with multiple variables. Upon application, the models demonstrated impressive efficacy. To validate the reliability and performance of our models, we employed the confusion matrix. This tool provided a clear visualization of the models' accuracy, revealing true positives, false negatives, and other crucial metrics. Furthermore, to enhance prediction outcomes, the Voting Classifier was implemented, combining the strengths of our primary models and consequently elevating the overall accuracy. The Random Forest algorithm exhibited substantial precision, while XGBoost further enhanced prediction accuracy. These findings underline the significant role of advanced data analytics and Machine Learning in comprehending traffic accident dynamics. In conclusion, our study emphasizes that leveraging state-of-the-art Machine Learning techniques on well-curated datasets can substantially improve our understanding and prediction of traffic accident severity. Such insights pave the way for the development of more effective preventive measures and safety protocols, aiming for a safer traffic environment in the future.

Analysis of Sedation Accident Records Available in the Japan Council for Quality Health Care Public Database.

Medical accidents occur frequently. However, only a few studies have been conducted on sedation-related medical accidents. This study aimed to classify sedation accidents and analyze their causes using the (Patient-management Software Hardware Environment Livewear (P-mSHELL) model. The Japan Council for Quality Health Care database on medical accidents was used. Sedation accidents that occurred during procedures between January 2010 and June 2022 were included. After examining the accident details for several variables, the accident factors were classified by factors in the P-mSHELL model, and statistical analyses, including multivariate analysis of each factor and outcome (presence or absence of residual disability), were conducted. Regarding the influence of the P-mSHELL factors on outcome, P factor (odds ratio = 6.347, 95% confidence interval = 2.000, 20.144) was a factor for having disability. There was a significant association between outcome and accident timing (that is, preoperative, intraoperative, or postoperative; p =0.01). No significant association was found between the outcomes and types of drugs used (p =1, 0.722, 0.594); however, there was a significant association between the incidence of respiratory depression and multiple drug use (p <0.001). To prevent sedation accidents, it is important to monitor patients throughout the perioperative period. However, it is especially important to know the patient's condition in advance, and strict postoperative management is essential, especially for high-risk patients, to prevent serious accidents.

Identifying key accident causation factors in the Malaysian construction industry

ABSTRACT Objectives. Notwithstanding its economic importance, the construction industry is still facing challenges due to its high accident record. As a result, the goal of this study is to identify the key underlying causes of accidents in the Malaysian construction industry that construction stakeholders can focus on to reduce the menace of accidents in the industry. Methods. To achieve this goal, relevant literature was reviewed in order to identify the causes of accidents. The identified factors were used to develop the survey questionnaire for collecting primary data, and the collected data were analysed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results. The results of the EFA and CFA establish and confirm 11 clusters for the causes of accidents on construction sites: management problems; inadequate training; inadequate supervision; mental health problems; bad attitudes; inadequate funding; inadequate experience; material and equipment handling; poor safety practices; inadequate orientation; and work environment. Conclusion. The study concludes that addressing all 11 factors will drastically reduce the incessant accident occurrences in the construction industry. The result of this study will help construction stakeholders know where to direct their energy in an effort to reduce construction accidents.

Analysis of accidents and road accidents involving vehicles of category L2

The article examines the issue of the peculiarities of maintaining statistics of road accidents in the Russian Federation in terms of recording road accidents involving tricycles. Taking into account the technical features of tricycles and the insignificant protection of the driver and passengers, it is proposed to separate these traffic accidents into a separate subcategory for analyzing and preventing the causes of accidents. Keywords tricycle, traffic accident, recording of traffic accidents

Comprehensive Screening of the Driving Ability of Older Drivers Using Physical Function, Driving Simulator Scores, Accident and Violation Records, and Life History Data

Comprehensive Screening of the Driving Ability of Older Drivers Using Physical Function, Driving Simulator Scores, Accident and Violation Records, and Life History Data

Cycling under the influence of alcohol and other drugs: An exploratory analysis

We explore several aspects of Cycling Under the Influence (CUI) of alcohol and other drugs. CUI remains a relatively under researched topic, even though evidence suggests that it is a rising safety risk as both cycling mileage and alcohol consumption are increasing. We present the results of a quantitative survey designed to (i) assess the amplitude of the problem among Parisians and (ii) identify precursors for bicycle accident involvement and CUI practices. Our research provides evidence proving that CUI is indeed a common practice among Parisian cyclists (F(alcohol) = 46 % and F(drugs) = 10 %). Cyclists declare to be aware of related risks, but rarely adapt their drinking/cycling behavior to avoid them, even when they have previous accident involvement record. Shared vehicles’ users are more prone to CUI during night leisure outings when public transport is not available. Also, increased previous experience in cycling or in alcohol or drug consumption seems to make riders overconfident and therefore raise the probability of CUI.

Identifying the Critical Risk Factors for Road Crashes Based on Large-Scale Safety Audits in India

Road transportation is considered one of the most essential factors for the growth of a country. Due to the exponential growth in population and fast urbanization, the existing roadway facilities are facing a huge surge in vehicle growth. But this development is also accompanied by the concerning growth of road crashes. To mitigate road crashes, one needs to identify the potential risk factors involved with them. This requires detailed accident data, which is sometimes difficult to acquire and in addition, there is a high probability of accidents in many places due to various hazardous situations, but there may not be an accident record yet. Road Safety Audit is an alternative approach that can overcome these obstacles. Hence, the present study has attempted to highlight various risk factors involved with road crashes for four different road facilities type, viz. Straight, intersection, curve, and road with culvert and flyovers (RCF) by conducting the Road Safety Audit for 216 black spots. Analytic Hierarchy Process (AHP) was performed on the data collected from the audit process to determine the weightage of involvement of each factor in road crashes and identify the most significant ones.

Longitudinal Outcomes of Cumulative Impact Exposure on Oculomotor Functioning in Professional Motorsport Drivers

Professional motorsport drivers are regularly exposed to biomechanical forces comparable with those experienced by contact and collision sport athletes, and little is known about the potential short-term and long-term neurologic sequelae. To determine whether cumulative impact exposure is associated with oculomotor functioning in motorsport drivers from the INDYCAR professional open-wheel automobile racing series. This is a longitudinal retrospective cohort study conducted across 3 racing seasons (2017-2019). Statistical analyses were conducted in November 2021. Data were retrieved from a secondary care setting associated with the INDYCAR series. INDYCAR series drivers who participated in 3 professional level racing seasons and were involved in at least 1 contact incident (ie, crash) in 2 of the 3 seasons were included in the study. Cumulative acceleration and deceleration forces and total contact incidents (ie, crashes) measured via accident data recorder third generation chassis and ear accelerometers. Postseries oculomotor performance, including predictive saccades, vergence smooth pursuit, and optokinetic nystagmus, was measured annually with a head-mounted, clinical eye tracking system (Neurolign Dx 100). Thirteen drivers (mean [SD] age, 29.36 [7.82] years; all men) sustained median resultant acceleration forces of 38.15 g (observed range, 12.01-93.05 g; 95% CI, 30.62-65.81 g) across 81 crashes. A 2-way multivariate analysis of variance did not reveal a statistically significant association between ear and chassis average resultant g forces, total number of contact incidents, and racing season assessed (F9,12 = 0.955; P = .54; Wilks Λ = 0.44). In this cohort study of professional drivers from the INDYCAR series, there were no statistically significant associations among cumulative impact exposure, racing season assessed, and oculomotor performance. Longitudinal studies across racing seasons using multidimensional examination modalities (eg, neurocognitive testing, advanced imaging, biomarkers, and physical examination) are critical to understand potential neurological and neurobehavioral sequelae and long-term consequences of cumulative impact exposure.

Причины разрушения технологического моста

The paper considers the conditions and causes that led to an accident during the construction of a bridge crossing over the Volga on support № 4. For the construction of the pile foundation of the main supports, a SENNEBOGEN 7700 erection crane was used, installed on an auxiliary technological bridge. The accident occurred on 06.12.2020. The SENNEBOGEN 7700 crane fell from the technological bridge into the water when moving a diesel hammer with a cage weighing 61 tons to the storage site. Analysis of the accident recording of the external surveillance camera, the results of the diving survey and the information decoded from the parameter recorder allow to conclude that the crane was lifting a load less than the maximum load capacity according to the project. The parameter recorder before the time of the accident showed that there was no overload. The accident was caused by the destruction of one of the ceiling beams on which the crane was located. This beam was found destroyed at the bottom of the river. To determine the reasons for the destruction of the beam, the expert organization EDO Research Center LLC conducted an expert examination of the support beams BO1. To do this, the destroyed elements of the bridge were raised from the bottom of the river, and the studies of the metal of the beam, welds, and the entire structure were carried out. A full analysis of the design and working documentation, according to which the beams were made, was carried out. The article analyzes the reasons that led to the destruction of the beam, and provides recommendations for the designers, manufacturers and enterprises operating technical devices at the hazardous production facilities. The organization-customer of such structures should entrust their manufacture only to the specialized organizations. The manufacturing organization is obliged to prepare a passport with a serial number, instructions for installation and operation, documents confirming the performance of the designated type and scope of non-destructive testing of welds, provide the design with a marking plate, and apply personal marks of welders to the welds. The operating organization, in case of doubt as to the quality of the manufacture of the product, should not use such structures in the construction of especially hazardous facilities.

Magnitude and determinants of road traffic accidents in North Gondar Zone; Amhara Region, Ethiopia

Background: Despite efforts that the government has made to minimize the number of casualties or injury levels in Ethiopia, road traffic accidents remain a severe health concern throughout the country and in the study area as well. This study aims to examine the primary contributing variables of road traffic accidents in the North Gondar zone, under 24 administrative. Methods: The functional class of roads were directly examined on the site to evaluate the existing conditions of the roads which includes the geometric design constraints, functional class, daily traffic, and surfacing materials. Secondary source of data types, previously recorded road traffic accident information was collected from North Gondar zone traffic police departments. Road inventory information was collected from Gondar branch Ethiopian road authority under the specified horizon lines. Results: The magnitude and frequency of traffic accidents caused by driver-related factors( age, sex, level of education, driving experience, ownership responsibility of a vehicle and driver responsibility, time and day-wise distribution of traffic accidents), vehicle-related factors (failures of mechanical parts and its service age), road related factors( geometric design and construction, inventory information, road surfacing materials), pedestrians, and environmental factors were critically analysed. The result shows that a higher proportion (67%) of traffic accidents are mainly due to driver behaviour related factors than other causative factors. Conclusions: According to the results of the study, bad driving behaviour’s (exceeding the design speed, using a phone while driving, dangerous overtaking, excessive braking, loading above capacities, illegally parking out of public stations should be controlled to reduce the road traffic accident in the study area. In addition, successive up-to-date advanced computerized traffic accident safety training and recording systems should be given at least once a year through regional-based or at a central zone administrative zones for the traffic officers.

Forecasting Road Traffic Accidents in Metro Manila Using ARIMA Modeling

In this paper, we have determined and analyzed the behavior of road traffic accidents (RTAs) in Metro Manila, Philippines over the period of 2012-2021, and created a forecast for the next 5 years using ARIMA modeling. This study used 10-year historical monthly data collated through the Metro Manila Accident Recording and Analysis System program for the years 2012 through 2021. Our result suggests that the total RTAs in Metro Manila gradually increased until the first quarter of 2020, then it plummeted and reached its lowest point in April 2020 due to COVID-19 lockdown. As lockdown eases, it bounced back but only halfway. Similarly, RTAs resulting in damage to property also bounced back to only halfway as lockdown eases, while RTAs resulting in injuries (fatal and nonfatal) bounced back to their normal range as before the lockdown. Despite the decrease in total RTAs, the ratio of RTAs resulting in injuries drastically increased during the lockdown due to reckless driving behaviors. Using Box-Jenkins methodology of ARIMA modeling, this study identified ARIMA (1, 1, 12) as the best model. With this model, the forecast shows that the total RTAs will stay halfway in 2022 and gradually decrease for the next 4 years.

VECDSigL: Video integrity verification using elliptic curve digital signature links

<h2>Abstract</h2> Video footage is produced as evidence in medical investigations, legal investigations, etc. With the advancements in video editing tools, it is easy to make modifications to videos without leaving evidence of manipulations. Thus requirement of video authentication is becoming a necessity need in mobile phones, accident data recorders, Closed Circuit Television, etc. The video integrity verification system confirms that the video under consideration is not altered. We present a prototype, VECDSigL that ensures faster and more secure signature generation, blockchain storage, and integrity verification of digital videos. Video integrity verification is done using blockchain, where each block stores elliptic curve digital signatures of a video segment and the previous block. This video integrity verification system implemented is robust to different attacks such as brute force attacks and collision attacks. This system can detect forgeries of any kind and can verify the integrity of any video type.

Assessment of Causes and Design Solution to Road Traffic Accident Along Onitsha-Owerri Expressway in Eastern Nigeria

The incessant road crashes on Onitsha-Owerri road is worrisome. It has become a norm that a day will not pass by without a record of accident on that road. This prompted the researchers to assess the dominant factors of such incidence and proffer solution. 300 questionnaires were prepared and distributed in the study area to source information from drivers, out of which 267 participated. The SPSS tool was used to analyze the data obtained from the respondents. The findings showed different causes of accidents which include driving under the influence of alcohol/drugs, uninspected vehicles, bad roads, and overloading. But the major factor found is purported wrong establishment of roadblocks at hilly, supper elevation and sharp bend using for checkpoint. The study recommends the construction of a toll gate with checkpoint on a good terrain at Oba and Awo-Omamma. The researcher sketched a toll gate with checkpoint, height barrier to avert overloading and a digital camera that will serve as a point of inspection. This would eliminate all unprofessional and unwanted road block/checkpoints in the area and creates an avenue for good revenue which will be a benefit to our economy. The issue of overloading would be tackled at the tollgate, where road height barriers are positioned to stop drivers from carrying excess loads and a weighing bridge would be positioned at the side of the toll gate to measure the weight of overloaded vehicles.

PEMBINAAN SISWA/I SMK WIDYA BATAM TERHADAP PROGRAM KESELAMATAN BERLALU LINTAS DALAM ETIKA BERKENDARA

Technological developments also have an impact on the transportation system on the highway. One of them is the various types and types of transportation used by society today. Based on data, every year 1.3 million people die as a result of road traffic accidents and more than 3,000 people die every day due to traffic accidents. One of the cities in Indonesia that is classified as having the highest traffic accident record, namely Batam. The rate of traffic accidents in Batam City has increased every year, where data states that there has been an increase in traffic accidents of 47% for the 2019-2020 period. The high traffic accidents in Batam generally occur due to a lack of public knowledge and awareness in driving and traffic, especially among school children and adolescent drivers. As happened at SMK Widya Batam, where almost 80% of the students use motorbikes for school transportation. Therefore, through fostering the Traffic Safety program socialization in driving ethics for Widya Batam Vocational School students both within the school environment and outside the school environment, it is hoped that it can provide the transfer of information and knowledge about the importance of increasing awareness of driving ethics and concern for traffic safety and also participate participate in maintaining security, order and safety on the road.

Bezpečnosť a ochrana zdravia pri práci s ohľadom na štatistickú klasifikáciu ekonomických činností

Occupational health and safety is responsible for creating conditions that eliminate the impact of hazardous and harmful factors of the work process or environment on employees. The employer is obliged to report work accidents with the prescribed formalities to the labour inspectorate. The Labour Inspectorate keeps a record of the accidents in question but does not carry out a detailed comparison of the individual factors in the work accident. In order to ascertain the factors influencing the accident, the accident records from the regional inspectorate were analysed and collated. The records were for the period 2012 to 2022. Based on the most common groups of injuries identified in each category, opportunities for improving occupational health and safety were suggested.

A review on safety knowledge and skills for reducing human error and accidents in construction

Human error remains a significant contributor to construction accidents, highlighting the importance of human factors in construction safety management. Possessing appropriate knowledge and skills is critical for workers in this regard. Safety knowledge enables workers to identify hazard, prevent, reduce, and eliminate potential accidents. On the other hand, safety skills are necessary for worker to carry out their task and responsibilities safely. The absence of either knowledge or skills can result in human error and construction accidents. This literature review aims to identify the various types of safety knowledge and skills that can help reduce construction human error and accidents. Through the analysis of several articles, the review found that safety regulation and accident record are essential safety knowledge, while hazard identification, communication, and leadership are crucial safety skills that can reduce construction human error and accidents.

Coastal Traffic Safety Index Based on Marine Accident and Traffic Records

Coastal Traffic Safety Index Based on Marine Accident and Traffic Records

Reckoning Level of Risk and Severity (LORS) Based on the Gap Acceptance at a Three-Legged Uncontrolled Intersection of a Rural Highway

Traffic safety assessment is an essential part of traffic planning and engineering. At uncontrolled intersections, the severity of crashes has increased manifolds. This is due to the fact of not following the priority rule during the right-turning movements. In conventional methods, past accident records were used to analyze traffic safety. However, the drawbacks of the traditional method to estimate the severity require a lot of accident data for analysis to draw any conclusion and suggest safety measures. The accuracy of the record of accidents and details is highly uncertain. Therefore, surrogate safety measures are being used to analyze the safety. In the present paper, the gap acceptance time (GT) is used to examine the risk and the speed and gap values define the level of risk and severity (LORS). Moreover, using the value of the critical gap, the probability of risk is estimated. Further, the level of risk and severity is computed based on the gap and speed data of vehicles at an uncontrolled intersection. Hence, with the speed and gap data, the level of risk and severity is classified as low risk, high risk and low severe, and high severe. The methodology implemented is validated by using the actual accident data.