Risk Of Accidents Research Articles

Path analysis of coal mine accident risk factors based on the 24Model.

Coal mine accidents seriously affect China's coal safety production and sustainable development. The present study aimed to reveal the risk factors in coal mine accidents and explore the causal relationship among risk factors. This study utilized text mining to analyse 450 coal mine accident reports, identifying 50 risk factors and efficiently mapping them into the 24Model. The association rule algorithm was then used to mine the strong association rules among the risk factors within the 24Model, establishing the interaction mechanism among them. Based on the strong association rules, related hypotheses were proposed. Finally, the hierarchical and logical relationships of risk factors within the 24Model were analysed, and the causal and mediating effects were tested by path analysis. The safety management system has a direct effect on unsafe acts, unsafe conditions, habitual behaviour and organizational safety culture. Moreover, external influence has an effect on unsafe acts, organizational safety culture and habitual behaviour through the mediating effect of the safety management system. Based on the results obtained, this study proposes a series of specific measures to prevent risks in coal mines, providing a new perspective for the analysis and prevention of accidents.

Application of Earned Value Analysis Method and Earned Schedule Method to Time and Cost Control In Bank X Building Project

Construction projects are activities that must be completed within limited time and resources. This research aims to identify risky activities and make control efforts to reduce the level of hazard risk in the installation of steel box girder on the bridge. This research used a mixed methods approach, combining quantitative and qualitative methods. Data were collected through surveys and interviews with 60 respondents from 35 bridge projects. The results showed that there were 29 variables of work accident risk factors, including 3 variables with moderate risk levels, 24 variables with high risk levels, and 2 variables with extreme risk levels. The highest risk factors were mobilization that caused congestion and crane overturning during girder lifting that caused operators to fall. To reduce the risk level, efforts are made to ensure all work is done correctly, conduct regular safety inspections, and ensure an effective communication system in the installation of steel box girders on the bridge. The findings can serve as a basis for policy makers to develop better OHS regulations and guidelines, as well as provide valuable information for the development of more effective safety training programs for workers in the construction sector.

Tire wear monitoring using feature fusion and CatBoost classifier

Addressing the critical issue of tire wear is essential for enhancing vehicle safety, performance, and maintenance. Worn-out tires often lead to accidents, underscoring the need for effective monitoring systems. This study is vital for several reasons: safety, as worn tires increase the risk of accidents due to reduced traction and longer braking distances; performance, as uneven tire wear affects vehicle handling and fuel efficiency; maintenance costs, as early detection can prevent more severe damage to suspension and alignment systems; and regulatory compliance, as ensuring tire integrity helps meet safety regulations imposed by transportation authorities. In response, this study systematically evaluates tire conditions at 25%, 50%, 75%, and 100% wear, with an intact tire as a reference, using vibration signals as the primary data source. The analysis employs statistical, histogram, and autoregressive–moving-average (ARMA) feature extraction techniques, followed by feature selection to identify key parameters influencing tire wear. CatBoost is used for feature classification, leveraging its adaptability and efficiency in distinguishing varying wear patterns. Additionally, the study incorporates feature fusion to combine different types of features for a more comprehensive analysis. The proposed methodology not only offers a robust framework for accurately classifying tire wear levels but also holds significant potential for real-time implementation, contributing to proactive maintenance practices, prolonged tire lifespan, and overall vehicular safety.

Relationship between urban traffic crashes and temporal/meteorological conditions: understanding and predicting the effects

Urban traffic accidents pose significant challenges to public safety and transportation management. Previous studies have revealed that temporal and meteorological factors are the key contributors to accident rate. Besides the inconsistent observations or lack of exploration in some aspects such as snowfall, fog, wind and daily temperatures, it has been shown that these factors are essentially entangled. Furthermore, existing methodologies of analysis or prediction have been limited to relative risk or traditional models. Hence, this study is centered on understanding the detailed correlations between temporal and meteorological factors and accident rate of two types of crashes – moving vehicle and fixed-object crashes using the traffic accident data from Dalian. Further, by incorporating a diverse set of the features, a prediction model leveraging the random forest algorithm is proposed and proved effective in anticipating accident occurrences on the district level. The feature importance analysis has shown that time period and factors such as holiday, temperature and season are most important factors. The rate is higher on working days and in spring, and collisions of both types peak at 6–7 am. When the highest daily temperature is 27 °C and the lowest is 20 °C or -8 °C, the incidence is relatively higher. On the basis, the recommendations are aimed at optimizing transportation systems, mitigating accident risks, and enhancing public safety in urban environments.

Machine learning and multisource data analysis approach towards traffic accident risk prediction

Traffic accidents are continually a concern across the world bringing with them huge economic costs and high rates of fatality and injuries each single year. Predictive modeling can lessen such risks if the accident hotspots and timing can easily be ascertained. This study collects various data including historical accident reports, water and meteorological conditions, road characteristics, and telematics data, to form traffic accident risk predictive models. To construct and analyze these predictive models, we use various machine learning techniques such as logistic regression, decision trees, and ensemble methods (Random Forest and Gradient Boosting). The results bear out as efficient and effective, ensemble models are streets ahead than regression-based techniques with Gradient Boosting achieving AUC-ROC scores of up to 0.89. The results of this research can also assist in applying effective safety measures in a more cost-effective manner as well as facilitate the development of efficient transport management systems and policies.

A case study of the subjective workload of forest equipment operators in South Carolina

ABSTRACT Logging operations in the Southern United States have become more mechanized over time. However, extensive use of complex and heavy forest machineries for long durations increases operator workload, especially the cognitive demand. Working under demanding conditions can decrease the health of forest equipment operators over time, reducing productivity and increasing the risk of accidents. This study provides an initial assessment of the workload of logging equipment operators during timber harvesting operations using conventional wheeled feller-buncher, grapple skidder, and knuckle-boom loader harvesting systems by assessing the subjective workload of the logging equipment operators in South Carolina. In addition, we observed the heart rate of equipment operators to study the activities causing excessive physical and mental workload. Logging equipment operators self-evaluated their workload using the NASA Task Load Index, a subjective measure of workload. Results show no significant difference in the overall workload of equipment operators working at clearcut and thinning sites. The workload dimensions of Effort and Frustration contributed the most to the overall workload, while Performance had the least contribution. Sudden heart rate spikes occurred when operators conducted physical activities such as clearing debris from a felling head but were otherwise unobserved.

Application of Safety Procedure As Efforts To Prevent Work Accidents In MT. Serang Jaya Engine Room

Safety Procedure is a formal written safety procedure and contains procedures, identification and obligations to carry it out while working. Not optimal due to lack of understanding of Safety Procedures that pose a risk of work accidents. This study aims to determine the causes and impacts of the non-optimal implementation of Safety Procedures and efforts so that the Safety Procedure can run optimally so as to prevent work accidents in the engine room. The research method used in this study is a qualitative method with a descriptive pattern. Research data sources are obtained from primary and secondary data. Data collection techniques through observation, literature study, interviews and documentation during the time researchers carried out marine practices on the MT ship. Serang Jaya. The data analysis techniques used are by collecting data, reducing data, presenting data and drawing conclusions or verifying data which is also supported by fishbone analysis. Testing the validity of data using the tringulation method. The results stated that the factors of not optimal Safety Procedure due to lack of crew understanding of Safety Procedure, and crew concern for safety as well as lack of supervision and coordination between crew and management are the reasons why Safety Procedure cannot run optimally. The impact of not optimal Safety Procedure is the high risk of work accidents, hampering ship operations, harming the ship or the parties concerned. Efforts that can be made to optimize this are by carrying out Safety meeting activities, Toolbox Meeting, Drill, installing Safety Signs. And always provide counseling related to Safety Procedure in the engine room.

Construction Project Performance Based on Occupational Safety, Occupational Health and Work Motivation

Many construction organizations still employ workers without regard to the application of accident risk, although a focus on safety is predicted to improve worker performance. This study aims to examine the effect of occupational safety and health and incentive factors on worker performance in housing construction projects. This study used a quantitative approach and was tested using the SEM-PLS method with a sample of 72 respondents. The results showed that well-implemented occupational safety and health significantly improved worker performance, by reducing the risk of injury and improving worker welfare. In addition, high work motivation plays a role in increasing project productivity and efficiency. Emphasis on safety, health, and work motivation was shown to have a positive impact on achieving better project performance. The implications of this research provide important insights for construction managers and policy makers in optimizing project success through the implementation of effective safety protocols, wellness programs, and appropriate motivation strategies. Thus, this study highlights the importance of integrating occupational safety and motivation as key factors in achieving superior project performance.

Design System of Solar-Powered Safety Lamp Integrated Proximity Sensor as a Solution for Accident Prevention at Blind Spot Areas

The curved contour of the road creates blind spots which increase the risk of traffic accidents. Throughout 2019, there were 107,500 accident cases recorded in Indonesia. Therefore, efforts are needed to provide road infrastructure that supports driving safety, such as traffic signs to reduce the risk of accidents in blind spot areas. This research aims to design a smart safety light warning system that is integrated with solar-based street lighting. The design uses a design-based research approach referring to several established standards including Indonesia National Standard (SNI) 7931: 2008, SNI IEC 60529:2014, Regulation of the Minister of Transportation of the Republic of Indonesia Number PM 13 of 2014, Manual on Uniform Traffic Control Devices (MUTCD) issued by the Federal Highway Administration (FHWA) of the United States Department of Transportation (USDOT), and Article 115 of Minister of Transportation Republic of Indonesia Regulation PM 27 of 2018. This study used Design-Based Research (DBR) as a research methodology. The result of this study is a prototype design and development of smart safety light warning system which can be optimized. Validation of the design and circuit is conducted using prototyping modeling 1:20 from the original dimensions to measure the function and performance of the circuit. The prototype is capable of turning on warning lights and siren notifications when detecting objects with a maximum distance of 350 cm as measured by the HC – SR04 sensor. Charging the stored solar panels via the accumulator allows the technology to continue working for 45 hours without charging. For power efficiency purposes, the technology is equipped with an LDR (Light Dependent Resistor) sensor with a minimum limit of 341-lux which regulates the lighting. The development of these safety lights will increase driver awareness when passing through blind spot areas and have positive implications for reducing the number of accidents in Indonesia.

Development of environmentally friendly sensor devices to monitor humidity

Manufacturing environmentally friendly electronic components is a major challenge for traditional microelectronics companies. Some factors make the industry polluting and pose a high risk of accidents since they employ the use of chemical or radioactive products during complex manufacturing processes and discard at end of useful life. Electronic waste, in addition to being an environmental problem, becomes logistically expensive to reuse. Thus, the development of new technologies focusing on the manufacture of green or ecological components, waste reduction, simple and correct disposal are instruments of study and increasing use. In this work, we present a proposal for a humidity sensor using paper and graphite. Paper is a biodegradable material and can be used in sensors, although its processing is complex. The sensors developed use simple manufacturing techniques and are biodegradable. We verified the functioning of humidity sensors through mathematical-experimental tests showing the sensitivity of the devices using a micro controlled system.

Adaptive sensor attack detection and defense framework for autonomous vehicles based on density

The security of autonomous vehicles heavily depends on localization systems that integrate multiple sensors, which are vulnerable to sensor attacks and increase the risk of accidents. Given the diversity of sensor attacks and the dynamic changing of driving scenarios of autonomous vehicles, an adaptive and effective attack detection and defense framework faces a considerable challenge. This paper proposes a novel real-time adaptive attack detection and defense framework based on density, which can detect and identify attacked sensors and effectively recover data. We first develop a reinforcement learning multi-armed Bandit-based Density-Based Spatial Clustering of Applications with Noise (BDBSCAN) algorithm that selects hyperparameters adaptively. The Adaptive Extended Kalman Filter (AEKF) combines with the vehicle dynamic model on the localization system and extracts data features used for the BDBSCAN algorithm to monitor potential sensor attacks. If attack detection indicates possible system compromise, AEKF is further employed on localization sensors with anomalies identified through the BDBSCAN algorithm of the attacked sensors. To ensure precision and reliability, the data recovery incorporates a redundancy mechanism to apply a decision tree to select the optimal state estimation between AEKF and Extended Kalman Filter (EKF) to replace corrupted sensor data. To evaluate the effectiveness and adaptability of the proposed framework, we conducted 15,000 experiments using the real-world KITTI and V2V4Real datasets across various driving and sensor attack scenarios. The results demonstrate that our proposed framework achieves 100% accuracy and 0% false alarm rate in various driving scenarios for attack detection within 0.15 s, with a recovery time of 0.08 s.

Design of Gas Leakage Monitoring System Based on Android Application and NodeMCU ESP8266

Gas leakage is a serious problem that can threaten public safety and health and cause significant material losses. This research aims to design and implement a gas leak monitoring system that can be accessed remotely based on Android applications and NodeMCU ESP8266. NodeMCU ESP8266 is chosen as the main microcontroller equipped with an MQ-2 gas sensor to detect the presence of hazardous gas. This research incorporates Internet of Things (IoT) technology to allow users to remotely monitor the condition of gas leaks, thereby increasing the level of safety in the use of gas in households or small industries. The hardware design includes the use of an MQ-2 gas sensor that is sensitive to certain gas concentrations, as well as setting up an ESP8266 NodeMCU to transmit detection data to a Firebase server for later access through an Android application. The Android application was developed using Android Studio with a focus on an intuitive user interface to monitor the status of gas leaks in real-time. he research methods used include system design, hardware and software implementation, and thorough system testing by simulating gas leak scenarios to test the reliability and response of the system. The results show that the system can detect gas leaks with high accuracy. It is expected that the system developed in this research can be a practical and effective solution in reducing the risk of accidents caused by gas leaks, as well as making a positive contribution in increasing awareness of the safety of gas use in the community.

Validating risk behavior in driving simulation using naturalistic driving data

The absence of physical accident risk in driving simulation, which allows for safely studying critical driving situations, also reduces the driver's risk perception, which may result in unrealistic driver behavior. Validation studies in this context are rare for ethical reasons, making it difficult to assess the extent of this issue at present. The present study addresses this gap by utilizing naturalistic driving data. Four critical cut-in situations on German highways were extracted from naturalistic data and replicated in a driving simulator study with N = 58 participants. Both in-situ self-ratings on subjective criticality and post-hoc video-based ratings (from the driver and objective observers), as well as presence ratings, were collected to supplement driver behavior. Although driver reactions in the simulator and the field were not equivalent in absolute terms, drivers in both the simulation and the real world exhibited accident-avoidance behavior through braking reactions, indicating relative validity. No clear mediating role of the sense of presence towards a more careful driver behavior was found. This work shows that drivers exhibit accident-avoiding behavior in the simulator and tend to react to hazards in the simulator similarly as they would in a real situation, while absolute numerical values should only be interpreted with caution.

Evaluation of Selected Factors Affecting the Speed of Drivers at Signal-Controlled Intersections in Poland

In traffic engineering, vehicle speed is a critical determinant of both the risk and severity of road crashes, a fact that holds particularly important for signalized intersections. Accurately selecting vehicle speeds is crucial not only for minimizing accident risks but also for ensuring the proper calculation of intergreen times, which directly influences the efficiency and safety of traffic flow. Traditionally, the design of signal programs relies on fixed speed parameters, such as the posted speed limit or the operational speed, typically represented by the 85th percentile speed from speed distribution data. Furthermore, many design guidelines allow for the selection of these critical speed values based on the designer’s own experience. However, such practices may lead to discrepancies in intergreen time calculations, potentially compromising safety and efficiency at intersections. Our research underscores the substantial variability in the speeds of passenger vehicles traveling intersections under free-flow conditions. This study encompassed numerous intersections with the highest number of accidents, using unmanned aerial vehicles to conduct surveys in three Polish cities: Toruń, Bydgoszcz, and Warsaw. The captured video footage of vehicle movements at predetermined measurement sections was analyzed to find appropriate speeds for various travel maneuvers through these sections, encompassing straight-through, left-turn, and right-turn relations. Our analysis focused on how specific infrastructure-related factors influence driver behavior. The following were evaluated: intersection type, traffic organization, approach lane width, number of lanes, longitudinal road gradient, trams or pedestrian or bicycle crossing presence, and even roadside obstacles such as buildings, barriers or trees, and others. The results reveal that these factors significantly affect drivers’ speed choices, particularly in turning maneuvers. Furthermore, it was observed that the average speeds chosen by drivers at signalized intersections did not reach the permissible speed limit of 50 km/h as established in typical Polish urban areas. A key outcome of our analysis is the recommendation for a more precise speed model that contributes to the design of signal programs, enhancing road safety, and aligning with sustainable transport development policies. Based on our statistical analyses, we propose adopting a more sophisticated model to determine actual vehicle speeds more accurately. It was proved that, using the developed model, the results of calculating the intergreen times are statistically significantly higher. This recommendation is particularly pertinent to the design of signal programs. Furthermore, by improving speed accuracy values in intergreen calculation models with a clear impact on increasing road safety, we anticipate reductions in operational costs for the transportation system, which will contribute to both economic and environmental goals.

Application of 360 Camera Technology and Excavator Operator Workload at a Nickel Ore Mine and Its Implication for Work Accident Rates Using the Nasa-TLX Method

Indonesia, as one of the largest nickel producers in the world, has around 90% of nickel reserves spread across various regions, such as Central Sulawesi, South Sulawesi, Southeast Sulawesi, and North Maluku. Even though demand for nickel continues to increase, a severe problem that needs attention is the rate of work accidents in mining fields. Most heavy equipment accidents that occur are caused by operator negligence while operating. This negligence can occur when operators are in a hurry, make mistakes while using heavy equipment, or do not have proper work time management. This research aims to analyze the impact of 360-degree camera technology on excavator operators in nickel ore mines on work accident rates and operator workload. The case study was carried out at PT Rifky and Raisha Anursyah using the NASA-TLX method to measure workload. In contrast, the number of accidents that occurred to each operator within one month was used to measure work accidents. The 360 camera technology provides a comprehensive view of the work environment, allowing operators to monitor the surrounding area better and reduce blind spots. The research results show that applying this technology can reduce the risk of work accidents and increase the work efficiency of excavator operators. With better monitoring, operators can identify potential hazards earlier and reduce the risk of accidents. Workload evaluation using NASA-TLX shows a decrease in operator workload after implementing 360 camera technology. This research provides strategic recommendations for workload management and implementing safety technology in the mining industry.

Road section traffic risk propagation model based on macro traffic flow energy consumption

Traffic risk is an important source of road traffic accidents. Effectively predicting the propagation of accident risks on the road after an accident is of great significance for preventing secondary accidents. Therefore, this paper establishes a road section accident risk propagation model based on macro traffic flow energy consumption. Firstly, the influence of lane occupation and vehicle lane changing after the accident on traffic flow is analyzed, and a macro traffic flow model under the risk after the accident is constructed. Secondly, combined with the definition of traffic flow energy dissipation, the movement of the whole vehicle is abstracted as a fluid movement process, and a traffic flow energy consumption model under the risk after the accident is proposed to quantify the accident risk. Finally, according to the spatiotemporal correlation of risk propagation, a risk impact range and duration calculation model is proposed to describe the risk propagation process. In order to verify the effectiveness of the risk propagation model proposed in this paper, MATLAB and VISSIM are used to carry out numerical simulation and simulation verification of traffic flow operation under different initial traffic flow densities. The experimental results show that the greater the initial density of the road section when the accident occurs, the wider the risk impact range and the longer the duration. The absolute value of the prediction deviation rate of the proposed model is below 8%, which has a good prediction effect.

The Establishment of Economic Dirigism In Maritime Trade of Turkey, 1923–1950

ABSTRACT In the aftermath of the establishment of the republican regime in Turkey in 1923, the policy of economic dirigisme began to dominate the markets step by step. This article aims to analyse the effects of economic dirigisme on maritime trade for a quarter of a century and furnishes an illustrative case delineating how the government’s favoured economic policy attenuated the developmental prospects of maritime commerce. Throughout this temporal span, endeavours advocating a laissez-faire market policy found themselves systematically marginalized, as the juggernaut of economic dirigisme unfolded. The corollary of this policy was a precipitous decline in the operational efficiency of maritime trade. The proclivity for deploying antiquated ships escalated the inherent risks of maritime accidents. Legislative initiatives, exemplified by the promulgation of cabotage laws and the imposition of onerous taxes, erected formidable impediments that curtailed the operability of foreign-flagged vessels in Turkish ports. Concurrently, the waning trade potential cast a pall over the developmental trajectory of Anatolian cities.

Role of the Regulation Framework in Occupational Safety in Construction Excavation Works—A Survey Analysis in Turkey

The construction sector is known to have the highest risks of occupational accidents. A rationale for this high occurrence of occupational risks can be related to legislative requirements to enforce safe construction practices within this sector. Within the context of excavation works in Turkey, this study investigates the leading risks for any compliance shortfalls and ultimately presents recommendations to mitigate occupational accidents’ occurrences during excavation works in the construction sector. Based on a quantitative methodology, a closed-ended survey consisting of 35 questions and based on legislative requirements was applied to project managers in the construction industry, such as site supervisors, occupational safety experts, auditors, and control personnel. A sample size of 277 responses was found to have stability and validity through a reliability analysis and an exploratory factor analysis, and was used for testing statistical significance via cross-tabulation analysis and chi-square tests. The findings revealed that the major deviation of safety in excavation works from legislative requirements is executing works during adverse weather conditions. Moreover, it was also noteworthy that protective curtains did not surround the excavation sites, and most of the employees encountered ground slippage during excavation work. Therefore, the findings revealed preliminary research that will contribute positively to providing incentives for a focus on and development of relevant security and technical measures. It also provided information to protect the safety and welfare of the workers involved in excavation works. Finally, though these findings may be considered context-specific, this research can be used for comparative purposes for similar studies into the safety practices of excavation works in different countries, where generalized findings can be later derived to inform academia and practice.

A study of the relation between traffic accidents and election posters

Inattention in traffic is a risk factor for the occurrence of accidents. Elements surrounding traffic could potentially be a safety risk for road users. This study investigates the relation between election posters and traffic accidents using a seasonal autoregressive-moving-average model with exogeneous variables (seasonal ARMAX) correcting for variations in meteorological conditions and general traffic volume indicated through public holidays. Danish traffic accident micro data are used to construct a time series for daily number of accidents in city zones adjusted for probable known accident causes, namely drunk driving, narcotics, drivers deemed unfit to drive, and accidents related to low visibility. Model parameters are determined from Maximum Likelihood estimation on the period from 1 January 1997 to 15 December 2009 with an indicator for general election periods. The presence of general election posters is associated with an increased risk of traffic accidents (p = 0.003), when correcting for meteorological variables and public school holidays. While a causal relation between traffic accidents and the presence of election posters cannot be concluded from the analysis, we find distraction from election posters to be the most likely explanation for the associated increase in traffic accidents. On average, the model indicates that 1.18 additional daily accidents occur for general elections in Denmark. In total, that amounts to 127 additional accidents for the investigated period of time. This study shows that such sudden changes in traffic surroundings are significantly related to increased safety risks which could lead to a better discussion of relevant traffic legislation.

Ефективність застосування світлофорів та їх роль у забезпеченні безпеки дорожнього руху

Introduction. The development of motor transport inevitably leads to an increase in traffic intensity, resulting in challenges related to ensuring the safety and comfort of road users, particularly at uncontrolled intersections and pedestrian crossings, which are areas of heightened risk for road accidents. Problem statement. The high likelihood of traffic accidents occurring at uncontrolled road intersections and pedestrian crossings necessitates the implementation of measures aimed at ensuring the safety of all road users, particularly pedestrians and cyclists. Purpose. Ensuring road safety, reducing the likelihood of traffic accidents, and providing comfortable travel conditions for road users. Materials and methods. The current regulatory acts and normative documents regarding traffic control devices, particularly traffic lights, as well as statistical information on road accidents in Ukraine, have been analyzed.