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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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23 pages, 1148 KB  
Article
Physical Security Auditing for Utilities: A Guide to Resilient Substation
by Nawaraj Kumar Mahato, Jiaxuan Yang, Junfeng Yang, Gangjun Gong and Jianhong Hao
Safety 2024, 10(3), 80; https://doi.org/10.3390/safety10030080 - 13 Sep 2024
Cited by 4 | Viewed by 3623
Abstract
Electric power substations, as critical components of modern power grids, are increasingly becoming targets for intentional physical attacks, including vandalism, theft, and sabotage. These threats, coupled with the potential for cyber-attacks and the weaponization of technologies, necessitate robust security measures and comprehensive auditing [...] Read more.
Electric power substations, as critical components of modern power grids, are increasingly becoming targets for intentional physical attacks, including vandalism, theft, and sabotage. These threats, coupled with the potential for cyber-attacks and the weaponization of technologies, necessitate robust security measures and comprehensive auditing practices. Despite utilities providers’ focus on understanding grid vulnerability and implementing physical security upgrades, there is a recognized gap in evaluating the effectiveness and long-term usability of these measures. This paper addresses the need for regular security audits to identify vulnerabilities and ensure the overall resilience of substations against evolving threats. The rationale behind this study is to propose a conventional auditing method that includes an auditing framework, checklists, inspections, and post-inspection suggestions. Through the systematic identification and addressing of vulnerabilities via security auditing, the framework aims to significantly enhance the resilience of substations against physical threats. This paper provides a comprehensive guideline for the physical security auditing procedure, which is essential for the reliable operation of the power grid. Full article
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18 pages, 312 KB  
Review
Digital and Virtual Technologies for Work-Related Biomechanical Risk Assessment: A Scoping Review
by Paulo C. Anacleto Filho, Ana Colim, Cristiano Jesus, Sérgio Ivan Lopes and Paula Carneiro
Safety 2024, 10(3), 79; https://doi.org/10.3390/safety10030079 - 12 Sep 2024
Cited by 7 | Viewed by 3430
Abstract
The field of ergonomics has been significantly shaped by the advent of evolving technologies linked to new industrial paradigms, often referred to as Industry 4.0 (I4.0) and, more recently, Industry 5.0 (I5.0). Consequently, several studies have reviewed the integration of advanced technologies for [...] Read more.
The field of ergonomics has been significantly shaped by the advent of evolving technologies linked to new industrial paradigms, often referred to as Industry 4.0 (I4.0) and, more recently, Industry 5.0 (I5.0). Consequently, several studies have reviewed the integration of advanced technologies for improved ergonomics in different industry sectors. However, studies often evaluate specific technologies, such as extended reality (XR), wearables, artificial intelligence (AI), and collaborative robot (cobot), and their advantages and problems. In this sense, there is a lack of research exploring the state of the art of I4.0 and I5.0 virtual and digital technologies in evaluating work-related biomechanical risks. Addressing this research gap, this study presents a comprehensive review of 24 commercial tools and 10 academic studies focusing on work-related biomechanical risk assessment using digital and virtual technologies. The analysis reveals that AI and digital human modelling (DHM) are the most commonly utilised technologies in commercial tools, followed by motion capture (MoCap) and virtual reality (VR). Discrepancies were found between commercial tools and academic studies. However, the study acknowledges limitations, including potential biases in sample selection and search methodology. Future research directions include enhancing transparency in commercial tool validation processes, examining the broader impact of emerging technologies on ergonomics, and considering human-centred design principles in technology integration. These findings contribute to a deeper understanding of the evolving landscape of biomechanical risk assessment. Full article
(This article belongs to the Special Issue Advances in Ergonomics and Safety)
12 pages, 1231 KB  
Article
Is Declined Cognitive Function Predictive for Fatal Accidents Involving Aging Pilots?
by Douglas D. Boyd and Alan J. Stolzer
Safety 2024, 10(3), 71; https://doi.org/10.3390/safety10030071 - 5 Aug 2024
Cited by 2 | Viewed by 2522
Abstract
Background. Civil aviation comprises airlines/charters and general aviation (GA). Currently, airlines are experiencing a pilot shortage, partly reflecting scheduled retirements mandatory for airline (but not GA) pilots aged 65 years, fueling a debate as to whether the retirement age should be increased. Herein, [...] Read more.
Background. Civil aviation comprises airlines/charters and general aviation (GA). Currently, airlines are experiencing a pilot shortage, partly reflecting scheduled retirements mandatory for airline (but not GA) pilots aged 65 years, fueling a debate as to whether the retirement age should be increased. Herein, using 16–40 years-of-age aviators as a reference, we determined whether GA pilots aged 60+ years (i) incurred an elevated accident rate, employing, for the first time, age-tiered flight time as a measure of risk exposure and (ii) carried an excess risk for cognitive deficiency-related fatal accidents. Methods. Airplane accidents (2002–2016) involving Class 3 medical certificated pilots were per the National Transportation Safety Board (NTSB) databases. Age-tiered pilot risk exposure represented a summation of flight hours per Class 3 medical applications. Cognitive decline measures were per NTSB field codes. Statistical analyses employed Chi-Square, Mann–Whitney, logistic regression, and binomial tests. Results. Using flight hours as the denominator, the fatal accident rate for older pilots (41–80 years) was unchanged compared with aviators aged 16–40 years. In the logistic regression, no cognitive deficiency measure was predictive (p = 0.11, p = 0.15) for pilots aged 61+ years who were involved in fatal accidents. Conclusion. These findings question the necessity of an automatic disqualification of air transport pilots at 65 years of age. Full article
(This article belongs to the Special Issue Aviation Safety—Accident Investigation, Analysis and Prevention)
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18 pages, 23855 KB  
Article
Risk Analysis of Underground Tunnel Construction with Tunnel Boring Machine by Using Fault Tree Analysis and Fuzzy Analytic Hierarchy Process
by Nitidetch Koohathongsumrit and Wasana Chankham
Safety 2024, 10(3), 68; https://doi.org/10.3390/safety10030068 - 1 Aug 2024
Cited by 7 | Viewed by 3668
Abstract
Tunnel boring machines (TBMs) are preferred for constructing tunnels, particularly for underground mass transit railways, because of their speed, minimal environmental impact, and increased safety. However, TBM tunneling involves unavoidable risks, necessitating careful assessment and management for successful project completion. This study presents [...] Read more.
Tunnel boring machines (TBMs) are preferred for constructing tunnels, particularly for underground mass transit railways, because of their speed, minimal environmental impact, and increased safety. However, TBM tunneling involves unavoidable risks, necessitating careful assessment and management for successful project completion. This study presents a novel hybrid risk-analysis method for tunnel construction using TBMs. The proposed method integrates fault tree analysis (FTA) and the fuzzy analytic hierarchy process (fuzzy AHP). FTA was employed to calculate the probabilities of risk occurrences, while fuzzy AHP was utilized to determine the consequences of the risks. These probability and consequence values were used to calculate continuous risk levels for more accurate risk analysis. The proposed method was applied to a real case of metro line construction. The results demonstrated that the proposed method effectively analyzes the risks, accurately reflecting decision support data. The risks were categorized based on the continuous risk levels in descending order. The most significant risk was the deterioration of the TBM. The benefits of this study provide project managers and stakeholders involved in underground construction with a new risk-analysis method that enhances work safety and facilitates the timely execution of urban tunnel construction projects. Full article
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33 pages, 1485 KB  
Review
Occupational Chemical Exposure and Health Status of Wildland Firefighters at the Firefront: A Systematic Review
by Tatiana Teixeira, Liliana Almeida, Isabel Dias, João Santos Baptista, Joana Santos, Mário Vaz and Joana Guedes
Safety 2024, 10(3), 60; https://doi.org/10.3390/safety10030060 - 5 Jul 2024
Cited by 3 | Viewed by 3406
Abstract
Wildland firefighting represents a physically and mentally demanding endeavour fraught with various risk factors. The primary aim of this study is to delineate occupational chemical exposure within the firefighting work environment on the firefront and its implications for firefighters’ health status. A systematic [...] Read more.
Wildland firefighting represents a physically and mentally demanding endeavour fraught with various risk factors. The primary aim of this study is to delineate occupational chemical exposure within the firefighting work environment on the firefront and its implications for firefighters’ health status. A systematic literature review was conducted utilising diverse keyword combinations across Scopus, Web of Science, Academic Search Complete, and ScienceDirect databases. Only English-language journal articles, real-world monitoring reports, and studies featuring samples of firefighters were considered for inclusion. Forty-one studies were analysed, with 26 focusing on firefighters’ occupational exposure to chemical agents during wildland firefighting and 15 addressing the health impairments of wildland firefighting activities. Polycyclic aromatic hydrocarbons (PAHs), VOCs, and particulates emerged as the most prevalent chemical agents in the exposure profiles of frontline firefighters. They were shown to be the main incidents of cardiovascular disease, respiratory disease, and work-related cancer. The rigorous demands of wildland firefighting have been demonstrated to significantly impact firefighter health, resulting in a notable prevalence of fatalities and illnesses. Given that an elevated number of health issues are common in this occupation, adopting advanced assessment technologies is imperative. Full article
(This article belongs to the Topic New Research in Work-Related Diseases, Safety and Health)
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22 pages, 295 KB  
Article
“Emergency Decisions”: The Choice of a Simulated Emergency Scenario to Reproduce a Decision-Making Condition in an Emergency Context as Close to Reality as Possible
by Ivan D’Alessio
Safety 2024, 10(2), 54; https://doi.org/10.3390/safety10020054 - 20 Jun 2024
Cited by 3 | Viewed by 1822
Abstract
Decisions are a crucial aspect of human life, especially when made in emergency contexts. This research involved 348 subjects, evaluating the relationship between socio-demographic variables and the choice of one of the proposed emergency scenarios suitable for reproducing a decision-making condition in an [...] Read more.
Decisions are a crucial aspect of human life, especially when made in emergency contexts. This research involved 348 subjects, evaluating the relationship between socio-demographic variables and the choice of one of the proposed emergency scenarios suitable for reproducing a decision-making condition in an emergency. Three scenarios were presented: one on climate change, one on pandemics, and one on seismic events. The survey captured individuals’ perceptions of the scenarios for dimensions such as realism (present, past, and future), emotions, risk, worry, emergency, catastrophe, immediate choice, and immediate decision. The results suggest that age, gender, education, and previous experience are predictive factors for subjects’ preferences regarding the chosen scenario and their evaluation of the related dimensions. To optimize decisions in emergencies by institutional decision makers and crisis managers, it is useful to expand knowledge and have data relevant to this area. This research provides a basis in terms of data and tools for designing future research and studies on decision making in emergency contexts. Full article
14 pages, 1129 KB  
Article
Evolution of Occupational Safety and Health Disclosure Practices: Insights from 8 Years in Taiwan’s Construction Industry
by Chieh-Wen Chang, Tomohisa Nagata, Louise E. Anthony and Ro-Ting Lin
Safety 2024, 10(2), 46; https://doi.org/10.3390/safety10020046 - 13 May 2024
Cited by 2 | Viewed by 2849
Abstract
The construction industry has been identified as a major contributor to occupational accidents that can lead to fatalities. As a result, this study aims to evaluate the effectiveness of new safety and health regulations and revised guidelines in improving safety and health disclosures [...] Read more.
The construction industry has been identified as a major contributor to occupational accidents that can lead to fatalities. As a result, this study aims to evaluate the effectiveness of new safety and health regulations and revised guidelines in improving safety and health disclosures and performance within the construction industry. We retrieved safety and health disclosure reports from 25 Taiwanese construction companies between 2013 and 2020 using the Market Observation Post System website. We analyzed the data using the Kaplan–Meier method to assess the timing of disclosures and differences between larger (≥300 employees) and smaller (<300 employees) companies. We found that construction companies reported safety indicators more promptly than health indicators and that larger companies disclosed earlier compared to smaller ones. Only 45% of companies provide detailed reviews and preventative measures in their sustainability reports despite 64% disclosing occupational accidents. We found that from 2013 to 2020, more companies improved their occupational safety and health (OSH) reporting. This improvement coincided significantly with the adoption of international standards and Taiwan’s government regulations. In summary, the study found that larger companies were more likely to disclose OSH data compared to smaller ones. This suggests that company size and available resources could have an impact on reporting practices. While some progress was made, companies still struggle to provide detailed reports on major accidents, balancing transparency with competitiveness. Full article
(This article belongs to the Topic Building a Sustainable Construction Workforce)
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24 pages, 1775 KB  
Article
Analysis of Hydrogen Value Chain Events: Implications for Hydrogen Refueling Stations’ Safety
by Eulàlia Badia, Joaquín Navajas, Roser Sala, Nicola Paltrinieri and Hitomi Sato
Safety 2024, 10(2), 44; https://doi.org/10.3390/safety10020044 - 30 Apr 2024
Cited by 4 | Viewed by 2219
Abstract
Renewable hydrogen is emerging as the key to a sustainable energy transition with multiple applications and uses. In the field of transport, in addition to fuel cell vehicles, it is necessary to develop an extensive network of hydrogen refueling stations (hereafter HRSs). The [...] Read more.
Renewable hydrogen is emerging as the key to a sustainable energy transition with multiple applications and uses. In the field of transport, in addition to fuel cell vehicles, it is necessary to develop an extensive network of hydrogen refueling stations (hereafter HRSs). The characteristics and properties of hydrogen make ensuring the safe operation of these facilities a crucial element for their successful deployment and implementation. This paper shows the outcomes of an analysis of hydrogen incidents and accidents considering their potential application to HRSs. For this purpose, the HIAD 2.0 was reviewed and a total of 224 events that could be repeated in any of the major industrial processes related to hydrogen refueling stations were analyzed. This analysis was carried out using a mixed methodology of quantitative and qualitative techniques, considering the following hydrogen value chain: production, storage, delivery and industrial use. The results provide general information segmented by event frequency, damage classes and failure typology. The analysis shows the main processes of the value chain allow the identification of key aspects for the safety management of refueling facilities. Full article
(This article belongs to the Special Issue Worldwide Accidents: Trends, Investigation and Prevention)
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13 pages, 1576 KB  
Article
Assessment of Fire Safety Management for Special Needs Schools in South Africa
by Tlou D. Raphela and Ndivhuwo Ndaba
Safety 2024, 10(2), 43; https://doi.org/10.3390/safety10020043 - 30 Apr 2024
Cited by 3 | Viewed by 2564
Abstract
The safety and well-being of learners with special educational needs in South Africa remain a paramount concern, significantly impacting their constitutional rights and dignity. Despite legislative commitments aimed at fostering inclusive education, a pervasive absence of adequate fire safety measures in special needs [...] Read more.
The safety and well-being of learners with special educational needs in South Africa remain a paramount concern, significantly impacting their constitutional rights and dignity. Despite legislative commitments aimed at fostering inclusive education, a pervasive absence of adequate fire safety measures in special needs schools (SNSs) in South Africa has persisted, leading to the vulnerability of these learners. Tragic incidents, such as fatal fires in these schools, as reported in the literature, underscore the urgent need for immediate intervention to ensure the safety and security of these learners, especially with regards to fire hazards. This study, conducted within the Northwest Province of South Africa, assessed the state of fire safety management in SNSs by applying a series of chi-squared (χ2) tests of independence for categorical variables, descriptive statistics, and regression analysis using the Statistical Package for Social Scientists (SPSS), Version 20 and found that limited access to power is the potential root cause of fires in these schools; also, the limited amount of fire safety initiatives was a problem. In addition, the ordinal regression showed a statistically significant relationship when the question of to what extent the learners in the sampled schools are involved in fire safety programs was regressed with the questions of whether management and stakeholders were involved in fire safety programs and also on taking part in the physical fire safety programs (χ2 = 47.412; df = 2; p < 0.001; R2 = 70.5%). Furthermore, fire safety management was not sufficiently implemented in the sampled schools and the safety legislations of the country were not implemented accordingly when it came to fire safety. This study identified root causes of fire risks, gauged stakeholders’ awareness and involvement in fire safety management, and advocated for more stringent safety policies and practices within the SNS based on the above findings. Full article
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9 pages, 415 KB  
Article
Monitoring Occupational Radiation Dose in Radiography Students: Implications for Safety and Training
by Mohamed Abuzaid, Zarmeena Noorajan, Wiam Elshami and Manal Ibham
Safety 2024, 10(2), 35; https://doi.org/10.3390/safety10020035 - 4 Apr 2024
Cited by 4 | Viewed by 5066
Abstract
Background: This study aimed to investigate the occupational exposure of undergraduate radiography students to ionising radiation and evaluate the effectiveness of safety protocols and training in reducing radiation exposure. Methods: This study tracked undergraduate radiography students from the University of Sharjah, UAE, using [...] Read more.
Background: This study aimed to investigate the occupational exposure of undergraduate radiography students to ionising radiation and evaluate the effectiveness of safety protocols and training in reducing radiation exposure. Methods: This study tracked undergraduate radiography students from the University of Sharjah, UAE, using thermoluminescent dosimeters (TLDs) from 2015 to 2023. TLD readings were conducted every 15 weeks during 384 h of clinical placement. This study encompassed various radiographic procedures, and the TLDs were used to measure shallow (HP (0.07)) and deep doses (HP (10)). Results: A data analysis from 599 dosimeters revealed an average of 74 students annually. The average effective doses for HP (10) and HP (0.07) were 0.227 mSv and 0.222 mSv, respectively. These doses were well-below the recommended annual limits. Conclusion: This study’s results indicated that radiography students’ occupational radiation exposure during clinical training was within the safe limits, demonstrating the effectiveness of training and safety protocols. A comparison with international data corroborated the low exposure levels. Clinical training is essential for radiography students, and this study highlights the success of safety protocols in minimising occupational radiation exposure. Continuous monitoring and education are crucial to sustaining these positive outcomes. Full article
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14 pages, 3796 KB  
Article
A Comparative Approach Study on the Thermal and Calorimetric Analysis of Fire-Extinguishing Powders
by An-Chi Huang, Fang-Chao Cao and Xin-Yue Ma
Safety 2024, 10(1), 31; https://doi.org/10.3390/safety10010031 - 15 Mar 2024
Cited by 8 | Viewed by 2910
Abstract
This study offers a comprehensive evaluation of the effectiveness of expansible graphite (EG) and potassium bicarbonate (KHCO3) in suppressing metal fires, which are known for their high intensity and resistance. Our assessment, utilizing thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), [...] Read more.
This study offers a comprehensive evaluation of the effectiveness of expansible graphite (EG) and potassium bicarbonate (KHCO3) in suppressing metal fires, which are known for their high intensity and resistance. Our assessment, utilizing thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM), revealed that compositions of EG–KHCO3 can endure temperatures of up to 350 °C, indicating their thermal resilience. The 3:1 EG–KHCO3 mixture demonstrated exceptional performance in fire suppression tests by extinguishing sodium flames in a mere 20 s, using approximately 50 g of the agent. This highlights a substantial improvement in efficiency. In addition, FTIR analysis identified important gaseous compounds released during decomposition, while XRD and SEM techniques confirmed the advantageous insertion of KHCO3 into the EG matrix, enhancing its resistance to heat and chemical reactions. The mixture with a ratio of 3:1 also demonstrated a higher cooling rate of 2.34 °C/s within the temperature range of 350 to 200 °C. The results emphasize the potential of EG–KHCO3 compositions, specifically in a 3:1 ratio, for efficient fire management by integrating fire suppression, heat resistance, and quick cooling. Subsequent investigations will prioritize the evaluation of these compositions across different circumstances and the assessment of their environmental and industrial viability. Full article
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30 pages, 14699 KB  
Article
Deep Learning for Detection of Proper Utilization and Adequacy of Personal Protective Equipment in Manufacturing Teaching Laboratories
by Adinda Sekar Ludwika and Achmad Pratama Rifai
Safety 2024, 10(1), 26; https://doi.org/10.3390/safety10010026 - 7 Mar 2024
Cited by 11 | Viewed by 5172
Abstract
Occupational sectors are perennially challenged by the potential for workplace accidents, particularly in roles involving tools and machinery. A notable cause of such accidents is the inadequate use of Personal Protective Equipment (PPE), essential in preventing injuries and illnesses. This risk is not [...] Read more.
Occupational sectors are perennially challenged by the potential for workplace accidents, particularly in roles involving tools and machinery. A notable cause of such accidents is the inadequate use of Personal Protective Equipment (PPE), essential in preventing injuries and illnesses. This risk is not confined to workplaces alone but extends to educational settings with practical activities, like manufacturing teaching laboratories in universities. Current methods for monitoring and ensuring proper PPE usage especially in the laboratories are limited, lacking in real-time and accurate detection capabilities. This study addresses this gap by developing a visual-based, deep learning system specifically tailored for assessing PPE usage in manufacturing teaching laboratories. The method of choice for object detection in this study is You Only Look Once (YOLO) algorithms, encompassing YOLOv4, YOLOv5, and YOLOv6. YOLO processes images in a single pass through its architecture, in which its efficiency allows for real-time detection. The novel contribution of this study lies in its computer vision models, adept at not only detecting compliance but also assessing adequacy of PPE usage. The result indicates that the proposed computer vision models achieve high accuracy for detection of PPE usage compliance and adequacy with a mAP value of 0.757 and an F1-score of 0.744, obtained with the YOLOv5 model. The implementation of a deep learning system for PPE compliance in manufacturing teaching laboratories could markedly improve safety, preventing accidents and injuries through real-time compliance monitoring. Its effectiveness and adaptability could set a precedent for safety protocols in various educational settings, fostering a wider culture of safety and compliance. Full article
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24 pages, 4897 KB  
Article
Analyzing Pile-Up Crash Severity: Insights from Real-Time Traffic and Environmental Factors Using Ensemble Machine Learning and Shapley Additive Explanations Method
by Seyed Alireza Samerei, Kayvan Aghabayk and Alfonso Montella
Safety 2024, 10(1), 22; https://doi.org/10.3390/safety10010022 - 23 Feb 2024
Cited by 8 | Viewed by 3704
Abstract
Pile-up (PU) crashes, which involve multiple collisions between more than two vehicles within a brief timeframe, carry substantial consequences, including fatalities and significant damages. This study aims to investigate the real-time traffic, environmental, and crash characteristics and their interactions in terms of their [...] Read more.
Pile-up (PU) crashes, which involve multiple collisions between more than two vehicles within a brief timeframe, carry substantial consequences, including fatalities and significant damages. This study aims to investigate the real-time traffic, environmental, and crash characteristics and their interactions in terms of their contributions to severe PU crashes, which have been understudied. This study investigates and interprets the effects of Total Volume/Capacity (TV/C), “Heavy Vehicles Volume/Total Volume” (HVV/TV), and average speed. For this purpose, the PU crash severity was modelled and interpreted using the crash and real-time traffic data of Iran’s freeways over a 5-year period. Among six machine learning methods, the CatBoost model demonstrated superior performance, interpreted via the SHAP method. The results indicate that avg.speed > 90 km/h, TV/C < 0.6, HVV/TV ≥ 0.1, horizontal curves, longitudinal grades, nighttime, and the involvement of heavy vehicles are associated with the risk of severe PU crashes. Additionally, several interactions are associated with severe PU crashes, including the co-occurrence of TV/C ≈ 0.1, HVV/TV ≥ 0.25, and nighttime; the interactions between TV/C ≈ 0.1 or 0.45, HVV/TV ≥ 0.25, and avg.speed > 90 km/h; horizontal curves and high average speeds; horizontal curves; and nighttime. Overall, this research provides essential insights into traffic and environmental factors driving severe PU crashes, supporting informed decision-making for policymakers. Full article
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16 pages, 3920 KB  
Article
Inertial Motion Capturing in Ergonomic Workplace Analysis: Assessing the Correlation between RULA, Upper-Body Posture Deviations and Musculoskeletal Discomfort
by Steven Simon, Jonas Dully, Carlo Dindorf, Eva Bartaguiz, Oliver Walle, Ilsemarie Roschlock-Sachs and Michael Fröhlich
Safety 2024, 10(1), 16; https://doi.org/10.3390/safety10010016 - 2 Feb 2024
Cited by 5 | Viewed by 3698
Abstract
(1) Background: Mobile movement analysis systems, for example, those based on Inertial Measurement Units (IMUs), enable digital real-time methods of collecting data in workplace ergonomics, but the relationship between observational method scores such as Rapid Upper Limb Assessment (RULA), upper-body posture, and their [...] Read more.
(1) Background: Mobile movement analysis systems, for example, those based on Inertial Measurement Units (IMUs), enable digital real-time methods of collecting data in workplace ergonomics, but the relationship between observational method scores such as Rapid Upper Limb Assessment (RULA), upper-body posture, and their influence on musculoskeletal discomfort, has not yet been well investigated. This field study aimed to evaluate the relationship of these variables in two different target groups: production and office workers. (2) Methods: There were 64 subjects (44 men and 20 women) participating. Data collection was divided into two categories: (1) Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) (n = 64) and 3D stereophotogrammetric posture analysis (n = 58), and (2) Investigation of workload via IMU-based motion capture (MoCap) and the Borg CR-10 body map (n = 24). Correlation tests and regression analysis were performed using SPSS and MATLAB software to examine the relationship between the upper-body posture and RULA. Multivariate analysis of variance (MANOVA) was applied to examine group differences. (3) Results: The findings did not support the authors’ hypothesis that posture risk at work significantly correlates with static upper-body posture and musculoskeletal discomfort. Pelvic tilt had a weak but significant influence on RULA. The data revealed interesting trends in physical exertion, musculoskeletal discomfort, and differences between production and office workers. However, the statistical analysis did not support this. Such approaches have the potential to enhance the accuracy of assessment outcomes and, in turn, provide a stronger foundation for enhancing ergonomic conditions. Full article
(This article belongs to the Special Issue Environmental Risk Assessment—Health and Safety)
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18 pages, 873 KB  
Review
Noise Exposure, Prevention, and Control in Agriculture and Forestry: A Scoping Review
by Massimo Cecchini, Leonardo Assettati, Pierluigi Rossi, Danilo Monarca and Simone Riccioni
Safety 2024, 10(1), 15; https://doi.org/10.3390/safety10010015 - 1 Feb 2024
Cited by 6 | Viewed by 5563
Abstract
Noise is a major physical hazard in agricultural activities, and numerous research activities have managed to detect its effects, resulting in surveys and measurements which help to define exposure limits, prevention methods, and control strategies. This review aims to collect and analyse the [...] Read more.
Noise is a major physical hazard in agricultural activities, and numerous research activities have managed to detect its effects, resulting in surveys and measurements which help to define exposure limits, prevention methods, and control strategies. This review aims to collect and analyse the data from research studies and to provide a comprehensive overview on the subject. Thus, a set of 81 papers, gathered from the Scopus and PubMed scientific databases, has been analysed to provide information regarding the evolution of noise exposure levels over time, to highlight findings on noise-induced hearing loss (NIHL), and to list strategies for noise prevention and control in agriculture. Bibliographic research showed that noise measurements between 1991 and 2022, included in scientific research on farming, forestry, and animal husbandry, mainly reported values beyond the threshold of 85 dB(A); furthermore, several research activities on NIHL showed that farmers’ family members and children are often exposed to high levels of noise. Lastly, an analysis of the prevention and control strategies over time is provided, focusing on prevention programmes, screening, and the use of hearing protection devices (HPD). The identified literature suggests that additional efforts are required in regards to machinery design relating to the socio-technical aspects of agricultural activities and that side-effects of NIHL, as well as the negative impact of noise on other risks, might deserve further investigation. Full article
(This article belongs to the Special Issue Occupational Health and Safety (OHS): Emerging Trends and Future Directions)
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18 pages, 719 KB  
Article
Nonlinear Analysis of the Effects of Socioeconomic, Demographic, and Technological Factors on the Number of Fatal Traffic Accidents
by Nassim Sohaee and Shahram Bohluli
Safety 2024, 10(1), 11; https://doi.org/10.3390/safety10010011 - 10 Jan 2024
Cited by 13 | Viewed by 4126
Abstract
This study explores the complex connections among various socioeconomic, demographic, and technological aspects and their impact on fatal traffic accidents. Utilizing the Lasso polynomial regression model, this study explores the impact of demographic variables, including income, education, unemployment rates, and family size. Additionally, [...] Read more.
This study explores the complex connections among various socioeconomic, demographic, and technological aspects and their impact on fatal traffic accidents. Utilizing the Lasso polynomial regression model, this study explores the impact of demographic variables, including income, education, unemployment rates, and family size. Additionally, socioeconomic factors such as Gross Domestic Product (GDP) per capita, inflation rate, minimum wage, and government spending on transportation and infrastructure are examined for their impact on the occurrence of fatal accidents. This study also investigates the influence of technological advances in vehicles on the outcomes of traffic safety. The findings of this research reveal that certain factors, such as average, alcohol consumption, unemployment rate, minimum wage, and vehicle miles traveled (VMT), among others, have a substantial impact on the multifactorial model and play a considerable role in the frequency of fatal accident rates. The research results have significant implications for policymakers, highlighting the need for a comprehensive approach that accounts for the interdependence of economic indicators, behavioral patterns, and traffic safety outcomes. This study underscores the importance of considering a wide range of socioeconomic, demographic, and technological factors to develop effective policies and strategies to reduce fatal traffic accidents. Full article
(This article belongs to the Special Issue Traffic Safety Culture)
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21 pages, 12715 KB  
Article
Adaptive Intervention Algorithms for Advanced Driver Assistance Systems
by Kui Yang, Christelle Al Haddad, Rakibul Alam, Tom Brijs and Constantinos Antoniou
Safety 2024, 10(1), 10; https://doi.org/10.3390/safety10010010 - 9 Jan 2024
Cited by 7 | Viewed by 3727
Abstract
Advanced driver assistance systems (ADASs) have recently gained popularity as they assist vehicle operators in staying within safe boundaries, helping them thereby to prevent possible collisions. However, despite their success and development, most ADAS use common and deterministic warning thresholds for all drivers [...] Read more.
Advanced driver assistance systems (ADASs) have recently gained popularity as they assist vehicle operators in staying within safe boundaries, helping them thereby to prevent possible collisions. However, despite their success and development, most ADAS use common and deterministic warning thresholds for all drivers in all driving environments. This may occasionally lead to the issuance of annoying inadequate warnings, due to the possible differences between drivers, the changing environments and driver statuses, thus reducing their acceptance and effectiveness. To fill this gap, this paper proposes adaptive algorithms for commonly used warnings based on real-time traffic environments and driver status including distraction and fatigue. We proposed adaptive algorithms for headway monitoring, illegal overtaking, over-speeding, and fatigue. The algorithms were then tested using a driving simulator. Results showed that the proposed adaptive headway warning algorithm was able to automatically update the headway warning thresholds and that, overall, the proposed algorithms provided the expected warnings. In particular, three or four different warning types were designed to distinguish different risk levels. The designed real-time intervention algorithms can be implemented in ADAS to provide warnings and interventions tailored to the driver status to further ensure driving safety. Full article
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22 pages, 1319 KB  
Article
Perceived Factors Affecting the Implementation of Occupational Health and Safety Management Systems in the South African Construction Industry
by Rejoice Kunodzia, Luviwe Steve Bikitsha and Rainer Haldenwang
Safety 2024, 10(1), 5; https://doi.org/10.3390/safety10010005 - 2 Jan 2024
Cited by 16 | Viewed by 9888
Abstract
Although notable efforts have been made in the past to improve Occupational Health and Safety (OHS), the overall performance has not significantly improved as high-level injuries, risks, and fatalities continue to occur. Earlier studies have shown that implementing an Occupational Health and Safety [...] Read more.
Although notable efforts have been made in the past to improve Occupational Health and Safety (OHS), the overall performance has not significantly improved as high-level injuries, risks, and fatalities continue to occur. Earlier studies have shown that implementing an Occupational Health and Safety Management System (OHSMS) ensures a reduction in accidents on site, which is, however, not easy due to the many challenges arising during its implementation. The research objectives were to identify, in order of importance, factors that affect the implementation of an OHSMS on construction sites and to analyse how an OHSMS can be implemented in the construction industry of the Western Cape, South Africa, using the Plan Do Check Act (PDCA) method. The research questionnaire obtained online opinions from construction professionals. The data were analysed using the Statistical Package for Social Sciences (SPSS) software version 27.0. The data were interpreted through Cronbach’s alpha coefficient, frequencies, descriptive statistics, and a multi-regression analysis. A multi-regression test was conducted to determine the relationship between internal and external factors and the implementation of an OHSMS, including the use of the PDCA method. The findings reveal that both internal and external factors affected the implementation of the OHSMS. The most important internal factors were risk control strategies, senior management commitment, and support and communication channels. The most common external factors were pressure from clients on project delivery, company reputation, OHS enforcement, and government legislation. A framework was developed to outline how an OHSMS can be implemented using the PDCA approach based on the findings from this study. The framework can be adopted by the construction industry to improve effectiveness when implementing their OHSMS. Full article
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34 pages, 1696 KB  
Article
Enhancing System Safety and Reliability through Integrated FMEA and Game Theory: A Multi-Factor Approach
by Mohammad Yazdi
Safety 2024, 10(1), 4; https://doi.org/10.3390/safety10010004 - 22 Dec 2023
Cited by 19 | Viewed by 5253
Abstract
This study aims to address the limitations of traditional Failure Mode and Effect Analysis (FMEA) in managing safety and reliability within complex systems characterized by interdependent critical factors. We propose an integrated framework that combines FMEA with the strategic decision-making principles of Game [...] Read more.
This study aims to address the limitations of traditional Failure Mode and Effect Analysis (FMEA) in managing safety and reliability within complex systems characterized by interdependent critical factors. We propose an integrated framework that combines FMEA with the strategic decision-making principles of Game Theory, thereby enhancing the assessment and mitigation of risks in intricate environments. The novel inclusion of the Best Worst Method (BWM) and Pythagorean fuzzy uncertain linguistic variables refines the accuracy of risk evaluation by overcoming the inherent deficiencies of conventional FMEA approaches. Through sensitivity analysis, the framework’s efficacy in identifying and prioritizing failure modes is empirically validated, guiding the development of targeted interventions. The practical application of our methodology is demonstrated in a comprehensive healthcare system analysis, showcasing its versatility and significant potential to improve operational safety and reliability across various sectors. This research is particularly beneficial for systems engineers, risk managers, and decision-makers seeking to fortify complex systems against failures and their effects. Full article
(This article belongs to the Special Issue Safety, Resilience and Reliability Challenges and Engineering Research in Renewable Energies)
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26 pages, 886 KB  
Review
The Role of Deep Learning Models in the Detection of Anti-Social Behaviours towards Women in Public Transport from Surveillance Videos: A Scoping Review
by Marcella Papini, Umair Iqbal, Johan Barthelemy and Christian Ritz
Safety 2023, 9(4), 91; https://doi.org/10.3390/safety9040091 - 13 Dec 2023
Cited by 4 | Viewed by 4274
Abstract
Increasing women’s active participation in economic, educational, and social spheres requires ensuring safe public transport environments. This study investigates the potential of machine learning-based models in addressing behaviours impacting the safety perception of women commuters. Specifically, we conduct a comprehensive review of the [...] Read more.
Increasing women’s active participation in economic, educational, and social spheres requires ensuring safe public transport environments. This study investigates the potential of machine learning-based models in addressing behaviours impacting the safety perception of women commuters. Specifically, we conduct a comprehensive review of the existing literature concerning the utilisation of deep learning models for identifying anti-social behaviours in public spaces. Employing a scoping review methodology, our study synthesises the current landscape, highlighting both the advantages and challenges associated with the automated detection of such behaviours. Additionally, we assess available video and audio datasets suitable for training detection algorithms in this context. The findings not only shed light on the feasibility of leveraging deep learning for recognising anti-social behaviours but also provide critical insights for researchers, developers, and transport operators. Our work aims to facilitate future studies focused on the development and implementation of deep learning models, enhancing safety for all passengers in public transportation systems. Full article
(This article belongs to the Special Issue Women’s Issues in Safety)
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20 pages, 304 KB  
Article
Relationship between Safety Climate and Safety Behavior in Company X in Indonesia
by Arief Hertanto, Dadan Erwandi, Baiduri Widanarko and Mila Tejamaya
Safety 2023, 9(4), 89; https://doi.org/10.3390/safety9040089 - 12 Dec 2023
Cited by 6 | Viewed by 5509
Abstract
Throughout 2019–2021, there was a considerable rise in total work accident cases in Indonesia, increasing from 210,789 to 234,370. According to the location of the incident, accident cases in the workplace also escalated from 139,999 to 144,929. The purpose of this study was [...] Read more.
Throughout 2019–2021, there was a considerable rise in total work accident cases in Indonesia, increasing from 210,789 to 234,370. According to the location of the incident, accident cases in the workplace also escalated from 139,999 to 144,929. The purpose of this study was to measure the maturity level of the safety climate at Company X in Indonesia and analyze its relationship with safety behavior. This was a quantitative study on a total of 200 respondents using a questionnaire as the data collection method. A structured questionnaire was used to capture the socio-demographic characteristics of respondents, the safety climate, and safety behavior. Respondents participated in this study by responding to the items in the questionnaire distributed. The findings of this study indicated that the maturity level of the safety climate at Company X was at the adequate level with a very strong relationship between the sub-dimensional variables and safety climate. The relationship between safety climate and safety behavior was quite strong. This study emphasized that an increase in the level of safety climate could improve safety behavior. Therefore, increasing safety climate level is effective to reduce the incidence of occupational accidents. Full article
(This article belongs to the Collection Occupational Health and Safety in A Changing World: Realities, Challenges and Perspectives)
20 pages, 11013 KB  
Article
Going beyond Chat: Designing Connotative Meaningful Line Stickers to Promote Road Safety in Thailand through Participatory Design
by Thawatphong Phithak, Pawanrat Surasangprasert and Sorachai Kamollimsakul
Safety 2023, 9(4), 87; https://doi.org/10.3390/safety9040087 - 7 Dec 2023
Cited by 2 | Viewed by 5197
Abstract
Road accidents are a leading cause of death in Thailand, with increasing fatalities. Despite road safety campaigns during holidays, consistent communication is lacking in daily life. This research aimed to create Line application stickers, a top chat platform for Thailand, using the participatory [...] Read more.
Road accidents are a leading cause of death in Thailand, with increasing fatalities. Despite road safety campaigns during holidays, consistent communication is lacking in daily life. This research aimed to create Line application stickers, a top chat platform for Thailand, using the participatory design (PD) approach. PD was implemented in two steps. Firstly, 100 participants outlined character types, moods, tones, and communication objectives. They recommended lively animal characters with diverse texts, such as greetings, work, travel, and emotions. Then, through a focus group, the tortoise was identified to represent cautious drivers who follow traffic rules, the rabbit to represent fast and risky drivers, and the zebra to represent vigilant and disciplined traffic police officers as characters for Line stickers. Subsequently, using the semiotics approach, 40 Line stickers were designed, and embedded with denotative and connotative road safety messages. Secondly, feedback from the focus group, integral to the PD process, led to refinements. After launching, a survey of 50 users showed “Benefits Received”, “Text and Messages”, and “Meaning” dimensions received “Very Satisfied/Strongly Agree” ratings. The “Character” dimension received a “Satisfied” rating. The results for “Benefits Received” can also be analyzed in the context of the Knowledge, Attitude, and Practice (KAP) theory, which revealed that K and A were at the highest level, while P was at a high level. This suggests that the Line stickers designed in this study effectively conveyed road safety messages to the receivers. This research constitutes the pioneering exploration within the realm of Line stickers concerning road safety, signifying the originality and unique contribution of our research to the existing body of knowledge in this domain. The PD process in this research can serve as a guideline for creating safety-promoting media in diverse fields. Full article
(This article belongs to the Special Issue Worldwide Accidents: Trends, Investigation and Prevention)
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17 pages, 3573 KB  
Article
A Case Study for an Assessment of Fire Station Selection in the Central Urban Area
by An-Chi Huang, Chung-Fu Huang and Chi-Min Shu
Safety 2023, 9(4), 84; https://doi.org/10.3390/safety9040084 - 4 Dec 2023
Cited by 16 | Viewed by 4687
Abstract
With the continual acceleration of urbanization, the amount of urban infrastructure and the quality of public services are increasing in many cities. A pressing concern in this context is the growing problem of incompatible fire protection construction, indicating a need for urban fire [...] Read more.
With the continual acceleration of urbanization, the amount of urban infrastructure and the quality of public services are increasing in many cities. A pressing concern in this context is the growing problem of incompatible fire protection construction, indicating a need for urban fire stations with well-planned layouts. However, research on optimizing the layout and placement of fire stations by considering the various factors affecting station layouts is lacking. The current study addressed this gap by establishing an optimal fire station layout by using a geographic information system (GIS) and elucidated the trends of GIS application in firefighting and rescue operations. The study’s findings reveal the benefits of avoiding blind spots, enhancing the selection of fire station sites, and optimizing service coverage. Furthermore, this study optimized the layout of CZ city’s downtown fire stations, which could enhance CZ city’s firefighting capabilities. Full article
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17 pages, 1975 KB  
Article
A Deep-Learning Approach to Driver Drowsiness Detection
by Mohammed Imran Basheer Ahmed, Halah Alabdulkarem, Fatimah Alomair, Dana Aldossary, Manar Alahmari, Munira Alhumaidan, Shoog Alrassan, Atta Rahman, Mustafa Youldash and Gohar Zaman
Safety 2023, 9(3), 65; https://doi.org/10.3390/safety9030065 - 13 Sep 2023
Cited by 38 | Viewed by 14201
Abstract
Drowsy driving is a widespread cause of traffic accidents, especially on highways. It has become an essential task to seek an understanding of the situation in order to be able to take immediate remedial actions to detect driver drowsiness and enhance road safety. [...] Read more.
Drowsy driving is a widespread cause of traffic accidents, especially on highways. It has become an essential task to seek an understanding of the situation in order to be able to take immediate remedial actions to detect driver drowsiness and enhance road safety. To address the issue of road safety, the proposed model offers a method for evaluating the level of driver fatigue based on changes in a driver’s eyeball movement using a convolutional neural network (CNN). Further, with the help of CNN and VGG16 models, facial sleepiness expressions were detected and classified into four categories (open, closed, yawning, and no yawning). Subsequently, a dataset of 2900 images of eye conditions associated with driver sleepiness was used to test the models, which include a different range of features such as gender, age, head position, and illumination. The results of the devolved models show a high degree of accountability, whereas the CNN model achieved an accuracy rate of 97%, a precision of 99%, and recall and F-score values of 99%. The VGG16 model reached an accuracy rate of 74%. This is a considerable contrast between the state-of-the-art methods in the literature for similar problems. Full article
(This article belongs to the Special Issue Safety and Risk Management in Digitalized Process Systems)
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22 pages, 1271 KB  
Systematic Review
A New Shift in Implementing Unmanned Aerial Vehicles (UAVs) in the Safety and Security of Smart Cities: A Systematic Literature Review
by Khalifa AL-Dosari and Noora Fetais
Safety 2023, 9(3), 64; https://doi.org/10.3390/safety9030064 - 13 Sep 2023
Cited by 35 | Viewed by 6667
Abstract
The rapid rise of Unmanned Aerial Vehicles (UAVs) and their integration into smart city initiatives has sparked a surge of research interest in a broad array of thematic areas. This study undertakes a comprehensive review of recent scholarly literature to elucidate key research [...] Read more.
The rapid rise of Unmanned Aerial Vehicles (UAVs) and their integration into smart city initiatives has sparked a surge of research interest in a broad array of thematic areas. This study undertakes a comprehensive review of recent scholarly literature to elucidate key research trends and innovative strategies for applying UAVs in smart cities. Through a detailed descriptive analysis, we identify prominent research clusters, including integrating the Internet of Things (IoT) with UAVs, applying artificial intelligence in surveillance, exploring the Internet of Drones (IoD), and cybersecurity challenges faced by smart cities. It is observed that security and privacy concerns within smart cities receive the most scholarly attention, indicating their central importance in shaping smart city strategies. The review of innovative strategies reveals a strong emphasis on leveraging cutting-edge technologies to enhance UAV capabilities and ensure drones’ efficient, secure, and ethical deployment in smart city environments. This study provides crucial insights that inform the design of future research and policies in the burgeoning field of smart city development through the use of UAVs. Full article
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21 pages, 14351 KB  
Article
Exploring the Robustness of Alternative Cluster Detection and the Threshold Distance Method for Crash Hot Spot Analysis: A Study on Vulnerable Road Users
by Muhammad Faisal Habib, Raj Bridgelall, Diomo Motuba and Baishali Rahman
Safety 2023, 9(3), 57; https://doi.org/10.3390/safety9030057 - 25 Aug 2023
Cited by 9 | Viewed by 4041
Abstract
Traditional hot spot and cluster analysis techniques based on the Euclidean distance may not be adequate for assessing high-risk locations related to crashes. This is because crashes occur on transportation networks where the spatial distance is network-based. Therefore, this research aims to conduct [...] Read more.
Traditional hot spot and cluster analysis techniques based on the Euclidean distance may not be adequate for assessing high-risk locations related to crashes. This is because crashes occur on transportation networks where the spatial distance is network-based. Therefore, this research aims to conduct spatial analysis to identify clusters of high- and low-risk crash locations. Using vulnerable road users’ crash data of San Francisco, the first step in the workflow involves using Ripley’s K-and G-functions to detect the presence of clustering patterns and to identify their threshold distance. Next, the threshold distance is incorporated into the Getis-Ord Gi* method to identify local hot and cold spots. The analysis demonstrates that the network-constrained G-function can effectively define the appropriate threshold distances for spatial correlation analysis. This workflow can serve as an analytical template to aid planners in improving their threshold distance selection for hot spot analysis as it employs actual road-network distances to produce more accurate results, which is especially relevant when assessing discrete-data phenomena such as crashes. Full article
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18 pages, 990 KB  
Article
Modelling the Impact of Driver Work Environment on Driving Performance among Oil and Gas Heavy Vehicles: SEM-PLS
by Al-Baraa Abdulrahman Al-Mekhlafi, Ahmad Shahrul Nizam Isha, Ali Nasser Al-Tahitah, Ahmed Farouk Kineber, Baker Nasser Saleh Al-Dhawi and Muhammad Ajmal
Safety 2023, 9(3), 48; https://doi.org/10.3390/safety9030048 - 20 Jul 2023
Cited by 9 | Viewed by 3641
Abstract
Driving heavy vehicles with dangerous cargo involves various work environments that can significantly impact road safety. This research aims to study the impact of oil and gas tanker drivers’ work environment on driving performance to identify and address any issues that may affect [...] Read more.
Driving heavy vehicles with dangerous cargo involves various work environments that can significantly impact road safety. This research aims to study the impact of oil and gas tanker drivers’ work environment on driving performance to identify and address any issues that may affect their ability to carry out their jobs effectively. To achieve this, a quantitative approach was employed using a questionnaire survey adapted from the literature review. The data collected from a sample of drivers of oil- and gas-heavy vehicles were analyzed using structural equation modelling. The study’s findings reveal a significant association between the drivers’ work environment and driving performance, represented by a path coefficient of β = 0.237. These results highlight the substantial contribution of the work environment to driving performance, with an effect of 63%. Consequently, the study emphasizes the importance of considering the work environment as a potential factor when assessing and enhancing tanker drivers’ driving abilities during oil and gas transportation. Full article
(This article belongs to the Special Issue Road Safety for All: The Impact of Sociodemographic Inequalities on Road Safety)
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22 pages, 3165 KB  
Review
Innovative Technologies for Occupational Health and Safety: A Scoping Review
by Omar Flor-Unda, Mauricio Fuentes, Daniel Dávila, Mario Rivera, Gladys Llano, Carlos Izurieta and Patricia Acosta-Vargas
Safety 2023, 9(2), 35; https://doi.org/10.3390/safety9020035 - 26 May 2023
Cited by 13 | Viewed by 15632
Abstract
Technological advancements have allowed for the design and development of multiple intelligent devices that monitor the health and safety status of workers in the industry in general. This paper reviews and describes the alternative technologies and their potential for monitoring risk situations, vital [...] Read more.
Technological advancements have allowed for the design and development of multiple intelligent devices that monitor the health and safety status of workers in the industry in general. This paper reviews and describes the alternative technologies and their potential for monitoring risk situations, vital signs, physical variables, worker positions, and behavioral trends of workers in their work activities in the workplace. A scoping review was conducted using PRISMA ScR in which information was extracted from 99 scientific articles related to these technological advances. The operational characteristics and utilities of devices whose primary function is to control better and monitor worker safety and health were identified. It was concluded that technology strongly improves the acquisition and sending of information. This information can be used to provide alerts and feedback to workers so that they act more safely and protect their health. In addition, technological developments have resulted in devices that eliminate operational risks by replacing manual activities with automated and autonomous tasks. Full article
(This article belongs to the Topic Cultural Safety—Towards a Global Research Agenda)
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12 pages, 757 KB  
Article
Comparing Machine Learning Techniques for Predictions of Motorway Segment Crash Risk Level
by Dimitrios Nikolaou, Apostolos Ziakopoulos, Anastasios Dragomanovits, Julia Roussou and George Yannis
Safety 2023, 9(2), 32; https://doi.org/10.3390/safety9020032 - 20 May 2023
Cited by 12 | Viewed by 2598
Abstract
Motorways are typically the safest road environment in terms of injury crashes per million vehicle kilometres; however, given the high severity of crashes occurring therein, there is still space for road safety improvements. The objective of this study is to compare the classification [...] Read more.
Motorways are typically the safest road environment in terms of injury crashes per million vehicle kilometres; however, given the high severity of crashes occurring therein, there is still space for road safety improvements. The objective of this study is to compare the classification performance of five machine learning techniques for predictions of crash risk levels of motorway segments. To that end, data on crash risk levels, driving behaviour metrics, and road geometry characteristics of 668 motorway segments were exploited. The utilized dataset was divided into training and test subsets, with a proportion of 75% and 25%, respectively. The training subset was used to train the models, whereas the test subset was used for the evaluation of their performance. The response variable of the models was the crash risk level of the considered motorway segments, while the predictors were various road design characteristics and naturalistic driving behaviour metrics. The techniques considered were Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and K-Nearest Neighbours. Among the five techniques, the Random Forest model achieved the best classification performance (overall accuracy: 89.3%, macro-averaged precision: 89.0%, macro-averaged recall: 88.4%, macro-averaged F1 score: 88.6%). Moreover, the Shapley additive explanations were calculated in order to assist with the interpretation of the model’s outcomes. The findings of this study are particularly useful as the Random Forest model could be used as a highly promising proactive road safety tool for identifying potentially hazardous motorway segments. Full article
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16 pages, 1826 KB  
Review
A Scoping Literature Review of Natural Language Processing Application to Safety Occurrence Reports
by Jon Ricketts, David Barry, Weisi Guo and Jonathan Pelham
Safety 2023, 9(2), 22; https://doi.org/10.3390/safety9020022 - 5 Apr 2023
Cited by 20 | Viewed by 8034
Abstract
Safety occurrence reports can contain valuable information on how incidents occur, revealing knowledge that can assist safety practitioners. This paper presents and discusses a literature review exploring how Natural Language Processing (NLP) has been applied to occurrence reports within safety-critical industries, informing further [...] Read more.
Safety occurrence reports can contain valuable information on how incidents occur, revealing knowledge that can assist safety practitioners. This paper presents and discusses a literature review exploring how Natural Language Processing (NLP) has been applied to occurrence reports within safety-critical industries, informing further research on the topic and highlighting common challenges. Some of the uses of NLP include the ability for occurrence reports to be automatically classified against categories, and entities such as causes and consequences to be extracted from the text as well as the semantic searching of occurrence databases. The review revealed that machine learning models form the dominant method when applying NLP, although rule-based algorithms still provide a viable option for some entity extraction tasks. Recent advances in deep learning models such as Bidirectional Transformers for Language Understanding are now achieving a high accuracy while eliminating the need to substantially pre-process text. The construction of safety-themed datasets would be of benefit for the application of NLP to occurrence reporting, as this would allow the fine-tuning of current language models to safety tasks. An interesting approach is the use of topic modelling, which represents a shift away from the prescriptive classification taxonomies, splitting data into “topics”. Where many papers focus on the computational accuracy of models, they would also benefit from real-world trials to further inform usefulness. It is anticipated that NLP will soon become a mainstream tool used by safety practitioners to efficiently process and gain knowledge from safety-related text. Full article
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22 pages, 3781 KB  
Review
Safety of Automated Agricultural Machineries: A Systematic Literature Review
by Guy R. Aby and Salah F. Issa
Safety 2023, 9(1), 13; https://doi.org/10.3390/safety9010013 - 6 Mar 2023
Cited by 21 | Viewed by 9854
Abstract
Automated agricultural machinery has advanced significantly in the previous ten years; however, the ability of such robots to operate safely will be critical to their commercialization. This study provides a holistic evaluation of the work carried out so far in the field of [...] Read more.
Automated agricultural machinery has advanced significantly in the previous ten years; however, the ability of such robots to operate safely will be critical to their commercialization. This study provides a holistic evaluation of the work carried out so far in the field of automated agricultural machines’ safety, as well as a framework for future research considerations. Previous automated agricultural machines’ safety-related studies are analyzed and grouped into three categories: (1) environmental perception, (2) risk assessment as well as risk mitigation, and (3) human factors as well as ergonomics. The key findings are as follows: (1) The usage of single perception, multiple perception sensors, developing datasets of agricultural environments, different algorithms, and external solutions to improve sensor performance were all explored as options to improve automated agricultural machines’ safety. (2) Current risk assessment methods cannot be efficient when dealing with new technology, such as automated agricultural machines, due to a lack of pre-existing knowledge. Full compliance with the guidelines provided by the current International Organization for Standardization (ISO 18497) cannot ensure automated agricultural machines’ safety. A regulatory framework and being able to test the functionalities of automated agricultural machines within a reliable software environment are efficient ways to mitigate risks. (3) Knowing foreseeable human activity is critical to ensure safe human–robot interaction. Full article
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21 pages, 1766 KB  
Article
Fatigue and Secondary Media Impacts in the Automated Vehicle: A Multidimensional State Perspective
by Catherine E. Neubauer, Gerald Matthews and Erika P. De Los Santos
Safety 2023, 9(1), 11; https://doi.org/10.3390/safety9010011 - 23 Feb 2023
Cited by 5 | Viewed by 2992
Abstract
Safety researchers increasingly recognize the impacts of task-induced fatigue on vehicle driving behavior. The current study (N = 180) explored the use of a multidimensional fatigue measure, the Driver Fatigue Questionnaire (DFQ), to test the impacts of vehicle automation, secondary media use, and [...] Read more.
Safety researchers increasingly recognize the impacts of task-induced fatigue on vehicle driving behavior. The current study (N = 180) explored the use of a multidimensional fatigue measure, the Driver Fatigue Questionnaire (DFQ), to test the impacts of vehicle automation, secondary media use, and driver personality on fatigue states and performance in a driving simulator. Secondary media included a trivia game and a cellphone conversation. Simulated driving induced large-magnitude fatigue states in participants, including tiredness, confusion, coping through self-comforting, and muscular symptoms. Consistent with previous laboratory and field studies, dispositional fatigue proneness predicted increases in state fatigue during the drive, especially tiredness, irrespective of automation level and secondary media. Similar to previous studies, automation slowed braking response to the emergency event following takeover but did not affect fatigue. Secondary media use relieved subjective fatigue and improved lateral control but did not affect emergency braking. Confusion was, surprisingly, associated with faster braking, and tiredness was associated with impaired control of lateral position of the vehicle. These associations were not moderated by the experimental factors. Overall, data support the use of multidimensional assessments of both fatigue symptoms and information-processing components for evaluating safety impacts of interventions for fatigue. Full article
(This article belongs to the Special Issue Human Factors in Road Safety and Mobility)
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20 pages, 2790 KB  
Article
Determination of Requirements for the Improvement of Occupational Safety in the Cleaning of Vertical Tanks of Petroleum Products
by Magdalena Ramírez-Peña, Alberto Cerezo-Narváez, Andrés Pastor-Fernández, Manuel Otero-Mateo and Pablo Ballesteros-Pérez
Safety 2023, 9(1), 6; https://doi.org/10.3390/safety9010006 - 2 Feb 2023
Cited by 8 | Viewed by 3773
Abstract
Since the beginning of the second industrial revolution, the use of tanks for the storage of petroleum products ensured the permanent supply of equipment that depended on fossil fuel derived from petroleum, either for direct consumption or as an element for power generation. [...] Read more.
Since the beginning of the second industrial revolution, the use of tanks for the storage of petroleum products ensured the permanent supply of equipment that depended on fossil fuel derived from petroleum, either for direct consumption or as an element for power generation. For correct operation, periodic cleaning of these confined spaces was required, being a common practice for the direct exposure of operators to explosive atmospheres. Currently, there are many industries that keep this kind of deposit, and cleaning works are considered of high occupational risk. In this context, the question arises as to whether human–machine collaboration thanks to the technologies that compose Industry 5.0 can mitigate these risks while generating a sustainable balance by optimizing costs and protecting the environment. In the present work, the analytic hierarchy process (AHP) method is used to prioritize the requirements that should be compiled to establish safe protocols in tank cleaning works, solving the multi-criteria problem. Results prove that a couple of alternatives improve the working conditions of the people involved in this process: the chemical cleaning and the robotic cleaning, which approximately accounts for two thirds of the decision. These requirements are aligned with the Industry 5.0 paradigm, encouraging the use of robots for high-risk processes, and influencing human behavior. In addition, cost reduction is achieved without compromising on quality of service or delivery schedule, thus enabling a circular economy that promotes occupational safety in company policies. Full article
(This article belongs to the Collection Occupational Health and Safety in A Changing World: Realities, Challenges and Perspectives)
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14 pages, 1772 KB  
Article
The Effect of Driving Style on Responses to Unexpected Vehicle Cyberattacks
by Fangda Zhang, Meng Wang, Jah’inaya Parker and Shannon C. Roberts
Safety 2023, 9(1), 5; https://doi.org/10.3390/safety9010005 - 31 Jan 2023
Cited by 8 | Viewed by 3299
Abstract
Vehicle cybersecurity is a serious concern, as modern vehicles are vulnerable to cyberattacks. How drivers respond to situations induced by vehicle cyberattacks is safety critical. This paper sought to understand the effect of human drivers’ risky driving style on response behavior to unexpected [...] Read more.
Vehicle cybersecurity is a serious concern, as modern vehicles are vulnerable to cyberattacks. How drivers respond to situations induced by vehicle cyberattacks is safety critical. This paper sought to understand the effect of human drivers’ risky driving style on response behavior to unexpected vehicle cyberattacks. A driving simulator study was conducted wherein 32 participants experienced a series of simulated drives in which unexpected events caused by vehicle cyberattacks were presented. Participants’ response behavior was assessed by their change in velocity after the cybersecurity events occurred, their post-event acceleration, as well as time to first reaction. Risky driving style was portrayed by scores on the Driver Behavior Questionnaire (DBQ) and the Brief Sensation Seeking Scale (BSSS). Half of the participants also received training regarding vehicle cybersecurity before the experiment. Results suggest that when encountering certain cyberattack-induced unexpected events, whether one received training, driving scenario, participants’ gender, DBQ-Violation scores, together with their sensation seeking measured by disinhibition, had a significant impact on their response behavior. Although both the DBQ and sensation seeking have been constantly reported to be linked with risky and aberrant driving behavior, we found that drivers with higher sensation seeking tended to respond to unexpected driving situations induced by vehicle cyberattacks in a less risky and potentially safer manner. This study incorporates not only human factors into the safety research of vehicle cybersecurity, but also builds direct connections between drivers’ risky driving style, which may come from their inherent risk-taking tendency, to response behavior to vehicle cyberattacks. Full article
(This article belongs to the Special Issue Human Factors in Road Safety and Mobility)
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11 pages, 2097 KB  
Article
Objective Evaluation of the Somatogravic Illusion from Flight Data of an Airplane Accident
by Eric L. Groen, Torin K. Clark, Mark M. J. Houben, Jelte E. Bos and Randall J. Mumaw
Safety 2022, 8(4), 85; https://doi.org/10.3390/safety8040085 - 14 Dec 2022
Cited by 5 | Viewed by 4543
Abstract
(1) Background: It is difficult for accident investigators to objectively determine whether spatial disorientation may have contributed to a fatal airplane accident. In this paper, we evaluate three methods to reconstruct the possible occurrence of the somatogravic illusion based on flight data recordings [...] Read more.
(1) Background: It is difficult for accident investigators to objectively determine whether spatial disorientation may have contributed to a fatal airplane accident. In this paper, we evaluate three methods to reconstruct the possible occurrence of the somatogravic illusion based on flight data recordings from an airplane accident. (2) Methods: The outputs of two vestibular models were compared with the “standard” method, which uses the unprocessed gravito-inertial acceleration (GIA). (3) Results: All three methods predicted that the changing orientation of the GIA would lead to a somatogravic illusion when no visual references were available. However, the methods were not able to explain the first pitch-down control input by the pilot flying, which may have been triggered by the inadvertent activation of the go-around mode and a corresponding pitch-up moment. Both vestibular models predicted a few seconds delay in the illusory tilt from GIA due to central processing and sensory integration. (4) Conclusions: While it is difficult to determine which method best predicted the somatogravic illusion perceived during the accident without data on the pilot’s pitch perception, both vestibular models go beyond the GIA analysis in taking into account validated vestibular dynamics, and they also account for other vestibular illusions. In that respect, accident investigators would benefit from a unified and validated vestibular model to better explain pilot actions in accidents related to spatial disorientation. Full article
(This article belongs to the Special Issue Aviation Safety—Accident Investigation, Analysis and Prevention)
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27 pages, 1472 KB  
Review
Augmented Reality for Vehicle-Driver Communication: A Systematic Review
by Liam Kettle and Yi-Ching Lee
Safety 2022, 8(4), 84; https://doi.org/10.3390/safety8040084 - 13 Dec 2022
Cited by 15 | Viewed by 7033
Abstract
Capabilities for automated driving system (ADS)-equipped vehicles have been expanding over the past decade. Research has explored integrating augmented reality (AR) interfaces in ADS-equipped vehicles to improve drivers’ situational awareness, performance, and trust. This paper systematically reviewed AR visualizations for in-vehicle vehicle-driver communication [...] Read more.
Capabilities for automated driving system (ADS)-equipped vehicles have been expanding over the past decade. Research has explored integrating augmented reality (AR) interfaces in ADS-equipped vehicles to improve drivers’ situational awareness, performance, and trust. This paper systematically reviewed AR visualizations for in-vehicle vehicle-driver communication from 2012 to 2022. The review first identified meta-data and methodological trends before aggregating findings from distinct AR interfaces and corresponding subjective and objective measures. Prominent subjective measures included acceptance, trust, and user experience; objective measures comprised various driving behavior or eye-tracking metrics. Research more often evaluated simulated AR interfaces, presented through windshields, and communicated object detection or intended maneuvers, in level 2 ADS. For object detection, key visualizations included bounding shapes, highlighting, or symbols. For intended route, mixed results were found for world-fixed verse screen-fixed arrows. Regardless of the AR design, communicating the ADS’ actions or environmental elements was beneficial to drivers, though presenting clear, relevant information was more favorable. Gaps in the literature that yet to be addressed include longitudinal effects, impaired visibility, contextual user needs, system reliability, and, most notably, inclusive design. Regardless, the review supports that integrating AR interfaces in ADS-equipped vehicles can lead to higher trust, acceptance, and safer driving performances. Full article
(This article belongs to the Special Issue Human Factors in Road Safety and Mobility)
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18 pages, 2787 KB  
Article
Dynamic Failure Risk Assessment of Wastewater Treatment and Reclamation Plant: An Industrial Case Study
by Razieh Analouei, Masoud Taheriyoun and Md Tanjin Amin
Safety 2022, 8(4), 79; https://doi.org/10.3390/safety8040079 - 4 Dec 2022
Cited by 6 | Viewed by 5733
Abstract
Due to the growing scarcity of water resources, wastewater reuse has become one of the most effective solutions for industrial consumption. However, various factors can detrimentally affect the performance of a wastewater treatment plant (WWTP), which is considered a risk of not fulfilling [...] Read more.
Due to the growing scarcity of water resources, wastewater reuse has become one of the most effective solutions for industrial consumption. However, various factors can detrimentally affect the performance of a wastewater treatment plant (WWTP), which is considered a risk of not fulfilling the effluent requirements. Thus, to ensure the quality of treated wastewater, it is essential to analyze system failure causes and their potential outcomes and mitigation measures through a systematic dynamic risk assessment approach. This work shows how a dynamic Bayesian network (DBN) can be effectively used in this context. Like the conventional Bayesian network (BN), the DBN can capture complex interactions between failure contributory factors. Additionally, it can forecast the upcoming failure likelihood using a prediction inference. This proposed methodology was applied to a WWTP of the Moorchekhort Industrial Complex (MIC), located in the center of Iran. A total of 15 years’ time frame (2016–2030) has been considered in this work. The first six years’ data have been used to develop the DBN model and to identify the crucial risk factors that are further used to reduce the risk in the remaining nine years. The risk increased from 21% to 42% in 2016–2021. Applying the proposed risk mitigation measures can decrease the failure risk from 33% to 9% in 2022–2030. The proposed model showed the capability of the DBN in risk management of a WWTP system which can help WWTPs’ managers and operators achieve better performance for higher reclaimed water quality. Full article
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24 pages, 12005 KB  
Article
Numerical Calculation and Analysis of Water Dump Distribution Out of the Belly Tanks of Firefighting Helicopters
by Tejun Zhou, Jiazheng Lu, Chuanping Wu and Shilong Lan
Safety 2022, 8(4), 69; https://doi.org/10.3390/safety8040069 - 3 Oct 2022
Cited by 6 | Viewed by 4182
Abstract
Helicopters are more and more widely used for water dumping in fire extinguishing operations nowadays. Increasing attention is being paid to improving helicopter firefighting efficiency. Water distribution onto the ground from the helicopter tank is a key reference target to evaluate firefighting efficiency. [...] Read more.
Helicopters are more and more widely used for water dumping in fire extinguishing operations nowadays. Increasing attention is being paid to improving helicopter firefighting efficiency. Water distribution onto the ground from the helicopter tank is a key reference target to evaluate firefighting efficiency. Numerical simulations and calculations were carried out concerning water dumping out of the belly tank of a helicopter using the VOF (Volume of Fluent Model) model and mesh adaptation in ANSYS Fluent, and the effects of two parameters, the height of the tank above the ground and the wind speed, on the wake flow and water distribution were discussed. The results showed that for forward flight, the higher the forward flight speed, the less the average water depth on the ground. Similar results were obtained for flight height. The average water depth was one order of magnitude less than in the cases of the corresponding hovering helicopter for a given wind speed. As for hovering flight, the higher the wind speed, the less the average water depth on the ground. The simulation results were basically consistent with the conclusions of water dump tests of fire-fighting equipment carried by helicopters. For example, when the helicopter flew at a forward flight speed of 15 m/s and the tank bottom was 30 m above the ground, the area covered by the dumped water would be 337.5 m2, and the average water depth accumulated per square meter would be 0.3 cm. This result was close to the 0.34 cm obtained under Hayden Biggs’s test condition with a forward flight speed of 70 km/h and a height above the ground of 24 m. Full article
(This article belongs to the Topic Multiagency Approach to Disaster Management, Focusing on Triage, Treatment and Transport)
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18 pages, 502 KB  
Article
The Effect of Psychosocial Safety Climate on Engagement and Psychological Distress: A Multilevel Study on the Healthcare Sector
by Silvia Platania, Martina Morando, Alice Caruso and Vittorio Edoardo Scuderi
Safety 2022, 8(3), 62; https://doi.org/10.3390/safety8030062 - 2 Sep 2022
Cited by 27 | Viewed by 7370
Abstract
All work sectors have been affected by the impact of the COVID-19 pandemic. The perception of risk combined with the lack of safety and fear for their own safety have caused severe psychological discomfort in workers. Of all the work sectors, the most [...] Read more.
All work sectors have been affected by the impact of the COVID-19 pandemic. The perception of risk combined with the lack of safety and fear for their own safety have caused severe psychological discomfort in workers. Of all the work sectors, the most affected was certainly the healthcare sector. In hospitals, medical staff were at the forefront of the battle against COVID-19, providing care in close physical proximity to patients and had a direct risk of being exposed to the virus. The main objective of the study was to investigate the perception of a psychosocial safety climate and the effect on engagement and psychological stress in a sample of 606 healthcare workers (physicians 39.6%, nurses 41.3%, healthcare assistant 19.1%), belonging to six organisations and organised into 11 working groups. Furthermore, we wanted to investigate the mediating effect of workaholism at both individual and group level. The results partially confirmed our hypotheses and the mediating effect at the individual level of working compulsively. A psychosocial safety climate in healthcare workers led to a decrease in engagement through the mediation of working compulsively. The mediating effect of working compulsively might be due to a climate that did not guarantee or preserve the psychological health and safety of healthcare workers. In this research, the most important limit concerns the number of organisations and the number of groups. Full article
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11 pages, 2245 KB  
Article
Musculoskeletal Disorders among Agricultural Workers of Various Cultivation Activities in Upper Northeastern Thailand
by Worawan Poochada, Sunisa Chaiklieng and Sari Andajani
Safety 2022, 8(3), 61; https://doi.org/10.3390/safety8030061 - 1 Sep 2022
Cited by 7 | Viewed by 6320
Abstract
Musculoskeletal disorders (MSDs) are the most significant work-related health conditions that are experienced by agricultural workers. This cross-sectional study has investigated MSDs among agriculturalists in upper northeastern Thailand. We assessed the types of MSDs, their severity, and their frequency. There were 889 cultivating [...] Read more.
Musculoskeletal disorders (MSDs) are the most significant work-related health conditions that are experienced by agricultural workers. This cross-sectional study has investigated MSDs among agriculturalists in upper northeastern Thailand. We assessed the types of MSDs, their severity, and their frequency. There were 889 cultivating agriculturalists from four provinces who participated in this study. The majority of the participants reported experiencing mild levels of MSDs (60.48%). Predominantly, the farmers who were working on cassava, vegetable, and sugarcane plantations reported experiencing the most severe MSDs in the knees/calves (22.40%). The rice plantation workers reported the largest number of MSDs complaints. The workers on rubber plantations and in sugarcane fields were more likely to feel knee/calf pain (OR = 1.59, 95% CI = 1.05–2.39) and lower limb pain (OR = 1.97, 95% CI = 1.35–2.89) than those who were working on rice and tobacco plantations. The individuals who were working on cassava, fruit, vegetable, and corn plantations were also more likely to report knee/calf pain (OR = 1.48, 95% CI = 1.01–2.17) and lower limb pain (OR = 1.97, 95% CI = 1.37–2.84) than those who were working on rice and tobacco plantations. The MSDs that were found among those working on agricultural activities affected many parts of their bodies. The ergonomic risk needs to be assessed in order to inform plantation workers of the implications in order to improve their health and well-being and to reduce the risks of MSDs. Full article
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20 pages, 1733 KB  
Article
Assessing System-Wide Safety Readiness for Successful Human–Robot Collaboration Adoption
by Nicole Berx, Arie Adriaensen, Wilm Decré and Liliane Pintelon
Safety 2022, 8(3), 48; https://doi.org/10.3390/safety8030048 - 1 Jul 2022
Cited by 14 | Viewed by 5054
Abstract
Despite their undisputed potential, the uptake of collaborative robots remains below expectations. Collaborative robots (cobots) are used differently from conventional industrial robots. The current safety focus of collaborative workspaces is predominantly on the technological design; additional factors also need to be considered to [...] Read more.
Despite their undisputed potential, the uptake of collaborative robots remains below expectations. Collaborative robots (cobots) are used differently from conventional industrial robots. The current safety focus of collaborative workspaces is predominantly on the technological design; additional factors also need to be considered to cope with the emerging risks associated with complex systems. Cobot technologies are characterized by an inherent tradeoff between safety and efficiency. They introduce new, emergent risks to organizations and can create psychosocial impacts on workers. This leads to a confusing body of information and an apparent contradiction about cobot safety. Combined with a lack of safety knowledge, this impedes the introduction of cobots. A multi-step methodology was used, including a literature review and conceptual modeling. This article argues for the need for a system-wide safety awareness readiness assessment in the consideration phase of cobot implementation to alleviate the knowledge deficit and confusion. This work will benefit both researchers and practitioners. In addition, it defends the appropriateness of a maturity grid model for a readiness assessment tool. The building blocks for an easy-to-use and practically applicable tool are proposed, as well as an agenda for the next steps. Full article
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20 pages, 3250 KB  
Article
Understanding the Factors Associated with the Temporal Variability in Crash Severity before, during, and after the COVID-19 Shelter-in-Place Order
by Emmanuel Kofi Adanu, Sunday Okafor, Praveena Penmetsa and Steven Jones
Safety 2022, 8(2), 42; https://doi.org/10.3390/safety8020042 - 2 Jun 2022
Cited by 13 | Viewed by 4646
Abstract
The COVID-19 travel restriction orders have significantly reduced travel and generally lowered the risk of road traffic collisions, but many accounts suggest an increase in risky driving behaviors and consequent fatal crashes during the shelter-in-place period. Risky driving behaviors including failure to wear [...] Read more.
The COVID-19 travel restriction orders have significantly reduced travel and generally lowered the risk of road traffic collisions, but many accounts suggest an increase in risky driving behaviors and consequent fatal crashes during the shelter-in-place period. Risky driving behaviors including failure to wear a seatbelt, speeding, and drunk driving were observed to be the leading contributing factors of the fatalities. Whereas the fatal crashes that characterized the shelter-in-place period has become a topical issue, the high number of crashes that occurred as a result of the panic shopping and increased travel activities in the weeks before the shelter-in-place order have not received much attention. In this study, we investigated the differences and similarities in the effects of the factors that were associated with crash injury severity before, during, and after the shelter-in-place order. The study used crash data from the state of Alabama for the 2020 calendar year. Preliminary data analysis revealed interesting variations in crash trends across the three periods. It was found that the highest weekly crash frequency occurred in the immediate week before the shelter-in-place order, and a higher proportion of crashes that occurred between 6 p.m. and 6 a.m. and those that occurred in residential areas happened during the shelter-in-place period while shopping area crashes, manufacturing/industrial area crashes, rear-end collisions, and crashes involving female drivers occurred mostly before the shelter-in-place period. Three injury severity models were developed using random parameters logit with heterogeneity in means and variances approach. The results showed that major injury crashes occurred mainly in rural areas and occurred due to speeding, fatigue driving, and failure to use a seatbelt. The effects of these factors on crash outcome did not vary across the year, indicating that the shelter-in-place order did not impact the driving behaviors of the driver population that got into major injury crashes. The results further revealed that the effects of some crash factors, such as road type and manner of collision, varied across the periods. The findings of the study provide a deeper, data-driven understanding of how driving behaviors and associated crash outcomes may be affected by extreme events such as the COVID-19 shelter-in-place. Full article
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25 pages, 10915 KB  
Article
Methodology for Monitoring Work Zones Traffic Operations Using Connected Vehicle Data
by Rahul Suryakant Sakhare, Jairaj Desai, Howell Li, Mischa A. Kachler and Darcy M. Bullock
Safety 2022, 8(2), 41; https://doi.org/10.3390/safety8020041 - 1 Jun 2022
Cited by 13 | Viewed by 6433
Abstract
The National Work Zone Safety Information Clearinghouse estimated there were approximately 115,000 work zone crashes with 842 fatalities in 2019. There is broad consensus that it is important for agencies to develop near real-time risk assessment of work zone traffic operations to proactively [...] Read more.
The National Work Zone Safety Information Clearinghouse estimated there were approximately 115,000 work zone crashes with 842 fatalities in 2019. There is broad consensus that it is important for agencies to develop near real-time risk assessment of work zone traffic operations to proactively identify improvement opportunities. Due to the huge spatial distribution and relatively low frequency of crashes, legacy techniques of monitoring crash locations do not scale well for identifying all but the most severe construction zone operational problems. Past research identified hard braking and congestion as strong predictors for crashes in and around work zones. This paper presents scalable methodologies that can be used to systematically analyze hard-braking and speed data obtained from connected vehicles. These techniques have been applied to over 205 billion records in Indiana since 2019. These statewide data analytics are fused into concise graphics to identify work zones with emerging anomalies in congestion and/or hard braking. Weekly screening reports, institutionalized in Indiana for the past two years, provide information for agile agency monitoring and response. Case studies show quantitative changes in work zone performance measures, and corresponding surveillance video images illustrate the significance of these changes. During this period of near real-time monitoring and agile agency response, Indiana interstate crash rates have been reduced by 31% from 2019 to 2021, even though most 2021 interstate traffic volumes have rebounded to pre-pandemic 2019 volumes. Full article
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18 pages, 613 KB  
Article
Goal Conflicts, Classical Management and Constructivism: How Operators Get Things Done
by Leonie Boskeljon-Horst, Robert J. De Boer, Simone Sillem and Sidney W. A. Dekker
Safety 2022, 8(2), 37; https://doi.org/10.3390/safety8020037 - 7 May 2022
Cited by 5 | Viewed by 4455
Abstract
In this study we identify the differences in goal realisation when applying two conflicting paradigms regarding rule perception and management. We gathered more than 30 scenarios where goal conflicts were apparent in a military operational unit. We found that operators repetitively utilized certain [...] Read more.
In this study we identify the differences in goal realisation when applying two conflicting paradigms regarding rule perception and management. We gathered more than 30 scenarios where goal conflicts were apparent in a military operational unit. We found that operators repetitively utilized certain routines in executing their tasks in an effort to realize several conflicting goals. These routines were not originally intended nor designed into the rules and not explicitly included in documentation. They were not necessarily at odds with the literal wording and/or the intent of rules and regulations, although we did find examples of this. Our data showed that local ingenuity was created innovatively within the frame of existing rules or kept invisible to those outside the unit. The routines were introduced and passed on informally, and we found no evidence of testing for the introduction of new risks, no migration into the knowledge base of the organisation, and no dissemination as new best practices. An explanation for this phenomenon was found in the fact that the military organisation was applying a top-down, classical, rational approach to rules. In contrast, the routines were generated by adopting a constructivist view of rules as dynamic, local, situated constructions with operators as experts. The results of this study suggest that organisations are more effective in solving goal conflicts and creating transparency on local ingenuity if they adopt a constructivist paradigm instead of, or together with, a classical paradigm. Full article
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17 pages, 992 KB  
Article
Prioritizing the Potential Smartification Measures by Using an Integrated Decision Support System with Sustainable Development Goals (a Case Study in Southern Italy)
by Giuseppe Guido, Sina Shaffiee Haghshenas, Sami Shaffiee Haghshenas, Alessandro Vitale, Vincenzo Gallelli and Vittorio Astarita
Safety 2022, 8(2), 35; https://doi.org/10.3390/safety8020035 - 5 May 2022
Cited by 14 | Viewed by 3707
Abstract
With the increasing population of cities, expanding roads as one of the essential urban infrastructures is a necessary task; therefore, adverse effects such as increased fuel consumption, pollution, noise, and road accidents are inevitable. One of the most efficient ways to mitigate congestion-related [...] Read more.
With the increasing population of cities, expanding roads as one of the essential urban infrastructures is a necessary task; therefore, adverse effects such as increased fuel consumption, pollution, noise, and road accidents are inevitable. One of the most efficient ways to mitigate congestion-related adverse effects is to introduce effective intelligent transportation systems (ITS), using advanced technologies and mobile communication protocols to make roads smarter and reduce negative impacts such as improvement in fuel consumption and pollution, and reduction of road accidents, which leads to improving quality of life. Smart roads might play a growing role in the improved safety of road transportation networks. This study aims to evaluate and rank the potential smartification measures for the road network in Calabria, in southern Italy, with sustainable development goals. For this purpose, some potential smartification measures were selected. Experts in the field were consulted using an advanced procedure: four criteria were considered for evaluating these smartification measures. The Integrated fuzzy decision support system (FDSS), namely the fuzzy Delphi analytic hierarchy process (FDAHP) with the fuzzy technique for order performance by similarity to ideal solution (FTOPSIS) were used for evaluating and ranking the potential smartification measures. The results demonstrated that the repetition of signals in the vehicle has the highest rank, and photovoltaic systems spread along the road axis has the lowest rank to use as smartification measures in the roads of the case study. Full article
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18 pages, 3329 KB  
Article
Ergonomic Design of Apron Bus with Consideration for Passengers with Mobility Constraints
by Ma. Janice J. Gumasing, Yogi Tri Prasetyo, Ardvin Kester S. Ong, Maria Rebeka Isabel M. Carcellar, John Brixter J. Aliado, Reny Nadlifatin and Satria Fadil Persada
Safety 2022, 8(2), 33; https://doi.org/10.3390/safety8020033 - 3 May 2022
Cited by 13 | Viewed by 9324
Abstract
Passengers in an apron bus are usually subjected to a standing position because of its limited seats and capacity. Due to this, passengers, especially those with mobility constraints, may expose themselves to musculoskeletal disorder (MSD) risks such as body pain, discomfort, and non-collision [...] Read more.
Passengers in an apron bus are usually subjected to a standing position because of its limited seats and capacity. Due to this, passengers, especially those with mobility constraints, may expose themselves to musculoskeletal disorder (MSD) risks such as body pain, discomfort, and non-collision injuries. The purpose of this study is to design an ergonomic apron bus to aid the musculoskeletal discomfort experienced by passengers with mobility constraints, specifically the elderly, pregnant women, mothers carrying infants, and persons needing wheelchair assistance. A total of 149 participants are involved in the study. Corlett’s and Bishop’s body discomfort questionnaires and Rapid Entire Body Assessment (REBA) are utilized to evaluate the respondent’s experience of discomfort in different regions of their body. The results show that passengers with mobility constraints experience body discomfort during the apron bus ride. The prevalence of body discomfort is evident in the lower back, knee, thigh, arm, shoulder, and middle back. Finally, principles of anthropometry are used in the study along with quality function deployment (QFD), failure mode and effects analysis (FMEA), and cost-benefit analysis to evaluate the feasibility of the recommended ergonomic design of the apron bus. To meet the requirements of people with disabilities, the ergonomic design of an apron bus is created to minimize the risk of exposure of passengers to certain musculoskeletal discomfort, maximize the space, minimize the delay time of the airlines, and be able to prioritize passengers who require mobility assistance. Full article
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13 pages, 1731 KB  
Article
Effects of Automation and Fatigue on Drivers from Various Age Groups
by Sadegh Arefnezhad, Arno Eichberger and Ioana Victoria Koglbauer
Safety 2022, 8(2), 30; https://doi.org/10.3390/safety8020030 - 11 Apr 2022
Cited by 10 | Viewed by 5219
Abstract
This study explores how drivers are affected by automation when driving in rested and fatigued conditions. Eighty-nine drivers (45 females, 44 males) aged between 20 and 85 years attended driving experiments on separate days, once in a rested and once in a fatigued [...] Read more.
This study explores how drivers are affected by automation when driving in rested and fatigued conditions. Eighty-nine drivers (45 females, 44 males) aged between 20 and 85 years attended driving experiments on separate days, once in a rested and once in a fatigued condition, in a counterbalanced order. The results show an overall effect of automation to significantly reduce drivers’ workload and effort. The automation had different effects, depending on the drivers’ conditions. Differences between the manual and automated mode were larger for the perceived time pressure and effort in the fatigued condition as compared to the rested condition. Frustration was higher during manual driving when fatigued, but also higher during automated driving when rested. Subjective fatigue and the percentage of eye closure (PERCLOS) were higher in the automated mode compared to manual driving mode. PERCLOS differences between the automated and manual mode were higher in the fatigued condition than in the rested condition. There was a significant interaction effect of age and automation on drivers’ PERCLOS. These results are important for the development of driver-centered automation because they show different benefits for drivers of different ages, depending on their condition (fatigued or rested). Full article
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23 pages, 2196 KB  
Article
Evaluation of Contributing Factors Affecting Number of Vehicles Involved in Crashes Using Machine Learning Techniques in Rural Roads of Cosenza, Italy
by Giuseppe Guido, Sina Shaffiee Haghshenas, Sami Shaffiee Haghshenas, Alessandro Vitale, Vittorio Astarita, Yongjin Park and Zong Woo Geem
Safety 2022, 8(2), 28; https://doi.org/10.3390/safety8020028 - 8 Apr 2022
Cited by 39 | Viewed by 5973
Abstract
The evaluation of road safety is a critical issue having to be conducted for successful safety management in road transport systems, whereas safety management is considered in road transportation systems as a challenging task according to the dynamic of this issue and the [...] Read more.
The evaluation of road safety is a critical issue having to be conducted for successful safety management in road transport systems, whereas safety management is considered in road transportation systems as a challenging task according to the dynamic of this issue and the presence of a large number of effective parameters on road safety. Therefore, the evaluation and analysis of important contributing factors affecting the number of vehicles involved in crashes play a key role in increasing the efficiency of road safety. For this purpose, in this research work, two machine learning algorithms, including the group method of data handling (GMDH)-type neural network and a combination of support vector machine (SVM) and the grasshopper optimization algorithm (GOA), are employed. Hence, the number of vehicles involved in an accident is considered to be the output, and the seven factors affecting transport safety, including Daylight (DL), Weekday (W), Type of accident (TA), Location (L), Speed limit (SL), Average speed (AS), and Annual average daily traffic (AADT) of rural roads in Cosenza, southern Italy, are selected as the inputs. In this study, 564 data sets from rural areas were investigated, and the relevant, effective parameters were measured. In the next stage, several models were developed to investigate the parameters affecting the safety management of road transportation in rural areas. The results obtained demonstrated that the “Type of accident” has the highest level and “Location” has the lowest importance in the investigated rural area. Finally, although the results of both algorithms were the same, the GOA-SVM model showed a better degree of accuracy and robustness than the GMDH model. Full article
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18 pages, 18689 KB  
Review
A Review of Vehicle-to-Vulnerable Road User Collisions on Limited-Access Highways to Support the Development of Automated Vehicle Safety Assessments
by Husam Muslim and Jacobo Antona-Makoshi
Safety 2022, 8(2), 26; https://doi.org/10.3390/safety8020026 - 6 Apr 2022
Cited by 8 | Viewed by 6216
Abstract
This study aims to provide evidence to support the development of automated vehicle (AV) safety assessments that consider the possible presence of non-motorized vulnerable road-users (VRUs) on limited-access highways. Although limited-access highways are designed to accommodate high-speed motor vehicles, collisions involving VRUs on [...] Read more.
This study aims to provide evidence to support the development of automated vehicle (AV) safety assessments that consider the possible presence of non-motorized vulnerable road-users (VRUs) on limited-access highways. Although limited-access highways are designed to accommodate high-speed motor vehicles, collisions involving VRUs on such roadways are frequently reported. A narrative review is conducted, covering the epidemiology of VRUs crashes on limited-access highways to identify typical crash patterns considering collisions severity and the underlying reasons for the VRUs to use the highway. The review results show that occupants alighting from a disabled or crashed vehicle, people seeking help or helping others, highway maintenance zones, police stops, and people crossing a highway should be given priority to ensure VRU safety on limited-access highways. The results are summarized in figures with schematic models to generate test scenarios for AV safety assessment. Additionally, the results are discussed using two examples of traffic situations relevant to the potential AV-VRU crashes on highways and the current performance of autonomous emergency braking and autonomous emergency steering systems. These findings have important implications for producing scenarios in which AV may not produce crashes lest it performs worse than human drivers in the proposed scenarios. Full article
(This article belongs to the Special Issue Transportation System Design)
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22 pages, 2750 KB  
Article
Safety Engagement in the Workplace: Text Mining Analysis
by Hyun Jeong Seo and Ah Jeong Hong
Safety 2022, 8(2), 24; https://doi.org/10.3390/safety8020024 - 1 Apr 2022
Cited by 3 | Viewed by 6623
Abstract
In order to derive safety engagement factors in the workplace and analyze the characteristics of the factors, we collected literature data to be analyzed by a systematic literature review and text mining analysis. We used safety, industrial, occupational, corporate, commitment, engagement, interaction, and [...] Read more.
In order to derive safety engagement factors in the workplace and analyze the characteristics of the factors, we collected literature data to be analyzed by a systematic literature review and text mining analysis. We used safety, industrial, occupational, corporate, commitment, engagement, interaction, and participation as key search terms for literature selection and used 143 literature datasets for analysis. We divided the factors of workplace safety engagement into the organizational level and the individual level. In studies after 2005, texts at the individual psychological level appeared in large numbers. Although individual factors have been studied as subfactors at the organizational level, we confirmed that the two types of factors must interact for safety engagement in the workplace. We classified safety engagement factors into cognitive, emotional, behavioral, and relational factors. In particular, relational factors were mainly composed of factors that negatively affected engagement. In the follow-up study, we identified the maturity level among safety engagement factors as divided into four dimensions needed to create a safe workplace environment and to suggest a direction for employees to engage themselves in safety. Full article
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