Safety

The State-of-the-Practice Survey on United States Departments of Transportation (DOTs) Worker Injuries and Safety Program Efforts is a comprehensive report that provides valuable insights into the safety programs of state DOTs. The survey was conducted using a web-based questionnaire that was distributed to all 50 state DOTs and received a response rate of 44% (22 states). The survey consisted of 40 questions that were designed to gather information about the safety programs of state DOTs, including their training and education efforts, injury analysis practices, and safety efforts. The survey responses were analyzed using descriptive statistics and a thematic analysis approach. The results highlighted contrasts in safety efforts across responding DOTs, with various methods of injury documentation, data collection, and the implementation of safety-related policies and procedures. The report offers recommendations for reducing worker injuries and illnesses, including the need for standardized injury documentation and data collection practices, the provision of regular and updated training to address new hazards that may arise due to changes in job tasks or procedures, the allocation of adequate funding and resources to support safety programs, and the development of a return-to-work program to facilitate the prompt return of injured workers. Additionally, ergonomic assessments and training should be provided to prevent musculoskeletal injuries. The report concludes that state DOTs can benefit from sharing best practices and collaborating on safety initiatives in order to improve worker safety and reduce the incidence of injuries and illnesses. The findings of this survey may be beneficial to any DOT implementing worker safety best practices within their respective agency. The limitations of the study include a lack of inferential statistical analysis due to the restricted statistical power of the sample size. Full article

This paper aims at delivering new empirical evidence as to the effectiveness of 20 mph speed limits in rural areas. For this purpose, speed and traffic data were drawn from the area of the Scottish Borders, UK, where the local Council led the rollout of a 20 mph speed limit trial in 97 villages and towns from October 2020. This intervention is considered as one of the first of its kind in the UK and overseas, as it was carried out on a large scale, in predominantly rural areas. To evaluate the impact of the 20 mph speed limit on vehicle speeds, we conducted a “before–after” quantitative analysis using traffic and speed data collected in different waves before and after the intervention. The descriptive analysis showed that both mean and 85th percentile speeds reduced directly after the introduction of the 20 mph speed limit (by 3.1 mph and 3.2 mph, respectively), and that such speed reductions were largely maintained even up to eight months after the onset of the intervention. The largest speed reductions were observed in locations with high-speed patterns before the intervention, and especially in those having mean speeds greater than 25 mph before the intervention. Both non-parametric and parametric statistical tests, which were conducted using approximately five million speed observations, showed that the observed speed changes were statistically significant for the vast majority of cases. Linear regression models were also estimated confirming the significant impact of the 20 mph limit on vehicle speeds, while controlling for the influence of traffic volume. Overall, the findings of this study will likely assist in filling an evidence gap regarding the effectiveness of 20 mph speed limits in rural settlements. They can also provide encouragement to those local authorities in the UK and abroad that are currently actively examining the possibility of setting the 20 mph as the default limit in built-up areas. Full article

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

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

Virtual Reality (VR) construction safety training modules have reached a level of maturity which renders them as a serious alternative to traditional safety training modules. The purpose of this study is to investigate the usability of a particular safety training module related to “Working at heights” for blue-collar construction workers in Kuwait. A mixed study approach was applied based on a semi-quasi experimental research design, utilizing a control group/experimental group with pre-/post-test measurements, supplemented by observations. The findings indicate a statistically insignificant higher learning effectiveness of the workers exposed to the VR approach. Observations confirmed that trainees require an extended time of preparation to become familiar with moving within the virtual environment and using the related hardware. Furthermore, younger users with less work experience reported a higher usability than older users with more work experience. VR content developers are encouraged to investigate the possibilities of simplifying the virtual environment to make it more relevant for blue-collar workers, reduce the complexity of the hardware, and intensify the feeling of the consequences resulting from users’ choices. Construction companies and educational institutions training construction blue-collar workers can benefit from the VR approach to safety training if they allow sufficient time for familiarization with the virtual training module. Full article

This work presents a data-centric method to use IoT data, generated from the site, to monitor core functions of safety barriers on a batch reactor. The approach turns process safety performance indicators (PSPIs) into online, globally available safety indicators that eliminate variability in human interpretation. This work also showcases a class of PSPIs that are reliable and time-dependent but only work in a digital online environment: profile PSPIs. It is demonstrated that the profile PSPI opens many new opportunities for leading indicators, without the need for complex mathematics. Online PSPI analyses were performed at the Syngenta Huddersfield Manufacturing Centre, Leeds Road, West Yorkshire, United Kingdom, and shared with their international headquarters in Basel, Switzerland. The performance was determined with industry software to extract time-series data and perform the calculations. The calculations were based on decades of IoT data stored in the AVEVA Factory Historian. Non-trivial data cleansing and additional data tags were required for the creation of relevant signal conditions and composite conditions. This work demonstrates that digital methods do not require gifted data analysts to report existing PSPIs in near real-time and is well within the capabilities of chemical (safety) engineers. Current PSPIs can also be evaluated in terms of their effectiveness to allow management to make decisions that lead to corrective actions. This improves significantly on traditional PSPI processes that, when reviewed monthly, lead to untimely decisions and actions. This approach also makes it possible to review PSPIs as they develop, receiving notifications of PSPIs when they reach prescribed limits, all with the potential to recommend alternative PSPIs that are more proactive in nature. Full article

Due to the advancements in real-time information communication technologies and sharing economies, rideshare services have gained significant momentum by offering dynamic and/or on-demand services. Rideshare service companies evolved from personal rideshare, where riders traveled solo or with known individuals, into pooled rideshare (PR), where riders can travel with one to multiple unknown riders. Similar to other shared economy services, pooled rideshare is beneficial as it efficiently utilizes resources, resulting in reduced energy usage, as well as reduced costs for the riders. However, previous research has demonstrated that riders have concerns about using pooled rideshare, especially regarding personal safety. A U.S. national survey with 5385 participants was used to understand human factor-related barriers and user preferences to develop a novel Pooled Rideshare Acceptance Model (PRAM). This model used a covariance-based structural equation model (CB-SEM) to identify the relationships between willingness to consider PR factors (time/cost, privacy, safety, service experience, and traffic/environment) and optimizing one’s experience of PR factors (vehicle technology/accessibility, convenience, comfort/ease of use, and passenger safety), resulting in the higher-order factor trust service. We examined the factors’ relative contribution to one’s willingness/attitude towards PR and user acceptance of PR. Privacy, safety, trust service, and convenience were statistically significant factors in the model, as were the comfort/ease of use factor and the service experience, traffic/environment, and passenger safety factors. The only two non-significant factors in the model were time/cost and vehicle technology/accessibility; it is only when a rider feels safe that individuals then consider the additional non-significant variables of time, cost, technology, and accessibility. Privacy, safety, and service experience were factors that discouraged the use of PR, whereas the convenience factor greatly encouraged the acceptance of PR. Despite the time/cost factor’s lack of significance, individual items related to time and cost were crucial when viewed within the context of convenience. This highlights that while user perceptions of privacy and safety are paramount to their attitude towards PR, once safety concerns are addressed, and services are deemed convenient, time and cost elements significantly enhance their trust in pooled rideshare services. This study provides a comprehensive understanding of user acceptance of PR services and offers actionable insights for policymakers and rideshare companies to improve their services and increase user adoption. Full article

This manuscript presents a study on the spatial relationships between bike accidents, the built environment, land use, and transportation network characteristics in Budapest, Hungary using geographic weighted regression (GWR). The sample period includes bike crash data between 2017 and 2022. The findings provide insights into the spatial distribution of bike crashes and their severity, which can be useful for designing targeted interventions to improve bike safety in Budapest and be useful for policymakers and city planners in developing effective strategies to reduce the severity of bike crashes in urban areas. The study reveals that built environment features, such as traffic signals, road crossings, and bus stops, are positively correlated with the bike crash index, particularly in the inner areas of the city. However, traffic signals have a negative correlation with the bike crash index in the suburbs, where they may contribute to making roads safer for cyclists. The study also shows that commercial activity and PT stops have a higher impact on bike crashes in the northern and western districts. GWR analysis further suggests that one-way roads and higher speed limits are associated with more severe bike crashes, while green and recreational areas are generally safer for cyclists. Future research should be focused on the traffic volume and bike trips’ effects on the severity index. Full article

Background: Permanent Daylight Savings Time (DST) may improve road safety by providing more daylight in the evening but could merely shift risk to morning commutes or increase risk due to fatigue and circadian misalignment. Methods: To identify how potential daylight exposure and fatigue risk could differ between permanent DST versus permanent Standard Time (ST) or current time arrangements (CTA), generic work and school schedules in five United States cities were modeled in SAFTE-FAST biomathematical modeling software. Commute data were categorized by morning (0700–0900) and evening (1600–1800) rush hours. Results: Percent darkness was greater under DST compared with ST for the total waking day (t = 2.59, p = 0.03) and sleep periods (t = 2.46, p = 0.045). Waketimes occurred before sunrise 63 ± 41% percent of the time under DST compared with CTA (42 ± 37%) or ST (33 ± 38%; F(_2,74) = 76.37; p < 0.001). Percent darkness was greater during morning (16 ± 31%) and lower during evening rush hour (0 ± 0%) in DST compared with either CTA (morning: 7 ± 23%; evening: 7 ± 14%) or ST (morning: 7 ± 23%; evening: 7 ± 15%). Discussion: Morning rush hour overlaps with students’ commutes and shift workers’ reverse commutes, which may increase traffic congestion and risk compared with evening rush hour. Switching to permanent DST may be more disruptive than either switching to ST or keeping CTA without noticeable benefit to fatigue or potential daylight exposure. Full article

Accidents pose significant obstacles to economic progress and quality of life, especially in developing countries. Thailand faces such challenges and this research seeks to assess the frequency and most common causes of road accidents that lead to fatalities. This study employed the Apriori algorithm to examine the interrelationships among factors contributing to accidents in order to inform policymaking for reducing accident rates, minimizing economic and human losses, and enhancing the effectiveness of the healthcare system. By analyzing road accident data from 2015 to 2020 in Thailand (167,820 accidents causing THB 1.13 billion in damages), this article specifically focuses on the drivers responsible for fatal highway accidents. The findings reveal several interconnected variables that heighten the likelihood of fatalities, such as male gender, exceeding speed limits, riding a motorbike, traveling on straight roads, encountering dry surface conditions, and clear weather. An association rule analysis underscores the increased risk of injury or death in traffic accidents. Full article

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

The offshore oil and gas working environment is an inherently dangerous one, with risks posed to physical safety on a daily basis. One neglected field of research is the added psychosocial stressors present in this environment. This research examined the experiences of offshore oil and gas workers through one-on-one online interviews which were recorded and transcribed. Transcripts were analyzed through the qualitative software NVivo, which generated themes and patterns for the responses given to questions that were developed through a focus group. The results of the analysis showed that multiple psychosocial stressors are present in this population, such as fear of speaking up, unsatisfactory company-provided facilities, work–life interference, work status, micromanaging, gender harassment and bullying. In addition, interviews identified that production and time pressures, along with fatigue, can influence accidents and mistakes. Climate factors also cause discomfort. However, these are managed according to best practices by organizations. Due to the timing of the study, COVID-19 was a significant stressor for some, but not all, employees. In conclusion, offshore oil and gas workers face multiple stressors in a dangerous environment that may lead to devastating consequences. Full article

In this article, the authors apply the intervention mapping (IM) protocol to develop safety leadership training for a rail infrastructure maintenance company. The IM protocol helps to create an evidence-based intervention in a structured way, based on concrete evidence. The application of IM within the occupational safety domain is limited, a research gap that this article bridges with the development and testing of a safety leadership intervention to promote safety behavior among managers. The company was positively and actively engaged in the training program thanks to the IM protocol. The local support group took full advantage of the opportunities to provide input during the development of the training’s various components. Despite this, interpersonal problems within the leadership team itself, such as a lack of psychological safety, were not identified during the needs assessment. These issues had an impact on the overall effectiveness of the training, as they manifested during the training when managers met physically for the first time in several years (due to the coronavirus). Our IM protocol will be adjusted accordingly for future applications, and we hope that sharing our experiences will enable fellow researchers to avoid this problem. Full article

Mega sports events may encounter safety and security challenges related to risk management issues such as overcrowding, disorderly behavior, assaults, and security breaches. An incident during the Champions League Final in France in 2022 serves as an example of such challenges. Therefore, this study focuses specifically on the Champions League Final in France, 2022, and presents a situational scenario analysis for safety and security professionals. The objective is to enhance situational awareness and improve risk management strategies for similar events. The study commences by investigating the awareness among security and safety professionals regarding the potential consequences of mega sporting events, utilizing a post-hoc damage evaluation of France ’22. It then compares the effectiveness of fixed and drone cameras in surveillance imaging, aiming to identify ways to enhance situational analysis for improved risk management. The findings indicate that safety and security professionals acknowledged the negative outcomes of adverse events and demonstrated higher situational awareness when using drone surveillance as opposed to relying solely on fixed cameras. They also expressed positive attitudes towards the adoption of surveillance for mega sporting events. Moreover, the study introduces a model for drone surveillance scenario analysis, designed for dynamic decision-making. This model has been developed and aligned to effectively integrate drone surveillance and enhance situational awareness, not only for mega sports events but also for similar applications in various contexts. This research contributes to the understanding of risk management and situational awareness in the realm of mega sports events. It underscores the significance of drone surveillance and proposes strategies to enhance security professionals’ ability to respond effectively to potential threats, ensuring the safety of participants and spectators. Full article

A fall from height is the main cause of serious injuries and fatalities in occupational and work-related accidents, especially construction. Falls from scaffolds, ladders, or roofs are very frequent accident scenarios. Especially for those falls from a height of 1 m to 6 m, the use of wearable smart airbags has been proposed to mitigate possible torso injuries. In this study, a virtual assessment of such an inflatable protector was conducted using numerical simulations and finite element human body models in order to determine its impact-protection performance under realistic impact conditions and identify its possible limitations. The findings obtained from the simulation study showed a significant protective effect provided by the airbag, mitigating a multiple rib fracture scenario and reducing the risk of internal organ injuries for those falling from four meters of height or less. The use case analyzed in this research demonstrates the suitability of using a virtual environment not only to evaluate current protectors but also to develop new protector devices, which could improve occupational safety. Full article

Paediatric homecare is an advancing field of healthcare, bringing care direct to patients in their own homes. Risk management is an integral component of homecare services, including incident and risk assessment management. The objective of the study was to investigate risk management in homecare focusing on two aspects: incident reporting and risk assessments. A Grounded Theory approach was used to gather key functions of these aspects; these were then mapped using the Functional Resonance Analysis method (FRAM). Nineteen nurses working in paediatric homecare services were interviewed for the study. The interviews were semi-structured and focused on risk, quality, complaints, audit, care, and management. The interview data were transcribed and coded using Nvivo; the data were then converted into functions for utilization in the FRAM tool. The FRAM detailed the process of incident reporting and risk assessment management of the actual work carried out as viewed by the participants of the study. The information was then analysed and contrasted with the organizational policy to gain an understanding of the systems of incident reporting and risk assessments, which then led to the development of a refined process that could have less variability in function. Consequently, changes to policy and training in risk management were recommended to enhance the systems. Full article

The industrial sector is improving its management systems and designing healthy workspaces by focusing on selecting the best ways to reduce accidents and optimize financial and human resources. Hand tools represent the general equipment used in a significant range of industrial jobs. This research aims to develop a tool selection method to help users, managers, and tool designers ensure awareness and care regarding ergonomics based on the anthropometrics of employees, considering the main risk factors for tool selection. The information, which relates to hand security risk factors and the established parameters set by official international institutions, is evaluated during the study. This paper also presents a safety risk assessment framework based on criteria collected through a survey from 10 experts to rate the initial risk value and determine its importance using the analytical hierarchy process (AHP). As a result, the analysis identified the possibility of injury (with 73.06% accuracy) as the biggest concern for companies due to its immediate effects on workers’ health. It provides a decision regimen—a tool for decision-makers to design and plan prevention activities to reduce accidents, injuries, and possible illnesses. It further lays out a methodical and analytical model to be used by managers to ensure correct hand tool selection. This model can be used to reduce the possibility of illnesses or injuries for workers and tailor the ergonomic design of each workstation according to specific hand anthropometric data for the worker. Full article

(1) Background: The use of force by public and private security forces is currently an issue of great relevance because of the potential injuries caused by any excessive use of force by either active or passive subjects or a deficit in the real mastery of appropriate physical intervention techniques (PITs). For this reason, certain traditionally used physical intervention techniques have been questioned by scientific research studies and punished by justice. On the other hand, certain media have dealt with this matter in a biased and unfair manner by broadcasting videos where the use of force by police officer is displayed out of context. As a consequence, this problem has been brought under the spotlight, causing general uneasiness of the communities and rapidly spreading over social networks while favoring all sorts of parallel judgments. (2) Research method: A suit was equipped with 19 inertial measurement units (IMUs) and a Biomechanics of Bodies software application for Marras analysis of the data collected on trajectory, trunk twisting velocity, sagittal angle, load, and nature and severity of the injuries associated with the different intervention techniques examined. (3) Results: According to the data registered, the implementation of operational tactical procedures (OTPs) reduces the probability of injuries and leads to a more satisfactory outcome. (4) Conclusions: The implementation of operational tactical procedures, together with an awareness of the risks associated with the excessive use of force by public and private security forces and bodies, could reduce the risk of injuries suffered by both officers and citizens. Full article

Fire is a typical disaster in the processing industry. Ionic liquids, as a type of green flame retardant, play an important role in process safety. In order to grasp the current research status, hotspots, and frontiers in the field of ionic liquids in flame retardancy, the bibliometric mapping method is applied to study the relevant literature in Web of Science datasets from 2000–2022 in this paper. The results show that the research on ionic liquids in flame retardancy is multidisciplinary and involves some disciplines such as energy science, material science, and environmental protection. Journal of Power Sources, Polymer Degradation and Stability, ACS Applied Materials and Interfaces, and Chemical Engineering Journal are the core journals in the field. The results of keyword co-occurrence indicate that the hotspots of research can be divided into five components: the improvement and application of pure ionic liquids electrolytes, the research of gel polymer electrolytes, applying ionic liquids to enhance the polymer materials’ flame retardancy properties, utilizing ionic liquids and inorganic materials to synergize flame retardant polymers, and using ionic liquids flame retardant to improve material’s multiple properties. The burst terms and time zone diagram’s results point out the combination of computational quantum chemistry to study the flame retardancy mechanism of ionic liquids, the study of fluorinated electrolytes, ionic liquids for smoke suppression, phosphorus-containing ionic liquids for flame retardant, and machine learning-assisted design of ILs flame retardants are the research frontiers and future research trends. Full article