Analysis of the elderly pedestrian traffic accidents in urban scenarios: the case of the Spanish municipalities.

As the elderly population grows, there is a greater concern for their safety on the roads. This is particularly important for elderly pedestrians who are more vulnerable to accidents. In Spain, one of the most aged countries in the world, the elderly accounted for 70% of all pedestrian deaths in 2019. In this study, the focus was on analysing the occurrence of elderly pedestrian-vehicle collisions in Spanish municipalities and how it is related to the built environment. The study used the hurdle negative binomial model to analyse the number of elderly and non-elderly pedestrian accidents per municipality in 2016-2019. The exploratory analysis showed that cities above 50,000 inhabitants were safer for the elderly, and larger provincial capitals had lower elderly pedestrian traffic accident rates. The occurrence of all pedestrian traffic accidents was linked to the socio-demographic features. For elderly pedestrians, land use was found to be influential, with a lower proportion of land covered by manufacturing and service activities linked to a smaller number of accidents. Results showed that improving road safety for older pedestrians may not necessarily compromise the situation for the rest of population. Hence, policymakers should focus on infrastructure improvements adapted to the needs of elderly pedestrians.

24Model-based comparative analysis of two catastrophic hazardous chemical pipeline accidents.

Objectives. This study conducted a comparative analysis of two catastrophic pipeline accidents in China in order to identify some common mistakes and lessons learned to prevent similar accidents. Methods. The 24Model was used in this study, which provides a universal pathway for accident analysis from the individual level to the organizational level. Results. There were similarities between the two cases in the aspects of the occurrence, development, emergency and causation at different levels: both were caused by leaks of pipelines and evolved into multiple explosions during emergency response; both leaks were caused by the corrosion of pipelines in the confined space of a damp or salt-spray environment; both were classified as 'responsibility accidents', and unsafe acts, such as the failure to identify hidden hazards of pipelines that were the direct cause of accidents, reflected the shortcomings of individual safety habitual behaviour in terms of knowledge, awareness, habits and psychology; weaknesses in the organizational management mainly concerned hazard identification, pipeline maintenance, emergency disposal, etc.; and there is not a good safety climate within the organization. Conclusions. Organizations should develop a closed-loop management system and strengthen the construction of safety culture, and the government should supervise the implementation of procedures.

Influence of Blind Spot Assistance Systems in Heavy Commercial Vehicles on Accident Reconstruction.

Accidents between right-turning commercial vehicles and crossing vulnerable road users (VRUs) in urban environments often lead to serious or fatal injuries and therefore play a significant role in forensic accident analysis. To reduce the risk of accidents, blind spot assistance systems have been installed in commercial vehicles for several years, among other things, to detect VRUs and warn the driver in time. However, since such systems cannot reliably prevent all turning accidents, an investigation by experts must clarify how the accident occurred and to what extent the blind spot assistance system influenced the course of the accident. The occurrence of the acoustic warning message can be defined as an objective reaction prompt for the driver, so that the blind spot assistance system can significantly influence the avoidability assessment. In order to be able to integrate the system into forensic accident analysis, a precise knowledge of how the system works and its limitations is required. For this purpose, tests with different systems and accident constellations were conducted and evaluated. It was found that the type of sensor used for the assistance systems has a great influence on the system's performance. The lateral distance between the right side of the commercial vehicle and the VRU, as well as obstacles between them, along with the speed difference can have great influence on the reliability of the assistance system. Depending on the concrete time of the system's warning signal, the accident can be avoided or not by the driver when reacting to this signal.

Investigation of annual trucks fatal accidents in El Hajeb province of Morocco using TRIZ-Ishikawa diagram.

A stretch of road in the province of EL HAJEB, located in the central-south region of Morocco, is classified among the roadways experiencing an accumulation of fatal traffic accidents, with a particular involvement of freight transport vehicles. Investigation reports elaborated for these fatal accidents specify that these accidents occurred when drivers lost control of their vehicles due to brake system failures, resulting in multiple fatalities. However, these investigation reports did not provide root causes of this phenomena. Scientific research efforts in this field are directed toward preventive solutions and proposing a comprehensive analytical approach. This study aims to elucidate the mechanisms behind these specific accident phenomena on the identified stretch in the city of EL HAJEB. To achieve the study's objective and identify the triggering or contributing factors of these failures, we employed a novel approach combining the TRIZ and Ishikawa tools. This is a systematic methodology for analyzing potential causes of accidents, allowing us to clarify the intricacies of the specific phenomena leading to accidents while systematizing the analysis process, thus contributing to enhancing the effectiveness of investigative teams. This article contributes to introducing a new analytical tool in the field of accident analysis.

Identification of critical causes of construction accidents in China using a hybrid HFACS-CN model.

Construction safety is of significance since construction accidents can result in loss of property and large numbers of casualties. This research aims to identify the critical causes of construction accidents by introducing a hybrid approach. The hybrid approach is developed to identify the critical causes of construction accidents by combining the human factors analysis and classification system (HFACS) model with complex network (CN) theory. A total of 863 construction accident cases were collected, and 46 causal factors were identified. Subsequently, the accident causal network was established, and six critical causal factors were extracted. The hybrid analysis approach is demonstrated with a real construction accident case, and the results demonstrate that the hybrid approach could better identify the critical causal factors. Consequently, this research enables the enhancement of understanding the HFACS framework and CN theory, as well as a contribution to safety management in the construction industry at different levels.

Testing the reliability of accident analysis methods: a comparison of AcciMap, STAMP-CAST and AcciNet.

Accident analysis methods are used to model the multifactorial cause of adverse incidents. Methods such as AcciMap, STAMP-CAST and recently AcciNet, are systemic approaches that support the identification of safety interventions across sociotechnical system levels. Despite their growing popularity, little is known about how reliable systems-based methods are when used to describe, model and classify contributory factors and relationships. Here, we conducted an intra-rater and inter-rater reliability assessment of AcciMap, STAMP-CAST and AcciNet using the Signal Detection Theory (SDT) paradigm. A total of 180 hours' worth of analyses across 360 comparisons were performed by 30 expert analysts. Findings revealed that all three methods produced a weak to moderate positive correlation coefficient, however the inter-rater reliability of STAMP-CAST was significantly higher compared to AcciMap and AcciNet. No statistically significant or practically meaningful differences were found between methods in the overall intra-rater reliability analyses. Implications and future research directions are discussed.

Practitioners who undertake accident analysis within their organisations should consider the use of STAMP-CAST due to the significantly higher inter-rater reliability findings obtained in this study compared to AcciMap and AcciNet, particularly if they tend to work alone and/or part of relatively small teams.

Analysis of characteristics and causes of gas explosion accidents: a historical review of coal mine accidents in China.

Objectives This study aimed to provide greater insight into the characteristics of severe and extraordinarily severe gas explosion accidents (SESGEAs). Methods. The study analyzed the accident characteristics and causes of SESGEAs. As an example, we conducted a specialized case analysis using the 24Model (fourth edition) on the recent Baoma coal mine gas explosion. Results. SESGEA data are characterized by greater volatility, with significant differences in the geographical distribution, temporal distribution and attributed characteristics of the accidents. From the accident analysis: chaotic ventilation management was the most serious accident cause of SESGEAs; unsafe acts related to ventilation operations accounted for 18.51% of all unsafe acts; coal miners lack professional safety knowledge and have a serious fluke mentality in mining work; enterprises have insufficient enforcement of safety procedure documents, and lack of attention to the allocation of underground human resources and safety training systems; and the importance of safety, the role of the safety department and satisfaction with safety facilities have become the most serious missing items of safety culture. Conclusion. This study can provide important data support and management basis to assist mine operators in developing more targeted accident prevention strategies.

A case study of unavoidable accidents of autonomous vehicles.

Objective: Autonomous driving technology eliminates human errors, and thus it is a promising solution for reducing road traffic fatalities and injuries. While future autonomous driving technology may be able to reduce the number of collision accidents, it will not be able to avoid all collision accidents. This study is aimed to demonstrate why some accidents will still be unavoidable even with advanced perceiving and controlling capabilities.Methods: Because fully autonomous vehicles are currently in the laboratory stage, we used the prospective method to study the unavoidable accident of autonomous vehicles. Suitable traffic accident cases were screened from the China In-Depth Accident Study (CIDAS). Videos of the accidents were analyzed and the accidents were reconstructed using PC-Crash software. We assumed that target vehicle possesses near-perfect autonomous driving capabilities. Unavoidable accidents were determined based on vehicle dynamics and traffic constraints. The time from perceiving hazard to collision was calculated for each accident.Results: Among the 112 accidents screened, 15 cases of unavoidable accidents were identified. Three typical cases are presented in detail in this study. Based on the reasons why the target vehicles cannot avoid the collisions, we classified the unavoidable accidents into time-limit type and space-limit type. Time-limit means that vehicle cannot stop or steer out of danger in time, and space-limit means that the traffic environment does not have sufficient space for vehicle to avoid collision.Conclusions: Collision accidents will still occur even with perfect autonomous driving technology. We used the prospective method to investigate scenarios and characteristics of unavoidable accidents of autonomous vehicles. The time-limit type and the space-limit type were identified as two categories of unavoidable accidents. For the time-limit unavoidable accidents, the time from perceiving hazard to collision is typically not longer than 1.5s. The characteristics of unavoidable accidents and the estimated pre-crash warning time can provide some reference for establishing future occupant protection strategies. This study also showed the limitations of active safety and the necessity of passive safety.

Development of German pedelec (and bicycle) crashes between 2013 and 2021.

INTRODUCTION: The continuous growth in the use of e-bikes (in Germany mostly pedelecs that support pedaling up to 25 km/h) raises questions about the use of historic crash data for the development of road safety measures. The aim of this study was to address this issue, by conducting a longitudinal analysis of pedelec and bicycle crash data over a period of nine years to identify trends and to clarify whether such trends are specific to pedelecs. METHOD: We analyzed 95,338 police reported pedelec and bicycle injury crashes from 2013 through 2021. The dataset consisted of crashes from three federal states of Germany: Brandenburg, Hesse and Saxony. Data were analyzed with respect to sex and age distribution, time, location and type of accident, conflict partner, cause of crash and injury severity. RESULTS: Many of the analyzed variables showed a considerable degree of temporal stability, with differences as well as similarities between the two bicycle types staying quite consistent over the years. One notable difference was the mean age of the involved riders, with crashed pedelec riders being significantly older than conventional cyclists. At the same time, however, the mean age of these pedelec riders has decreased by eight years over time. Single vehicle crashes were consistently more common for pedelec riders than for cyclists. Similarly, pedelec rider crashes went with a higher injury severity over all the years. CONCLUSIONS AND PRACTICAL APPLICATIONS: While, on a more detailed level, we found differences between the two bicycle types, overall crash characteristics were remarkably similar and consistent over time. Our findings provide no clear argument for road safety measures that are specifically designed to target pedelecs. Instead, the stable crash total, and the increases in ridership of both bicycles and pedelecs, highlight the demand for new, innovative solutions to improve cycling safety in general.

Impact of Partially Automated Driving Functions on Forensic Accident Reconstruction: A Simulator Study on Driver Reaction Behavior in the Event of a Malfunctioning System Behavior.

Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The results show that none of the subjects could avoid leaving their lane and moving into the oncoming lane and, therefore, could not control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 s. The second scenario examined driver responses to phantom braking caused by AEBS. We found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered.

Assessing bicycle crash risks controlling for detailed exposure: A Copenhagen case study.

A better understanding of factors associated with bicycle crashes can inform future efforts to limit crash risks. Many previous studies have analysed crash risk based on crash databases. However, these can only provide conditional information on crash risks. A few recent studies have included aggregate flow measures in their crash risk analyses. This study incorporates detailed bicycle flow to investigate factors related to bicycle crashes. Specifically, the study assesses the relative crash risk given various conditions by applying Palm distributions to control for exposure. The study specifically investigates the relationship between weather and time conditions and the relative risk of bicycle crashes at a disaggregate level. The study uses bicycle crash data from police reports of bicycle crashes from 2017-2020 in the greater Copenhagen area (N = 4877). The relations between the bicycle crash risk and the air temperature and wind speeds are found to be highly non-linear. The relative risk of bicycle crashes is elevated at low and high temperatures (0 °C ¿ x, x ¿ 21 °C). The results also show how decreasing visibility relates to increasing bicycle crash risk. Meanwhile, cycling during the early morning peak (7-8) and afternoon peak hours (15-18) is related to an increased risk of bicycle crashes. While some of the effects are likely spurious, they highlight specific conditions associated with higher relative risk. Finally, the results illustrate the increased risk at weekend night times when cyclists are likely to bike under the influence of alcohol. In conclusion, the analysis confirms that visibility, slippery surfaces, and intoxication are all factors associated with a higher risk of bicycle crashes. Hence, it is relevant to consider how infrastructure planning and preventive measures can modify the bicycle environment to minimise these risks.

Safety accident analysis of power transmission and substation projects based on association rule mining.

To achieve the sustainable development goals (SDGs) of power transmission and substation project construction, statistical analysis was used to provide an outline of safety accidents, the 4M1E method was applied for sorting out and analyzing the risk factors, and the Apriori algorithm was carried out for exploring the intrinsic interaction among risk factors based on association rule mining. The results showed that the safety accidents that happen in the construction of power transmission and substation projects were not much frequent, but deadly; the process of foundation construction and high fall was the most accident-prone process and injury type respectively. In addition, human behaviors were the foremost factors leading to accidents, and there was a strong correlation among the risk factors of low project management level, lack of safety awareness, and poor risk identification ability. For improving the security situation, measures should be taken for controlling human factors, performing flexible management, and strengthening safety training. In further research, more detailed and diversified accident reports and case data should be analyzed, and more consideration should be put on the weighted risk factor analysis to obtain more comprehensive and objective safety accident analysis results for power transmission and substation projects. This study highlights the risks in power transmission and substation project construction and introduces a novel method for better analyzing the intrinsic interaction among risk factors, which provides theoretical support for related departments to conduct sustainable safety management.

Burden of injury due to occupational accidents and its spatiotemporal trend at the national and subnational levels in Iran, 2011-2018.

PURPOSE: The spatiotemporal trend of the burden of injury due to occupational accidents in Iran, 2011-2018 were assessed at the national and subnational levels. METHODS: The burden of occupational injury was estimated using three datasets of occupational injury data, the employed population, and duration and disability weight of injuries. RESULTS: The disability-adjusted life years (DALYs), deaths, DALY rate, and death rate (per 100,000 workers) of occupational injury in Iran drastically decreased from 169,523, 2,280, 827, and 11 in 2011 to 86,235, 1,151, 362, and 5 in 2018, respectively. The DALY rates of occupational injury were significantly different by gender and age in a manner that the DALY rate of men was much higher than that of women and the DALY rates by age group in 2018 ranged from 98 for 50 y and over to 901 for 15-19 y. The shares of injury outcomes in the total DALYs in 2018 were as follows: 63.6% for fatal injuries, 17.4% for fracture, 7.9% for open wound, 7.3% for amputation, and 3.8% for other injuries. Over 83% of the DALYs was observed in three economic activity groups of construction, manufacturing, and community, social, and personal service activities. The three provinces with the highest DALY rates in 2018 were Markazi, West Azarbaijan, and East Azarbaijan, respectively. CONCLUSION: Despite the decreasing temporal trend, the burden of occupational injury in Iran in 2018 was high. The high-risk groups and hot spot provinces should be taken into more consideration for further reduction of the injury burden.

Analysis of profitability of Pay-As-You-Speed scheme.

OBJECTIVE: Implementing usage-based insurance (UBI) schemes captured the attention and has found a better practical foundation, thanks to the presence of probes for recording the driving and traveling data. The UBI is believed to provide an incentive measure through premium discounts for correcting driving and traveling behavior. However, the success of UBI implementation is dependent on different factors including the presence of alternative insurance plans, the level of privacy concerns among society, and the amount of trust within the society. Therefore, designing proper discount schemes which affect UBI acceptance by drivers and its profitability for government and insurance companies differs across countries and different scenarios. We aim to investigate the profitability of UBI Pay-As-You-Speed in Iran with a focus on the government and insurance companies. This study will be beneficial for policymakers seeking to understand the potential impact of UBI Pay-As-You-Speed in Iran. METHODS: The research is conducted on a synthesized population with acceptance and accident frequency models based on a self-reported survey. We assumed six UBI schemes based on previous research. The acceptance model is a logit discrete choice model and the accident frequency is based on Poisson regression. Costs of crashes are estimated based on one-year data of the Central Insurance company in Iran. After models' estimation, the simulated population is used to estimate the resultant profit of private insurance companies and government. RESULTS: It is found that the scheme with no premium discount and no rental prices for the required monitoring device, results in the highest revenue for the government. Moreover, with an increase in the probe penetration rate, the profitability of the government increases with a greater reduction in crashes. However, this trend is not observed for insurance companies because the cost of the monitoring device and premium discounts offset the profits gained from prevented crashes. CONCLUSION: The presence of the government as a main actor in facilitating the implementation of UBI schemes is essential or private insurance companies would be reluctant to provide these schemes to customers.

Hero or hazard: A systematic review of individual differences linked with reduced accident involvement and influencing success during emergencies.

Objectives: This review aimed to integrate previous research to gain a deeper understanding of which individual factors are associated with reduced accident involvement, and which factors may be linked to success during emergency situations when they do occur. Better understanding how the human will react in these situations, combined with technological enhancements is vital to risk mitigation and ensuring successful performance. This review will also identify gaps in the literature that have yet to be addressed. Method: A systematic literature review was undertaken, beginning with 18,319 articles from three multidisciplinary databases. After careful review and exclusion, a final sample of 22 relevant articles were retained. This analysis was spread across various high risk, sociotechnical industries, including aviation, rail, mining, nuclear power, etc. Findings: The findings show that previous research has identified cognitive ability, leadership, situation awareness, personality, and risk perception as the most prominently considered factors in reducing accident involvement. Training, skill, situation awareness, and emotional stability were the most commonly associated factors to success through emergencies. Conclusion: While the research around individual differences impacting success during emergencies is scarce, this review provides future direction on potential factors influencing reduced accident involvement and/or potential factors that could influence a person's success through a disaster or emergency. This information could be implemented in recruitment and training of front-line workers in high-reliability organisations to reduce risk, increase safety and work towards reducing the number of accidents.

A content-aware corpus-based model for analysis of marine accidents.

In the past decades, marine accidents brought the serious loss of life and property and environmental contamination. With the accumulation of marine accident data, especially accident investigation reports, compared with subjective reasoning based on expert experience, data-driven methods for analysis and accident prevention are more comprehensive and objective. This paper aims to develop a content-aware corpus-based model for the analysis of marine accidents to mine the accident semantic features. The general research framework is established to combine accident data, expert prior knowledge, and semi-automated natural language processing (NLP) technology. The NLP models are optimized, fused, and applied to the case study of ship collision accidents. The results show that the proposed model can accurately and quickly extract hazards, accident causes, and scenarios from the accident reports, and perform semantic analysis for the latent relationships between them to extend the accident causation theory. This study can provide a powerful and innovative analysis tool for marine accidents for maritime traffic safety management departments and relevant research institutions.

Cause-responsibility analysis of occupational accidents in an automotive company.

The aim of this study was to determine the root causes of accidents and the responsibility rates of the parties involved in those accidents. For this purpose, 20 important accidents of an automotive company were selected and the root causes, the parties involved in the accidents and the respective responsibility rates were determined by 10 experts based on dividing into 11 Tripod Beta basic risk factors and using occupational accident tree analysis (OATA) and occupational accident component analysis (OACA) techniques. The results revealed that among the defects in the management system, the organizational system's defects had the greatest impact on the occurrence of occupational accidents. By modifying about half of the basic risk factors, 80% of occupational accidents can be controlled. Also, by focusing on monitoring and design units, the company's accidents can be reduced by up to 50%.

Factors That Affect Drivers' Perception of Closing and an Immediate Hazard.

OBJECTIVE: To measure the looming threshold for when drivers perceive closing and an immediate hazard and determine what factors affect these thresholds. BACKGROUND: Rear-end collisions are a common type of crash. One key issue is determining when drivers first perceive they need to react. The looming threshold for closing and an immediate hazard are critical perceptual thresholds that reflect when drivers perceive they need to react. METHOD: Two driving simulator experiments examined whether engaging in a cell phone conversation and whether the complexity of the roadway environment affect these thresholds for the perception of closing and immediate hazard. Half of the participants engaged in a cognitive task, the last letter task, to emulate a cell phone conversation, and all participants experienced both simple and complex roadway environments. RESULTS: Drivers perceived an immediate hazard later when engaged in a cell phone conversation than when not engaged in a conversation but only when the driving task was relatively less demanding (e.g., simple roadway, slow closing velocity). Compared to simple scenes, drivers perceived closing and an immediate hazard later for complex scenes but only when closing velocity was 30 mph (48.28 km/h) or greater. CONCLUSION: Cell phone conversation can affect when drivers perceive an immediate hazard when the roadway is less demanding. Roadway complexity can affect when drivers perceive closing and an immediate hazard when closing velocity is high. APPLICATION: Results can aid accident analysis cases and the design of driving automation systems by suggesting when a typical driver would respond.

John Senders, Human Error, and System Safety.

OBJECTIVE: I examine John Senders' work and discuss his influence on the study of error causation,error mitigation, and sociotechnical system safety. BACKGROUND: John Senders' passing calls for an evaluation of the impact of his work. METHOD: I review literature and accident investigation findings to discuss themes in Senders' work and potential associations between that work and error causation and system safety. RESULTS: Senders consistently emphasized empirical rigor and theoretical exploration in his research, with the desire to apply that work to enhance human performance. He has contributed to changing the way error has been viewed, and to developing and implementing programs and techniques to mitigate error. While a causal relationship between Senders' work and safety cannot be established, an association can be drawn between his research and efforts to mitigate error. CONCLUSION: Because of Senders' work, we have a better understanding of error causation and enhanced ways of mitigating system errors. However, new sources of error, involving advanced systems and operators' knowledge and understanding of their functionalities can, if not addressed, degrade system safety. APPLICATION: Modifications to advanced automation and operator training are suggested, and research to improve operator expertise in interacting with automated systems proposed.

Towards a unified model of accident causation: refining and validating the systems thinking safety tenets.

The systems thinking tenets were developed based on a synthesis of contemporary accident causation theory, models and approaches and encapsulate 15 features of complex systems that interact to create both safety and adverse events. Whilst initial testing provided supportive evidence, the tenets have not yet been subject to formal validation. This article presents the findings from a three-round Delphi study undertaken to refine and validate the tenets and assess their suitability for inclusion in a unified model of accident causation. Participants with expertise in accident causation and systems thinking provided feedback on the tenets and associated definitions until an acceptable level of consensus was achieved. The results reduced the original 15 tenets to 14 and 10 were identified as important to include in unified model of accident causation. The refined systems thinking tenets are presented along with future research directions designed to facilitate their use in safety practice.Practitioner summary: This article presents a refined and validated set of systems thinking tenets which describe features of complex systems that interact to create adverse events. The tenets can be used by practitioners to proactively identify safety leading indicators and contributory factors during adverse event analysis.