Bicycles are employed as means of transportation across various age groups, from young students to the elderly, for work, education, health, and leisure trips. Despite not achieving high speeds, ...bicyclists remain vulnerable to severe and even fatal injuries when they are involved in traffic accidents. Although the rising awareness of ecological issues and traffic law enforcement mean that cyclists are increasingly susceptible to road traffic crashes and injuries. Injuries resulting from a traffic accident involving cyclists can show distinct and specific characteristics depending on the manner of occurrence. The aim of this study is to provide a systematic review of the literature on injuries sustained in cyclists involved in road accidents describing and analysing elements useful for forensic assessment. The literature search was performed using PubMed, Scopus, and Web of Science from January 1970 to March 2023. Eligible studies have investigated issues of interest to forensic medicine about traffic accidents involving bicycles. A total of 128 studies satisfied the inclusion criteria and were categorized and analyzed according to the anatomical regions of the body affected (head, neck, thoraco-abdominal, and limb injuries), and the assessment of lesions in reconstruction of the bicycle accident was examined and discussed. This review highlights that injuries resulting from a traffic accident involving cyclists can show distinct and specific characteristics depending on the manner of occurrence and the energy levels involved in the crash. The assessment of injuries offers valuable insights that integrated with circumstantial and engineering data perform the reconstruction of accident dynamics.
•Bicycle riders are susceptible to high and low-energy impacts, each associated with distinct fatal injury patterns.•The unique injury patterns found in bike riders can relate to helmet usage or not and to bike structural components.•Features of the injuries help in reconstructing the accident dynamics, combined with circumstantial and engineering data.
Abstract Background This study addresses the persistent global burden of road traffic fatalities, particularly in middle-income countries like Malaysia, by exploring the impact of the COVID-19 ...pandemic on Road Traffic Accident (RTA) fatalities in Perak state, Malaysia, with a secondary focus on applying Years of Life Lost (YLL) to understand the implications of these premature deaths. Methodology The cross-sectional study retrospectively reviewed certified RTA fatalities from 2018 to 2021, individually counting fatalities in accidents and excluding cases with incomplete death profiles. Data were collected from all Forensic Departments in the government hospitals in Perak. RTA fatalities were confirmed by medical officers/physicians following established procedures during routine procedures. A total of 2517 fatal accident and victim profiles were transcribed into data collection form after reviewing death registration records and post-mortem reports. Inferential analyses were used for comparison between pre- and during COVID-19 pandemic. The standard expected YLL was calculated by comparing the age of death to the external standard life expectancy curve taking into consideration of age and gender in Malaysia. Results This study included 2207 (87.7%) of the RTA fatalities in Perak State. The analysis revealed a decreasing trend in RTA deaths from 2018 to 2021, with a remarkable Annual Percent Change (APC) of -25.1% in 2020 compared to the pre-pandemic year in 2019 and remained stable with lower APC in 2021. Comparison between pre-pandemic (2018–2019) and pandemic years (2020–2021) revealed a difference in the fatality distribution with a median age rise during the pandemic (37.7 (IQR: 22.96, 58.08) vs. 41.0 (IQR: 25.08, 61.00), p = 0.002). Vehicle profiles remained consistent, yet changes were observed in the involvement of various road users, where more motorcycle riders and pedestrian were killed during pandemic ( p = 0.049). During pandemic, there was a decline in vehicle collisions, but slight increase of the non-collision accidents and incidents involving pedestrians/animals ( p = 0.015). A shift in accident from noon till midnight were also notable during the pandemic ( p = 0.028). YLL revealed differences by age and gender, indicating a higher YLL for females aged 30–34 during the pandemic. Conclusion The decline in RTA fatalities during COVID-19 pandemic underscores the influence of pandemic-induced restrictions and reduced traffic. However, demographic shifts, increased accident severity due to risky behaviors and gender-specific impacts on YLL, stress the necessity for improved safety interventions amidst evolving dynamics.
Distracted driving attributable to the performance of secondary tasks is a major cause of motor vehicle crashes both among teenagers who are novice drivers and among adults who are experienced ...drivers.
We conducted two studies on the relationship between the performance of secondary tasks, including cell-phone use, and the risk of crashes and near-crashes. To facilitate objective assessment, accelerometers, cameras, global positioning systems, and other sensors were installed in the vehicles of 42 newly licensed drivers (16.3 to 17.0 years of age) and 109 adults with more driving experience.
During the study periods, 167 crashes and near-crashes among novice drivers and 518 crashes and near-crashes among experienced drivers were identified. The risk of a crash or near-crash among novice drivers increased significantly if they were dialing a cell phone (odds ratio, 8.32; 95% confidence interval CI, 2.83 to 24.42), reaching for a cell phone (odds ratio, 7.05; 95% CI, 2.64 to 18.83), sending or receiving text messages (odds ratio, 3.87; 95% CI, 1.62 to 9.25), reaching for an object other than a cell phone (odds ratio, 8.00; 95% CI, 3.67 to 17.50), looking at a roadside object (odds ratio, 3.90; 95% CI, 1.72 to 8.81), or eating (odds ratio, 2.99; 95% CI, 1.30 to 6.91). Among experienced drivers, dialing a cell phone was associated with a significantly increased risk of a crash or near-crash (odds ratio, 2.49; 95% CI, 1.38 to 4.54); the risk associated with texting or accessing the Internet was not assessed in this population. The prevalence of high-risk attention to secondary tasks increased over time among novice drivers but not among experienced drivers.
The risk of a crash or near-crash among novice drivers increased with the performance of many secondary tasks, including texting and dialing cell phones. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Highway Traffic Safety Administration.).
The increase in the number of tourists visiting many destinations in Greece could lead to spillover effects on the safety of tourists with road traffic accidents being the major contributor to the ...morbidity and mortality of travellers worldwide. We employ data from 51 Greek regions (NUTS-3) during the period 2000–2017 to investigate the role of tourism in road accidents. We examine whether road accidents are affected by factors such as tourism, economic, demographic, meteorological, and risk exposure variables. We reveal that tourism affects road accidents in Greece, and that foreign tourists have a significant influence in this regard. Domestic tourists have a significant effect on non-fatal accidents, unlike foreign travellers, who covary more with cases of severe injuries and fatalities. There is a positive relationship between the number of road traffic accidents and tourism; more and longer stays of tourists coincide with increased vehicular collisions. Our findings suggest that domestic and foreign tourists are important to the national road safety policy plan, and that policymakers should be aware of this.
Road telematics and driver assistance systems offer a real opportunity to aid mobility and road safety. However, they also raise numerous questions. Problems related to the design and evaluation of ...intelligent driver support systems (IDSSs) and social perspectives related to their large scale introduction may only be fully addressed from a multi-disciplinary viewpoint. People from both engineering and social sciences, should be involved and this book provides such knowledge from both a human and social factors perspective.
•Automatic driving stress detection system in physiological records was proposed.•Features were extracted from multimodal analysis.•Efficient feature selection and reduction methods were ...employed.•Several kernel-based classifiers were adopted and compared.•Our proposed method shows a promising application in intelligent vehicle systems.
Monitoring driving status has great potential in helping us decline the occurrence probability of traffic accidents and the aim of this research is to develop a novel system for driving stress detection based on multimodal feature analysis and kernel-based classifiers. Physiological signals such as electrocardiogram, galvanic skin response and respiration were record from fourteen drives executed in a prescribed route at real drive environments. Features were widely extracted from time, spectral and wavelet multi-domains. In order to search for the optimal feature sets, Sparse Bayesian Learning (SBL) and Principal Component Analysis (PCA) were combined and adopted. Kernel-based classifiers were employed to improve the accuracy of stress detection task. Analysis I used features from 10s intervals of data which were recorded during well-defined rest, highway and city driving conditions to discriminate three levels of diving stress achieving an averaging accuracy over 99% at per-drive level and 89% in cross-drive validation. Analysis II made continuous stress evaluation throughout a complete driving test attaining a high coincidence with the true road situation especially at the switching interval of traffic conditions. Experimental results reveal that different levels of driving stress can be characterized by specific set of physiological measures. These physiological measures could be applied to in-vehicle intelligent systems in various approaches to help the drivers better manage their negative driving status. Our design scheme for driving stress detection could also facilitate the development of similar in-vehicle expert systems, such as driver's emotion management, driver's sleeping onset monitoring, and human-computer interaction (HCI).
Abstract
Background
Injuries caused by RTA are classified under the International Classification of Diseases-10 as ‘S00-T99’ and represent imbalanced samples with a mortality rate of only 1.2% among ...all RTA victims. To predict the characteristics of external causes of road traffic accident (RTA) injuries and mortality, we compared performances based on differences in the correction and classification techniques for imbalanced samples.
Methods
The present study extracted and utilized data spanning over a 5-year period (2013–2017) from the Korean National Hospital Discharge In-depth Injury Survey (KNHDS), a national level survey conducted by the Korea Disease Control and Prevention Agency, A total of eight variables were used in the prediction, including patient, accident, and injury/disease characteristics. As the data was imbalanced, a sample consisting of only severe injuries was constructed and compared against the total sample. Considering the characteristics of the samples, preprocessing was performed in the study. The samples were standardized first, considering that they contained many variables with different units. Among the ensemble techniques for classification, the present study utilized Random Forest, Extra-Trees, and XGBoost. Four different over- and under-sampling techniques were used to compare the performance of algorithms using “accuracy”, “precision”, “recall”, “F1”, and “MCC”.
Results
The results showed that among the prediction techniques, XGBoost had the best performance. While the synthetic minority oversampling technique (SMOTE), a type of over-sampling, also demonstrated a certain level of performance, under-sampling was the most superior. Overall, prediction by the XGBoost model with samples using SMOTE produced the best results.
Conclusion
This study presented the results of an empirical comparison of the validity of sampling techniques and classification algorithms that affect the accuracy of imbalanced samples by combining two techniques. The findings could be used as reference data in classification analyses of imbalanced data in the medical field.
The study presented an approach that integrated kernel density estimation (KDE) algorithm and spatial autocorrelation analysis, which helped to determine traffic accident (TA) hotspot locations and ...simultaneously evaluate the statistical significance of the hotspot clusters. Firstly, hotspots were identified by applying a GIS-based KDE algorithm. Secondly, the hotspot clusters were evaluated in terms of statistical significance by applying the Moran's I statistic indices. Finally, hotspots were arranged according to their significance. TA data in the (2015-2017) period in Hanoi, Vietnam were applied to test this approach. Importantly, the study proposed a validation process for the results by applying the Gi* statistics method to validate the (H-H) clusters and the EPDO method to validate the ranking of hotspots. The results showed that this integration overcame the drawbacks of the KDE method. The statistical test process of clusters helped to hinder the occurrence of too many clusters that were determined by the KDE method because they were not really dangerous. This approach was helpful and precise in identifying TA hotspots with the statistical meaning. These outcomes will not only enable traffic authorities to comprehensively understand the reasons for each accident but also to help them manage and deal with hazardous areas according to the prior order in case of limited expenses and allocate traffic safety sources accordingly.
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