Accident black spots are usually defined as road locations with a high risk of fatal accidents. A thorough analysis of these areas is essential to determine the real causes of mortality due to these ...accidents and can thus help anticipate the necessary decisions to be made to mitigate their effects. In this context, this study aims to develop a model for the identification, classification and analysis of black spots on roads in Morocco. These areas are first identified using extreme learning machine (ELM) algorithm, and then the infrastructure factors are analyzed by ordinal regression. The XGBoost model is adopted for weighted severity index (WSI) generation, which in turn generates the severity scores to be assigned to individual road segments. The latter are then classified into four classes by using a categorization approach (high, medium, low and safe). Finally, the bagging extreme learning machine is used to classify the severity of road segments according to infrastructures and environmental factors. Simulation results show that the proposed framework accurately and efficiently identified the black spots and outperformed the reputable competing models, especially in terms of accuracy 98.6%. In conclusion, the ordinal analysis revealed that pavement width, road curve type, shoulder width and position were the significant factors contributing to accidents on rural roads.
Objective The recently reported endoscopic finding of black spots is defined as black pigmentation in gastric mucosa. We attempted to clarify the relationship between the Helicobacter pylori ...infection status and black spot occurrence. Methods The study subjects were 1,600 individuals who underwent an annual medical checkup and whose H. pylori status could be determined. Upper endoscopic examinations were performed in all, and the presence of black spots in the stomach as well as the degree of gastric mucosal atrophy were determined. Results Among the 1,600 enrolled subjects, 784 underwent eradication for H. pylori, of whom 144 were originally H. pylori-positive and 672 H. pylori-negative. Black spots in the stomach were observed in 156 (9.8%). The rate of prevalence of black spots in the H. pylori-positive and H. pylori-negative subjects was 2.1% and 1.5%, respectively, while that in subjects after undergoing eradication of H. pylori was 18.2%. A multiple logistic regression analysis demonstrated that an older age and post-eradication status were significant factors for black spot occurrence, while proton pump inhibitor treatment showed a tendency to be a risk factor. In subjects with post-eradication status, a higher grade of gastric mucosal atrophy was a significant risk factor for the occurrence of black spots. Conclusion H. pylori post-eradication status and an older age were significant factors related to the appearance of black spots, and a higher grade of gastric mucosal atrophy was also a significant risk factor in subjects who had undergone successful eradication.
Roads are valuable assets worldwide that must be kept in good condition with minimum maintenance to safeguard against accident. From the literature review and the field observations, it is quite ...evident that geo-fields are one of the parameters which is responsible for damaging the road surface and hence further increasing the possibility of accidents. Present study is an attempt to provide a detailed insight into the performance of the road segment when subjected to geo-fields. For the same accident data of the Mumbai-Pune expressway, over six years from 2016 to 2021 has been used. Based on this data 46 accident black spots were segregated for investigation. An automated method is used to measure the pavement roughness index (PRI). On these spots, the quality of pavement is determined using the non– destructive test of Ultra Sonic Pulse Velocity (UPV). Geo-fields are measured in terms of electric and magnetic fields at these black spots. Data has been analyzed using Karl Pearson’s correlation coefficient and linear regression models are developed for the average number of road accidents (Ā) with respect to PRI, UPV and Geo-fields. The mathematical models developed may provide a useful link between road accidents, geo-fields, and pavement surface conditions. It will also help transport authorities not only to predict the number of accidents at particular spots envisaged on existing expressway but will also enable them to design pavements appropriately for the detrimental effects of weak electric and magnetic fields.
Road safety is the main problem in developing countries. Every year, millions of people die in road traffic accidents, resulting in huge losses of humankind and the economy. This study focuses on the ...road traffic accident analysis and identification of black spots on the Lahore-Islamabad Highway M-2. Official data of road traffic accidents were collected from National Highway and Highway Police (NH & MP) Pakistan. The data was digitized on MS Excel and Origin Pro. The accident Point weightage (APW) method was employed to identify the black spots and rank of the top ten black spots. The analysis shows that the trend of road traffic accidents on M-2 was characterized by a high rate of fatal accidents of 35.3%. Human errors account for 66.8% as the major contributing factors in road traffic accidents, while vehicle errors (25.6%) and environmental factors (7.6%) were secondary and tertiary contributing factors. The main causes of road traffic accidents were the dozing on the wheel (27.9%), the careless driving (24.6%), tyre burst (11.7%), and the brakes failure (7.4%). Kallar Kahar (Salt Range) was identified as a black spot (223 km, 224 km, 225 km, 229 km, and 234 km) due to vehicle brake failure. The human error was a major contributory factor in road traffic accidents, therefore public awareness campaign on road safety is inevitable and use of the dozen alarm to overcome dozing on the wheel. Doi: 10.28991/cej-2020-03091629 Full Text: PDF
The identification of accident black spots is of great significance for the prevention of traffic accidents. Commonly used accident black spot identification methods divide road sections for the ...analysis of accident data, the direct result of which is the splitting of accident black spots, which affects the results. This paper is based on three years of traffic accident data from the Beijing–Harbin Expressway, including the time and location of traffic accidents, form of the accident fatalities, severe injuries, slight injuries, and property damage only (PDO). To avoid road division effects, an identification method based on the accident spacing distribution is established by using quality control theory. The results show that the average number of accidents per kilometer by the method proposed in this paper is 42, which is much higher than 10, identified by other identification methods. The method proposed in this paper improves the accuracy of the identification results. This method avoids the problem of road segmentation found in other common methods and can more accurately reflect the spatial distribution of traffic accidents. Thus making the identification of accidents more scientific and accurate.
•Reviews and summarizes the identification methods of accident black spots.•Uses the Poisson distribution to avoid the division of road sections.•Introduces the concept of quality control management –3σ principle provide basis for the method.•Compared with other methods, the accuracy of the method proposed in the paper is higher.
This work assessed the pattern and distribution of criminal activities in Osun State Nigeria. It selected ten famous black-spots crime-area in the State using structured questionnaires and secondary ...data for household-heads and security outfits to obtain relevant data. Factor analysis and multiple regression techniques were employed to analyse data obtained.The findings indicated that most urban residents exhibited a significant higher-level of uncertainties but still want to remain in their ancestral-homes. Suggestions were put forward to governments and security agencies to play priority roles in securing people in their residential areas to conform to other cities of the world.
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•Polymer light-emitting electrochemical cells (PLECs) have been tested both intermittently and continuously for a long duration.•The reversible electrochemical doping process is a key ...factor that dictates the observed cell characteristics over time.•Doping causes fluorescence quenching and the apparent luminance decay, which are partly recoverable when the cell is allowed to relax.•Surprisingly, the formation of black spots is caused by chemical changes that have occurred only at the cathode interface during storage, and the black spots are in fact manifestation of localized heavy doping seeded by the chemical changes.
Polymer light-emitting electrochemical cells (PLECs) have been tested either continuously or intermittently for a long duration. In situ electrochemical doping of the polymer film causes fluorescence quenching and apparent luminance decay when the effect of quenching outweighs the effect on charge injection. The quenching-induced luminance loss, however, is partly recoverable when the cell is allowed to relax without an applied bias. The long test duration causes the appearance of large black spots in both photoluminescence and electroluminescence. Two very startling observations shed light on the nature of the black spots. First, black spot growth was completely suppressed when a cell was tested with a freshly deposited top aluminum electrode, even though the polymer film had been stored for up to nine months. Second, the black spots in photoluminescence gradually faded when the applied bias voltage was removed. The black spots in these PLECs were therefore sites of heavy doping that were promoted by changes that occurred at the cathode/polymer interface.
In improving road safety, identifying black spots based on safety potential is also known as identifying locations with potential saving in accident costs. Such identification is an attempt to make ...the selection of black spots which are most suitable to treat out of the identified ones. This paper intends to introduce an approach to identifying locations with potential saving in accident costs. In such approach, the key parameter used to assess the safety performance of road spots is the safety potential. This approach enables the identification of the black spots for which safety improvement measures are expected to have the greatest economical effectiveness. As a result, the approach is of great use to accident reduction in developing countries facing limited budgets for road safety improvement.
Road accidents, mostly on national highways, pose a significant public health and economic burden in Bangladesh, requiring in-depth analysis for road safety measures. This study comprehensively ...analyzes accident trends, characteristics, causes, and consequences by identifying the accident black spots on the Kushtia-Jhenaidah National Highway (N704). Accident records from 2017 to 2021 were collected from nearby police stations. Additionally, using a cluster random sampling approach, a questionnaire survey with 100 respondents (50% drivers and 50% general road users) was also conducted to capture diverse perceptions and behaviors. The study utilizes descriptive methods, such as trends analysis and frequency distributions, alongside spatial analysis techniques, including severity index, Kernel Density Estimation, and hotspot analysis. Findings indicate a decrease in accidents from 2018 to 2021, yet a concerning rise in fatalities in 2021. Trucks (47.9%) emerge as the primary contributor among 169 vehicles involved in accidents. Head-on collisions (36%) are prevalent, attributed to both human and environmental factors, including driver inexperience (56%), mobile phone use while driving (78%), lack of proper training (12%), overspeeding (28.3%), and nighttime driving (54%) influenced by seasons and land use. Mostly, victims aged from 20 to 40, where men are more affected by fatalities (70.7%) and women by injuries (86.3%). Out of 35 identified accident spots, including Battail, Bittipara Bazar, Laxmipur Bazar, Modhupur Bazar, IU Main Gate, Sheikhpara Bazar, and DM College Front, are designated as blackspot zones based on the frequency of accidents, deaths, and injuries. The study concludes by recommending targeted interventions, driver training, infrastructure improvements, regulatory measures, and victim assistance in collaboration with local and national agencies to enhance road safety and mitigate accident risks.
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