Road accidents have increased rapidly in recent years for a variety of reasons. Analyzing and visualizing road accidents through heatmaps can help improve policies for their prevention by informing ...about areas with a high-risk of road accidents.
The purpose of this research is to build a model for the analysis and visualization of road accidents through heatmaps. Information about road accidents is extracted from the news of the main online media portals through scripts in the Python language and Web Scraping techniques. From the extraction of about 30,000 articles from news portals for one year, only 829 were selected in the end that provided information about road accidents.
As a result, and contribution of this research, a corpus was built with the geographic coordinates of road accidents and on this data our model was applied for the analysis and visualization of high-risk areas of road accidents using heatmaps. The visualization of heatmaps was done through a Python script, where it was applied to the geographic coordinates of road accidents.
Actions related to the improvement of the safety of disabled road users have multiple levels and are burdened with problems related to the collection and proper analysis of road incidents. A ...meta-analysis of databases could provide a better understanding of the causes of these events and prevent them in the future. Currently, residual information on participants of road accidents can be found in the Accident and Collision Record System; the data are analyzed by the Polish Road Traffic Observatory and submitted to the International Road Traffic and Accident Database and the Community Road Accident Database. In connection with the above, an article was prepared containing a propaedeutic review of research materials to date, as well as domestic and foreign databases constituting the diagnostics of the research area. An international literature search was also conducted on accidents involving people with disabilities. The findings indicate the need to collect and expand information about disabled participants of road incidents, fill this gap in databases, and systematize them as the starting material for the development of remedial actions.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Road accidents are often caused by short abnormal events, including traffic violations, abrupt change in vehicular motion, driver fatigue, etc. Observing an accident event from the right camera ...perspective plays a crucial role while detecting accidents. However, it may not be possible to capture such abnormal events from a limited camera perspective. We present a deep learning framework to analyze the accident events recorded from multiple perspectives. First, we estimate feature similarity in videos recorded from multiple perspectives. We then divided the video samples into high and low feature similarity groups. Next, we extract spatio-temporal features from each group using two-branch DCNNs and fuse them using a rank-based weighted average pooling strategy followed by classification. We present a new road accident video dataset (MP-RAD), where each accident event is synthetically generated and captured from five independent camera perspectives using a computer gaming platform. Most of the existing road accident datasets use egocentric views or they are captured in fixed camera setups. However, our dataset is large and multi-perspective that can be used to validate ITS-related tasks such as accident detection, accident localization, traffic monitoring, etc. The dataset contains 400 accident events with a total of 2000 videos. We provide temporal annotations of all videos. The proposed framework and the dataset have been cross-validated with latest accident detection baselines trained on real-world road accident videos and vice-versa. The sub-optimal detection accuracy obtained using the baselines indicates that the proposed framework and the dataset can be useful for ITS related research. Code and dataset is available at: https://github.com/draxler1/MP-RAD-Dataset-ITS-
Road accidents are an essential issue for every country in the world because their consequences are devastating for the people involved in all senses. Speeding has been considered one of the main ...reasons for these tragedies. Therefore, the current research analyzed the relationship between speeding and severe accidents on the Pan-American highway in Peru. Publicly available data kept in a Peruvian official agency was employed. Methodologically, the logit regression was harnessed since the data were categorical. After the analysis, the research found that it was riskier to have severe accidents than speeding in urban areas crossing the highway and driving or being inside a truck.
Background: Road accidents are regarded as one of the most critical global health issues. In Iran, road accidents are the second cause of death, followed by cardiovascular diseases. The present study ...was conducted with the aim of the epidemiological evaluation of deaths caused by road accidents in Torbat Heydariyeh City, Iran, between 2013 and 2017. Materials and Methods: This is a cross-sectional study in which information on fatal road accidents recorded in the Forensic Medicine Organization of Torbat Heydariyeh City was collected from 2013 to 2017. Excel software was used to analyze the data. A total of 311 fatal accidents have been reported in Torbat Heydariyeh from 2013 to 2017. Results: The mean±SD age of the deceased was 39.55±22.71. Men accounted for 69% of deaths. Most road accidents occurred in 2016 with a percentage of 24%, most of which happened in the sixth month with a percentage of 13%. Head injury in road accidents was reported as the main cause of death (48%). 130 of the dead were passengers (42%). The type of vehicle used by victims of road accidents was motorcycles (25%), and pedestrians (18%). Conclusion: Since fatal road accidents impose direct and indirect costs on society, intervention measures, such as repairing the roads on accident-prone roads, installing warning signs, defined fines, etc., should be taken to improve public health and prevent the increasing trend of accidents in Iran.
Detection and localization of road accidents in real-time is an integral part of the Intelligent Transportation System (ITS). Even though the existing road accident detection methods show promising ...results, the process suffers from some drawbacks. For example, existing methods require a large number of sample videos for feature learning. Moreover, features such as temporal gradients or flow fields are time-consuming. To address these issues, we introduce a new method that uses objects and their positions to detect accidents in real-time. Apart from localization of the accident events in videos, we perform a high-level post processing to describe the severity and context of an accident. Firstly, we divide an input video into pre-accident, accident and post-accident stages to extract object interactions. These interaction proposals are then filtered using a refinement algorithm. We then adopt an iterative training procedure to classify normal and accident interactions. We also highlight the damaged zone using heat maps. Finally, we generate high-level textual descriptions to quantify the context and severity of an accident. We have trained the proposed model using offline setups. However, it can be deployed online to detect road accident events in real-time by taking the video inputs directly from the CCTV camera. Moreover, with a minimal supervision, the model can be retrained for online surveillance. Extensive experiments carried out on UCF Crime and CADP datasets reveal that the proposed framework achieves state-of-the-art performance when compared with the recently proposed accident event detection methods in terms of AUC (UCF Crime: 69.70% and CADP: 72.59%) and FAR (UCF Crime: 0.8 and CADP: 2.2). The high-level description of the accident is an added advantage that will certainly help the traffic police to react in a timely manner.
This paper proposes an evolved Self-Adaptive Interactive Navigation Tool (SAINT+) to reduce the delivery time of emergency services and to improve navigation efficiency for the vehicles influenced by ...accidents. To the best of our knowledge, SAINT+ is the first attempt to optimize the delivery of emergency services as well as the navigation routes of vehicles around accident areas. Based on the congestion contribution model of SAINT and aggregated information from vehicles in the vehicular cloud, we propose a virtual path reservation strategy for emergency vehicles to guarantee a fast emergency service delivery. We also develop an accident area protection scheme based on an adjusted congestion contribution matrix and protection zones to evacuate vehicles in the accident area. To further reduce travel delay of neighbor vehicles in the accident area, we also present a dynamic traffic flow control model. Through extensive simulations with a real-world map, SAINT+ outperforms other state-of-the-art schemes for the travel delay of emergency vehicles. In scenarios with a high vehicle density, SAINT+ reduces the travel delay of emergency vehicles by 42.2%.
Problem. Globally, car crashes are the major cause of death, killing 1.2 million people, and despite improvements in car safety, forecasts indicate that car crash deaths will increase significantly ...by 2030 due to the increase in the number of cars. Such a trend requires an increase in passive safety in the design of cars. It is also necessary to consider with these factors the most popular segments of SUV cars, which during an accident create more dangerous consequences in the event of a side impact, taking into account the mass and dimensions parameters. Goal. The aim is to conduct an analysis of the side collision mechanism of cars of different mass and dimensional parameters. Taking into account the trends in the sale of cars, identifying the most popular classes of cars in Ukraine both on the new car market and on the second-hand market, to further identify problems in testing cars according to various certification protocols. Methodology. The approaches to solving the tasks used in the work are based on the use of statistical data and comparative analysis of various methodologies and certification protocols. Results. Considering that scientific studies of frontal impact are presented by the scientific community in the broadest form, the study of the side impact of two cars is currently a relevant direction, taking into account the global trend towards the production of cars in the SUV segment, which exceed passenger cars in terms of mass and dimensions. In a road accident with a side impact of a passenger car and an off-road vehicle of the SUV segment, we will get a large difference in the height of the primary impact, which is 250 millimeters. That is, all the energy of the impact to the side of the passenger car falls not on the safety bar, but 250 millimeters higher, which will inevitably lead to fatal injuries to the driver and passenger. Unfortunately, the European NCAP and the US National Highway Traffic Safety Administration use moving barriers that are similar in terms of mass and dimensions to an average passenger car. Originality. The obtained results of the analysis of the mechanism of the car side collision make it possible to evaluate the current trend of the automobile market in terms of passive safety and, in particular, to conduct certification tests for side impact in a new way. Practical value. The obtained results can be recommended when studying the structural features of preparing and conducting crash tests.
Objetivo: Determinar el impacto que tuvieron las muertes por atropellos de peatones y colisiones entre vehículos sobre la esperanza de vida en Argentina durante el periodo 1998-2017. Material y ...métodos: Se obtuvieron las bases de datos sobre las causas de muerte, sexo, edad y jurisdicción de residencia de los fallecidos de la Dirección de Estadísticas e Investigación en Salud de Argentina. Se calcularon las tasas de mortalidad y el indicador de los años de esperanza de vida perdidos (AEVP) para determinar el impacto de la mortalidad vial. Resultados: Argentina redujo en un 13 % los fallecimientos por atropellos de peatones y choques entre vehículos durante los últimos 20 años. La tasa de mortalidad vial pasó de 12.0 a 10.6 defunciones cada 100 000 habitantes entre los trienios 1998-2000 y 2015-2017 respectivamente. Los decesos en el tránsito tuvieron mayor impacto entre los hombres de edades de 15 a 49 años. Al mismo tiempo, hubo un fuerte contraste del nivel de mortalidad vial registrado en cada una de las jurisdicciones del interior del país, donde las tasas de mortalidad oscilaron entre 1.2 y 24.1 decesos cada 100 000 habitantes. Conclusiones: Si bien hubo una disminución del nivel de mortalidad vial, las políticas públicas implementadas en Argentina no han logrado el objetivo de reducir a la mitad la cantidad de defunciones. Este flagelo sigue generando la destrucción y desarticulación de las familias del país. Es necesario la implementación de nuevos programas que apunten a reducir las conductas violatorias de las normas de tránsito.
