With increase in traffic volume across the globe traffic safety has come into highlight and become a major concern. Apparently, with due increase in traffic volume resulting in higher road accidents ...which considerably causes negative impact on economic growth, public health and general welfare of wellbeing. In the present scenario challenges are faced to mitigate the blackspots and by making road users aware with road safety parameters which may results in less road fatalities. The root cause of an accidents intends to perception, intellection emotion and violation. The approach towards this research is to get minimal setback/casualties of the road. In order to gain the best possible course of action, the stretch of 8 KM of National highway (NH-66) situated in a plain terrain in the district of Alapphuza, Kerala India. To begin with, accident data has been collected from NHAI office and Police station of above location with proper analysis by Accident Severity Index (ASI) method has been carried out. Adding to an idea, location of Black Spot has been identified by ASI method. Based on Severity of accident short term and long-term measures has been adopted. Eventually, after analyzing short term measures 10 black spot location along with the estimate has been worked out.
Sustainable transportation goals include an improvement in the level of road safety worldwide. It is well known that traffic accidents are one of the major causes of death worldwide. Black spots are ...road locations with a higher than statistically expected number of accidents. Remedying black spots would decisively improve road safety. A literature review of black spot identification methods, i.e., accident numbers, accident rates related to exposure, severity of accidents, Poisson and quality control methods, is presented within the framework of this paper. The various approaches adopted by key European and other countries are also summarized and evaluated. An important parameter is the unit length of a road, where accidents are referred. The quality of accident records is also critical. It is concluded that the coupling of statistical and accident severity index methods can contribute to assessing road infrastructure in a more holistic way and, therefore, in providing more reliable results with regard to the road safety level. The design and implementation of effective road safety strategies, based on black spot analysis, can be of great value for the decision makers and decision takers who are involved in the development of a sustainable transportation system.
This research aimed to examine the spatial distribution of road traffic accidents in Budapest, Hungary. The primary objective was to identify the factors associated with traffic accidents on the ...city's transportation network and to determine the locations of the most frequent accidents during peak and off-peak hours. A quantitative methodology was employed in this study, utilizing a dataset of recent accidents that occurred between 2019 and 2021, classified into peak and off-peak incidents. The data was analyzed using Python software and Quantum Geographic Information System (QGIS) tools for big data analytics. These programs enabled the creation of spatial maps of the study area and the identification of accident spots based on latitude and longitude information. A decision tree classification approach was used in the machine-learning method implemented with Python software. Additionally, the dataset file was uploaded to QGIS, which applied the heatmap (Kernel Density Estimation) algorithm to identify accident hotspots. The study findings revealed that the city center was the most common location for accidents overall, with peak and off-peak times, lanes, and days of the week investigated as potential contributing factors. The target variable was the number of accidents involving serious and minor injuries, which were found to be significantly associated with the identified accidents in this study.
Identifying black spots effectively and accurately is a pivotal and challenging task to improve road traffic safety. A novel black spot identification model is proposed by integrating the GIS-based ...processing with hierarchical density-based spatial clustering of applications with noise. Additionally, the optimal clustering parameters are determined based on an internal validation indicator called the density-based clustering validation index to minimize the impact of subjectivity in parameter selection. The model is validated by collecting 3536 accident data from 1 August to 31 October 2020 in Hangzhou, China, and eventually identifies 39 black spots. The results show that: (1) The number of accidents contained in black spots account for 75% of all accidents, while the length of network in the black spots only account for 23.26% of the total road network length. (2) Compared with the conventional density-based spatial clustering of applications with noise model and K-means model, the proposed model achieves the best performance with more accidents gathered per unit road length. (3) The sample survey with 6 onsite of the identified black spots indicates that the proposed model has high recognition accuracy and recommend these sites for further investigation.
The primary goal of the pavement is to provide a safe and smooth riding surface. Few research studies have explored the influence of geopathic stress in road accidents. Still, its effect on the ...pavement distresses and, as a result, on-road accidents are yet to be explored. This research aims to formulate regression models between the average number of accidents with geopathic stress and Pavement Condition Index (PCI) values. For Pune city, 36 accident black spots on the flexible pavement are considered, and accident data from 2016 to 2020 has been used. On each spot, the Pavement Condition Index (PCI) is determined using the traditional, precise manual method as per IRC 82:2015. Geopathic stress is measured using the innovative NAAV meter instrument. In the NAAV meter due to the influence of geopathic stress, the laser beam deviates, which can be visually observed; which is not possible with other devices such as Esmog Spion and magnetometer. Three linear regression models are developed. The first one relates the average number of road accidents (Ā) with the Pavement Condition Index (PCI). In contrast, the second one relates (Ā) with the electric field output on account of the interference of geopathic stress with a laser beam emitted from the source in the NAAV meter, (NR) in microamperes. Equation three relates the pavement condition index (PCI) with (NR) as well. It is found that the number of accidents increases on distressed spots with the increase in geopathic stress. The mathematical models developed would effectively establish a relationship between road accidents, geopathic stress, and pavement surface condition. This would further enable transportation authorities to predict the number of road accidents at specific locations on existing pavement. In addition, transport authorities can economize at the road maintenance cost by identifying critically distressed sections at black spots which are severely impacted by weak electromagnetic fields emanating from the subgrade on account of the geopathic stress.
Trichothecium roseum
is an important pathogen and causes moldy core and black spots on apple fruit. The effects of temperature, moisture and nutrition on conidial germination, survival, colonization ...and sporulation of
T. roseum
were examined in controlled environments. The results revealed that external nutriments, such as extracts from apple fruit and flower promoted the conidial germination. The temperature required for conidial germination and sporulation of
T. roseum
ranged from 10 °C to 35 °C, with an optimum at approximately 28 °C. No conidia were produced at 35 °C, although conidia germinated at this temperature. The lethal temperature for the conidia was 46 °C and the conidia survived for 6.8 days at 40 °C. The most favorable moisture for conidial germination and sporulation of the pathogen was 95% relative humidity (RH). The humidity limit was RH = 90% for the conidial germination and RH = 70% for the fungal sporulation. At the optimum temperature, the fungi finished one generation (i.e., from conidial germination to sporulation) was no more than two days in
Malus micromalus
flowers, although the conidia germinated more slowly in vitro. Conidial germination and sporulation dynamics of
T. roseum
were well described by modified logistic models. The results can be used to develop disease forecasting model and help improving fungicide control of the disease.
For the purpose of reducing the harm of expressway traffic accidents and improving the accuracy of traffic accident black spots identification, this paper proposes a method for black spots ...identification of expressway accidents based on road unit secondary division and empirical Bayes method. Based on the modelling ideas of expressway accident prediction models in HSM (Highway Safety Manual), an expressway accident prediction model is established as a prior distribution and combined with empirical Bayes method safety estimation to obtain a Bayes posterior estimate. The posterior estimated value is substituted into the quality control method to obtain the black spots identification threshold. Finally, combining the Xi'an-Baoji expressway related data and using the method proposed in this paper, a case study of Xibao Expressway is carried out, and sections 9, 19, and 25 of Xibao Expressway are identified as black spots. The results show that the method of secondary segmentation based on dynamic clustering can objectively describe the concentration and dispersion of accident spots on the expressway, and the proposed black point recognition method based on empirical Bayes method can accurately identify accident black spots. The research results of this paper can provide a basis for decision-making of expressway management departments, take targeted safety improvement measures.
Traffic accidents in urban areas lead to reduced quality of life and added pressure in the cities’ infra-structures. In the context of smart city data is becoming available that allows a deeper ...analysis of the phenomenon. We propose a data fusion process from different information sources like road accidents, weather conditions, local authority reports tools, traffic, fire brigade. These big data analytics allow the creation of knowledge for local municipalities using local data. Data visualizations allow big picture overview. This paper presents an approach to the geo-referenced accident-hotspots identification. Using ArcGIS Pro, we apply Kernel Density and Hot Spot Analysis (Getis-Ord Gi*) tools, identifying the existence of black spots in terms of location and context conditions, and evaluate the possible human, environmental and circumstantial factors that may influence the severity of accidents. The results were validated by an expert committee. This approach can be applied to other cites wherever this data is available.
Abstract
Road accidents have presently become an major social worry in India which are increasing year by year. These road accidents lead to loss of human life, injuries and property damage which is ...very serious concern. As per the Sustainable Development Goals (SDG): 2030 relating to transport infrastructure provision of access to safe, accessible, and sustainable transport is the need of the hour. Therefore, road safety becomes very important issues in today’s scenario. In this paper, road safety analysis was done on NH-103 stretch to identify accident/crash black spots. The accidental data was collected from police stations and visual surveys on two lane NH-103 stretch of 58 km. The analysis has been done by using ranking and severity method, accident severity index (ASI) method and accidental density method. and accidental black spots were indentified. It has been found that 6 accidental crash black spots have been identified namely BS-1, BS-2, BS-3, BS-4, BS-5, and BS-6. The reasons for accidents in these blackspots have been traced to suggest counter measures for reduction in number of accidents on this stretch.
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