scholarly journals ASI Based Identification and Prioritization of Accident Black Spot

2021 ◽  
Vol 9 (9) ◽  
pp. 1728-1734
Author(s):  
K. N. Thakare
Keyword(s):  
Black Spot ◽  
Severity Index ◽  
Motor Vehicles ◽  
Economic Losses ◽  
The Road ◽  
Black Spots ◽  
Accident Severity ◽  
Severity Index Score ◽  
Accident Data ◽  
Crucial Part

Abstract: The number of motor vehicles on road increased spectacularly which causing major social and transportation problems such as death and economic losses. Eradication of accident blackspots is a crucial part of the road safety approach. So, this issue informed the quest to study and identify the accidental black spot in the context of NH 6. The stretch of 35 km on NH 6 near Pune was considered to identify the black spot. Accident blackspot locations were distinguished through the accident severity index (ASI) method by employing two years of accident data. These identified black spots were prioritized based on their final severity index score. The two most vulnerable black spots out of nine were selected for further analysis and countermeasure process. Conclusively, the accident severity-based framework can effectively correlate the nature of the accident with the type of casualty to provide detailed and accurate black spot location. Keywords: Black Spots, Accident Severity Index (ASI), Black Spot Prioritization, Traffic Volume, Highway, Countermeasures.

scholarly journals Road Accidental Analysis and Identify the Black Spot

2020 ◽  
Vol 5 (8) ◽  
pp. 871-876
Author(s):  
Jaffar Hussian Meer ◽  
Sukhdeep Singh ◽  
Komalpreet Singh
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Black Spot ◽  
Motor Vehicles ◽  
Road Accidents ◽  
The Road ◽  
Black Spots ◽  
On The Road ◽  
Adverse Influence ◽  
Capital Development

The increase in motor vehicles accompanied with expansion of roads has brought with it the challenge of addressing the adverse influence of road traffic accidents. Road incidents are a nationwide cataclysm with ever increasing trend which incurs a human health and development challenge and highly affect the human capital development of every nation. A mortality rate database (WHO, 2002) assures that India has highest number of accidents. Accident Black Spots are those locations on the road which have higher severity of accident either in terms of numbers or in terms of injuries. In this paper, efforts have been made to identify the location of accident black spots on national highway from singhpora pattan to panthachowk srinagar.The present era accidents are contributing major deaths worldwide due to increase in vehicular traffic.It has been estimated that every year 1.38 lakh lose their limbs and 6 lakh people get injured in road accidents in india.our country incurs a loss of 58000 crore each year due to road accidents. The most used roads to travel from jalandhar in punjab to uri in kashmir is NH-1A.The old name for NH-44 is NH-1A which was replaced after renumbering of all national highways in year 2010. In this report,the analysis includes study of some major accident spots or busy intersections in the NH-1A in between Pantha chowkh Srinagar to Singhpora Pattan.The study includes visiting sites,collecting required data for analysis and derives the results and remedies from what we had got. This report will be containing the material surveyed,pictures of road at different locations ,road details,figures,material for understanding of the unknown and finally the conclusion

scholarly journals Prioritization of Black Spots in Hilly Road Segment using Road Engineering Data

2020 ◽  
Vol 9 (3) ◽  
pp. 4418-4422
Keyword(s):  
Black Spot ◽  
Road Transport ◽  
Road Accident ◽  
Industrialized Countries ◽  
Road Accidents ◽  
Road Engineering ◽  
The Road ◽  
Black Spots ◽  
Accident Data ◽  
On The Road

Road accidents are one of the causes of disability, injury and death. As per the latest road accident data released by the Ministry of Road Transport & Highways (MoRTH), the total number of accidents increased by 2.5 percent from 4,89,400 in 2014 to 5,01,423 in 2015. The analysis reveals that about 1,374 accidents and 400 deaths take place every day. Every single year, it has been estimated that over three lakh persons die and 10-15 million persons are injured in road accidents throughout the world. According to the analyses, statistics of global accident indicate that in developing countries, the rate of fatality per licensed vehicle is very high as compared to that of industrialized countries. A road stretch of about 500 metres in length in which either ten fatalities or five road accidents (involving grievous injuries/fatalities) took place during last three calendar years, on National Highways is considered as a road accident black spot according to MoRTH, Government of India. In the present study the identified black spots of Haridwar and Dehradun city were included comprising of a total of 81 black spots out of which there were 49 black spots which were identified in Dehradun followed by 32 black spots in Haridwar. The present study was an attempt to carry out the prioritization of these identified blackspots with respect to the factors that were considered to evaluate accident prone locations on the road. The identified black spots were then prioritized using the classification scheme (ranking from low to high).The study reveals that the advantage of using this approach for prioritizing accident black spots on roads is that it requires very less additional data other than the road network maps.

scholarly journals Traffic Accident Data Analysis at Section from Sarai Khawaja to Old Faridabad of New Nh-44 (Old Nh-2) Including Bypass in Harayana Using GIS

2019 ◽  
pp. 87-96
Author(s):  
Sandeep Tewatia
Keyword(s):  
Traffic Accident ◽  
Black Spot ◽  
Severity Index ◽  
Data Bank ◽  
High Rate ◽  
Police Station ◽  
Black Spots ◽  
Accident Data ◽  
Serious Injury ◽  
Gis Software

The main object of this study is to discuss the present state of traffic accident information of study area (Area under Old Faridabad and Sector-31 Faridabad Police station). It shall discuss the Identification of high rate accident locations and safety deficient areas on the highway by analysing accident data bank for the study area extracted from Police FIR records for the year 2015 to 2018 with the help of GIS software. The Severity index of every accident is calculated using proportionate weightage of fatal, serious injury, minor injury and property damage only and Severity Index is used in spatial analysis. Eleven numbers of black spot locations have been identified and ranked on NH-44 section (old NH-2) including bypass in Faridabad, Haryana. Also, various remedial measures to those accidental locations (Black Spots) have been suggested.

scholarly journals Mitigation Of Black-Spot’s on Highways by The Application of Safe System Approach

2021 ◽  
pp. 583-591
Author(s):  
Dinesh K Yadav ◽  
Sujesh D. Ghodmare ◽  
N. Naveen Kumar
Keyword(s):  
Traffic Safety ◽  
Negative Impact ◽  
Black Spot ◽  
Severity Index ◽  
Traffic Volume ◽  
Short Term ◽  
The Road ◽  
Course Of Action ◽  
Accident Data ◽  
Safety Parameters

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 traffic volume 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.

scholarly journals PENINGKATAN KESELAMATAN JALAN PADA BLACK SPOT JALAN PROVINSI DI KABUPATEN SLEMAN

2021 ◽  
Vol 21 (2) ◽  
pp. 109-122
Author(s):  
One Sigit Hermanto ◽  
Agus Taufik Mulyono ◽  
Latif Budi Suparma
Keyword(s):  
Road Safety ◽  
Traffic Management ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Safety Evaluation ◽  
Black Spot ◽  
The Road ◽  
Technical Requirements ◽  
Black Spots ◽  
Rumble Strip

Abstract   The fatality rate of traffic accidents in Sleman Regency is increasing every year. This study aims to identify black spots and set priorities for repairing road infrastructure components needed to improve road safety on 3 provincial roads in Sleman Regency. The black spot is determined using the Accident Equivalence Number Method and the Upper Control Limit. The evaluation carried out resulted in the 3 worst segments on each observed road segment. The results of the road safety evaluation show that the technical implementation of traffic management and engineering, the technical use of road components, and the technicality of road equipment are the 3 technical requirements of the road with the lowest level of application. To improve road safety, this study recommends adding rumble strips, adding signs, relocating roadside hazards, and adding sidewalks and crossing zones.   Keywords: fatality; black spots; traffic accident; road; road safety.     Abstrak   Tingkat fatalitas kecelakaan lalu lintas di Kabupaten Sleman meningkat setiap tahun. Penelitian ini bertujuan untuk mengidentifikasi black spot dan menetapkan prioritas perbaikan komponen infrastruktur jalan yang diperlukan untuk meningkatkan keselamatan jalan di 3 ruas jalan provinsi di Kabupaten Sleman. Black spot ditentukan dengan menggunakan Metode Angka Ekivalensi Kecelakaan dan Batas Kontrol Atas. Evaluasi yang dilakukan menghasilkan 3 segmen terburuk pada setiap ruas jalan yang diamati. Hasil evaluasi keselamatan jalan menunjukkan bahwa teknis penyelenggaraan manajemen dan rekayasa lalu lintas, teknis pemanfaatan bagian-bagian jalan, dan teknis perlengkapan jalan merupakan 3 persyaratan teknis jalan dengan tingkat penerapan terendah. Untuk meningkatkan keselamatan jalan, studi ini merekomendasikan penambahan rumble strip, penambahan rambu, merelokasi hazard yang terdapat di tepi jalan, serta penambahan trotoar dan zona penyeberangan.   Kata-kata kunci: fatalitas; black spot; kecelakaan lalu lintas; jalan; keselamatan jalan.

scholarly journals Identification of Road Accident by using Black Spot Method Between Panthaghati to Dhalli Road

2020 ◽  
Vol 9 (2) ◽  
pp. 723-728
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Black Spot ◽  
Research Paper ◽  
Road Accident ◽  
Road Traffic Accidents ◽  
Road Accidents ◽  
The Road ◽  
Black Spots

In India road accidents are very serious problem because of large population and high traffic density of vehicles. Most of the road accidents occur mainly due to the negligence of driver and poor infrastructure only a few accidents occur due to the technical error of vehicles. The main purpose of this research paper is prevention of road traffic accidents and improvement of road safety in Shimla. Road safety is very important aspect of today’s life, so it is important that everybody should aware about road safety. To do this study a section of 12km length is chosen between Panthaghati to Dhalli in district Shimla on NH 5 where accidents black spots are identified for the section by analyzing secondary data used to prevent road accidents. In this study primary data is used for observing the road conditions and secondary data is used to find accidents black spot. Black Spot is a point or a place on the road where road accident occurs repeatedly one after another which is known as accident black spot. To identify these black spots we use weighted severity index (WSI) method. It is one the most reliable and effective method for determining the most proven accidents black spots. Shimla is a hilly area and it has narrow roads, blind curve and black spots which increase the chances of road traffic accidents. In past recent years road traffic accidents are increasing in Shimla and this study deals with identification of major issues causing road traffic accidents. This research paper helps to improve the road safety in Shimla because in this study the analysis has been done to identify the major problems responsible for gradually increasing road accidents. This research paper is also used in future research paper as reference purpose and it will also provide an overview to other researchers who want do their research on similar kind of topics.

scholarly journals Accident Study and Analysis of Selected Black Spots – A Case Study

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1254
Author(s):  
Sandeep Singh ◽  
. .
Keyword(s):  
Preventive Measures ◽  
Black Spot ◽  
The Road ◽  
Black Spots ◽  
Traffic Speed ◽  
Accident Statistics

In the present study, accident statistics of 2011 to 2014 has resolved Vidya path as a black spot. In addition, attempt has been made to investigate the prevailing conditions of two V3 road stretches i.e. (Stretch – 1: road dividing sec – 14 and 15 and Stretch – 2: road dividing sec – 11 and 12) of Chandigarh for accidental risk. The moral of investigation has cleared that all the prime associated parties i.e. traffic, speed and users/driver are favoring the accidental risk; as during peak hour the road stretches were found short of capacity, speed of vehicles was over the legal speed and the users were ignoring the rules and regulation of driving. Consequently, the injury and life risk for pedestrians and cyclists are at the most. The preventive measures for the same are also incorporated.  

scholarly journals Accident Analysis and Identification of Black Spots on the Motorways in Pakistan - a Reliability Analysis Approach

2021 ◽  
Vol 40 (4) ◽  
pp. 692-702
Author(s):  
Muhammad Hussain ◽  
Jing SHI ◽  
Yousaf Ali
Keyword(s):  
Reliability Analysis ◽  
Black Spot ◽  
Road Accident ◽  
Analysis Approach ◽  
Contributory Factor ◽  
Road Accidents ◽  
Drowsy Driving ◽  
Late Night ◽  
Black Spots ◽  
Accident Data

The objective of this study is to explore the contributory factors responsible for road accidents and identifies the black spots on the three motorways; M1 (Peshawar-Islamabad), M2 (Islamabad-Lahore), and M3 (Pindi BhattianFaisalabad) in Pakistan. Five years’ road accident data was obtained from the National Highways and Motorway Police (NHMP), Pakistan. The database of this study included six hundred road accidents on a total of 574 kilometers long routes of M1, M2 and M3. The reliability analysis approach was used to locate black spot locations on each motorway. For the visualization and mapping of black spots on each motorway, a Geographic Information System (GIS) was used. The results explored that vehicle condition was the significant contributory factor responsible for the maximum number of road accidents on M1 and M3, while for M2, it was drowsy driving. It is also found that a maximum number of road accidents on M2 and M3 occurred in late-night, while for M1, it was day timing. Furthermore, road accidents were relatively higher in May-July and December on M1 and M2, which shows that extreme weather influences the occurrence of road accidents. On the contrary, no substantial variation of road accidents was examined for M3 month-wise. Finally, black spots on each motorway were located and their georeferenced coordinates were presented for future use. As a result, precautionary measures and provisions are suggested for concerned authorities to mitigate road safety problems.

Road Macula Analysis and Evaluation

2011 ◽  
Vol 97-98 ◽  
pp. 360-366
Author(s):  
Jian Cheng Sun ◽  
Lin Song Wang
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Black Spot ◽  
Road Accident ◽  
The Road ◽  
Discriminant Model ◽  
Road Traffic Safety ◽  
Black Spots

The subject Introduced the analysis method of the black-spot, established the black-spot discriminant model, And gave its algorithm. According to the characteristics of China's traffic flow, we develope black-spot database, so that the work of the black-spot identification can be quickly carried out。The Road black-spot traffic accidents describes the road sections which have significantly higher accident rate than the average level . Road black-spots identification, analysis and processing are widely considered to be the most efficient way to prevent traffic accidents. The identification of Road accident black-spots is the concern of road design, road safety review, operation management, and security studies , The research studies of road black-spot identification,and determines risk road sections, so that countermeasures can be put forward, and we can achieve the goals of design improvement, strengthen management, improvement of road safety operation environment, decrease of the number of traffic accidents and improvement of the whole road traffic safety performance.

scholarly journals Integration of Probability and Clustering Based Approaches in the Field of Black Spot Identification

2018 ◽  
Author(s):  
Maen Ghadi ◽  
Árpád Török ◽  
Katalin Tánczos
Keyword(s):  
Empirical Bayes ◽  
Black Spot ◽  
Segment Length ◽  
Bayes Method ◽  
The Road ◽  
Traffic Conditions ◽  
Black Spots ◽  
Empirical Bayes Method ◽  
Infrastructure Network ◽  
Clustering Approach

The objective of the paper is to define a complex methodology to analyze black spot locations of road infrastructure network combining the benefit of both; Empirical Bayes method and K-mean clustering approach. In the first step, K-mean algorithm is used to define homogeneous accident clusters. The homogeneity is described in three terms: traffic conditions, geometric design of the road and accident characteristics. Then, Empirical Bayes method is applied to define black spots based on the determined clusters. Due to the combination of the introduced methods, a powerful technique is provided that is able to identify high-risk locations and cluster dependent segment length as the output of the model.

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