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 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 Accident Hotspot Identification on the Midnapore Kharagpur Development Authority Planning Area.

2020 ◽  
Vol 9 (2) ◽  
pp. 169-174 ◽  
Keyword(s):  
Geographical Information Systems ◽  
Black Spot ◽  
Kernel Density ◽  
Road Accident ◽  
Geographical Information ◽  
Road Accidents ◽  
Police Station ◽  
Black Spots ◽  
The World ◽  
Accident Data

Road accidents are a vital problem in our country for various reasons. According to WHO reports, approximately 1.25 million people died each year, and more than 50 million people injured in road accidents all over the world. Road accident is mostly human-made, and it's affecting your life negatively. Regarding, many studies or research has been performed to reduce road accident and identify the accident blackspot. This paper represents a methodology to find out the accident-prone zone, estimation of Kernel Density and black Site & black Spot identification of major roads Medinipur and Kharagpur development Authority (MKDA) planning area using of Geographical Information Systems (GIS). For this study, road accident data collected from Paschim Medinipur Kotwali Police station from 2016 to 2019. A kernel density estimation was created to identify black spots & black sites of the study area. Based on the result, suggestions are provided to improve the situation in the future.

scholarly journals Road Traffic Accident Analysis and Identification of Black Spot Locations on Highway

2020 ◽  
Vol 6 (12) ◽  
pp. 2448-2456
Author(s):  
Asad Iqbal ◽  
Zia Ur Rehman ◽  
Shahid Ali ◽  
Kaleem Ullah ◽  
Usman Ghani
Keyword(s):  
Road Safety ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Black Spot ◽  
Accident Analysis ◽  
Road Traffic Accidents ◽  
Contributing Factors ◽  
Black Spots

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

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 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.

A Traffic Accident Predictive Model Based on Neural Networks Algorithm and Rough Set Theory

2011 ◽  
Vol 97-98 ◽  
pp. 947-951 ◽  
Author(s):  
Qiao Ru Li ◽  
Liang Chen ◽  
Chang Guang Cheng ◽  
Yue Xiang Pan
Keyword(s):  
Neural Network ◽  
Set Theory ◽  
Rough Set ◽  
Bp Neural Network ◽  
Traffic Accident ◽  
Rough Set Theory ◽  
Road Traffic ◽  
Black Spot ◽  
Black Spots ◽  
Neural Network Algorithm

The most important and critical step to improve road traffic safety is prediction and identification of traffic accident black spot. A new prediction model of traffic accident black spots is proposed based on GA-BP neural network algorithm and rough set theory. First of all, the traffic accident statistics of Jinwei Road in Tianjin are analyzed. With consideration of static road conditions, the samples of road accident black spots are obtained by the GA-BP neural network algorithm. Furthermore, an effective road traffic accident black spot prediction model is established by utilizing rough set theory with consideration of the impact of real time dynamic conditions. Finally, a numerical example is illustrated. Experimental results show that the proposed model with the combination of these two theories can reduce the hybrid and burdensome amount of data, lower the false alarm rate and improve the forecasting accuracy of accident black spots.

scholarly journals RANCANG BANGUN APLIKASI PEMETAAN DAERAH RAWAN KECELAKAAN BERBASIS ANDROID

2020 ◽  
Vol 15 (1) ◽  
pp. 26
Author(s):  
Novia Anggraini ◽  
Moh. Anshori Aris Widya ◽  
Siti Sufaidah
Keyword(s):  
Traffic Accident ◽  
Black Spot ◽  
Building Design ◽  
Transportation Safety ◽  
Z Score ◽  
Accident Rate ◽  
Digital Map ◽  
Gis Application ◽  
Accident Data ◽  
Map Service

Kecelakaan lalu lintas merupakan masalah yang membutuhkan penanganan serius mengingat besarnya kerugian yang diakibatkannya. Salah satu upaya untuk meningkatkan keselamatan transportasi yaitu dengan mengetahui titik lokasi rawan kecelakaan. Metode yang digunakan untuk mengidentifikasi lokasi rawan kecelakaan yaitu metode Angka kecelakaan dan frekuensi kecelakaan. Tujuan studi ini untuk mengidentifikasi titik lokasi rawan kecelakaan dengan menggunakan metode Batas Angka Ekivalen kecelakaan dan Z-Score. Data kecelakaan lalu lintas yang dianalisis bersumber dari satlantas Jombang dari tahun 2018 dan data yang bersumber dari media elektronik, variabel dummy dari tahun 2016 - 2019. Aplikasi rancang bangun daerah rawan kecelakaan Berbasis mobile, dibangun dengan framework Codeigniter dan Framework 7, MySql sebagai basis data dan Mapbox Api sebagai layanan peta digital.  Hasil akhir dari penelitian ini adalah terciptanya aplikasi SIG berbasis mobile yang menyajikan informasi titik lokasi rawan kecelakaan dan tingkat kerawanannya serta notifikasi kepada pengguna jika berada di radius titik rawan yang dapat diakses oleh masyarakat. AbstractTraffic accidents are a problem that requires serious treatment considering the amount of loss caused. One effort to improve transportation safety is to know the location of accident-prone locations. The method used to identify accident prone locations is the accident rate and frequency of accident methods. The purpose of the study is to identify accident prone locations by using the Accidental Equivalent Limit Limits and Z-Score methods. Traffic accident data analyzed were sourced from Jombang Satlantas from 2018 and data were sourced from electronic media, dummy variables from 2016 - 2019. Application of building design for accident-prone areas Based on mobile, built with Codeigniter frame and Framework 7, MySql as database and the Fire Mapbox as a digital map service. The final result of this study is the creation of a mobile-based GIS application that presents information on the location of accident-prone locations and their vulnerability levels as well as notifications to users if they are in a vulnerable point radius that can be accessed by the public.Keywords: Equivalent accident number (EEK); Black Spot; Framework7; SIG; Z-Score

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.

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.

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