Prediction of the cause of accident and accident prone location on roads using data mining techniques

Kaur, Gagandeep; Kaur, Er. Harpreet

doi:10.1109/icccnt.2017.8204001

Cited by 26 publications

(5 citation statements)

References 4 publications

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“…Treatment plans. Based on the table above, it can be seen that the cause of accidents is dominated by the human factor, namely the vehicle users themselves; this is in line with previous research that human negligence is the main factor causing accidents to occur on the highway (Ichbal Maulana, 2023); (Kaur & Kaur, 2017); (Mohan & Landge, 2017). These results prove that the analysis of the causes of accidents occurs not only due to environmental factors or road conditions.…”

Section: Results and Discussion Identification Of Accident Prone Loca...supporting

confidence: 83%

Accident-Prone Locations on National Roads in Kupang Regency, East Nusa Tenggara Province

Widjajanti

2023

JWS

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This study aimed to identify and formulate recommendations for improvements to Accident-Prone Locations (LRK) in Kupang Regency, East Nusa Tenggara Province. The approach methodology used includes collecting secondary data on accidents from the police and primary data through field surveys to analyze and rank the severity of accidents. The ranking is done through the value of the Equivalent Accident Number (EAN) and Upper Limit Control (UCL). The analysis results show that there are 18 points of Accident Prone Locations on the national road in Kupang Regency. These namely locations have an EAN value above the BKA and UCL values. A motorcycle is the dominant type of vehicle involved in an accident, and the dominant cause of accidents is the driving factor. The formulation of recommendations for improvement was carried out for 3 locations with the highest EAN values, namely Jl. Oesapa-Oesao Km 5, Km 1 and Km 4. For these three locations, the necessary treatment recommendations were formulated. This research has implications in helping identify and prioritize the most accident-prone locations. The study can also encourage the development or improvement of roads, sidewalks, street lighting, traffic signs, or other necessary infrastructure elements to enhance traffic safety in LRK.

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Section: Results and Discussion Identification Of Accident Prone Loca...supporting

confidence: 83%

Accident-Prone Locations on National Roads in Kupang Regency, East Nusa Tenggara Province

Widjajanti

2023

JWS

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“…Geospatial data was used to identify crash locations, as well as to examine the pattern of traffic crashes in Jalgaon [9]. Kaur et al (2017) estimated the severity of accidents on State highways and other district roads. By evaluating the accident severity based on the kind of accident and location of accident using the R tool, this study focused on forecasting the occurrence of accidents on roads.…”

Section: Month-wise Distribution Of Accidentsmentioning

confidence: 99%

“…Improvement in the level and scope of the road traffic safety management can be effectively implemented using this methodology. The current study modeled accident and incident data acquired from traffic data and data pertaining to the construction industry [10]. Singh et al (2016) predicted the accidents using the M5 tree model and binomial regression model on rural road sections of Haryana state.…”

Section: Month-wise Distribution Of Accidentsmentioning

confidence: 99%

Road Accident Analysis and Safety Audit: A Case Study of MDR 132

Khan¹,

Sabir²,

Dass³

et al. 2023

Komunikácie

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Road accident and road safety are the key global concerns and problem for emerging nations like India. It has been attempted to examine the accidents that happened on Major District Road (MDR) 132 (Nuh to Hodal), India in the last five years. The primary objective of this study was to perform the Road Safety Audit for identification of accident-prone areas based on Accident Severity Index (ASI) and provide some improvement measures in order to lower the frequency and severity of accidents. Identified accident prone locations (blackspots) were ranked according to the ASI index. The distribution of accidents based on various parameters were also discussed. Site visit of critical sections of the road to observe road deficiencies were made and safety recommendations, along with the risk associated with them and priority as per IRC: SP: 88-2019, were suggested.

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“…The base map instance is often accustomed calculate positions on the map and also the inverse operation, changing positions on the map to geographical coordinates [11]. For the google map visualization of accident-prone area [12] in UK, Geojson is used. For that, a csv file is to be created from the observations acquired.…”

Section: Proposed Systemmentioning

confidence: 99%

Road Traffic Accident Analysis and Visualization of Accident Prone Areas

Sreedhar¹

2021

IJRASET

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Road accident has a huge impact on society where there is a great cost for fatalities and injuries. Analysing the road accidents and thereby finding a solution is an emerging research area. The project mainly deals with the analysis of road accidents that happened in UK. Initially, the attributes such as sex, age, weather conditions, light conditions etc. were analysed and its effect over the road accident was analysed and found out their relationship according to certain conditions. This can be implemented using heatmap, boxplot, histogram etc. At the second level, a logistic regression model was used to explain the effect of weather and road surface condition towards the accident severity, through variables retrieved from the database. Also, the major accident-prone areas can be identified and plot it using Base map. Apart from this, we extend the functionality of existing services of the Google maps using Geojson to visualize accident prone areas.

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Prediction of the cause of accident and accident prone location on roads using data mining techniques

Cited by 26 publications

References 4 publications

Accident-Prone Locations on National Roads in Kupang Regency, East Nusa Tenggara Province

Accident-Prone Locations on National Roads in Kupang Regency, East Nusa Tenggara Province

Road Accident Analysis and Safety Audit: A Case Study of MDR 132

Road Traffic Accident Analysis and Visualization of Accident Prone Areas

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