Vehicle Safety Device (Airbag) Specific Classification of Road Traffic Accident Patterns through Data Mining Techniques

Shanthi, S.; Ramani, R.

doi:10.1007/978-3-642-31552-7_45

Cited by 27 publications

(28 citation statements)

References 8 publications

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“…Tibebe et al [6] employed classification adaptive regression trees (CART) and random forest approaches which are identified relevant patterns and illustrated the performance of the techniques for the road safety domain where road accident data collected from Addis Ababa traffic office. S Shanthi and R Geetha Ramani are worked on feature relevance analysis and classification of road traffic accident using different data mining techniques [7]. They are implemented in different clustering and association analysis algorithms on the traffic accident records.…”

Section: Related Workmentioning

confidence: 99%

Predicting Accidental Locations of Dhaka-Aricha Highway in Bangladesh using Different Data Mining Techniques

Satu¹,

Akter²,

Arifen³

et al. 2017

IJCA

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Road traffic accident is one of the most leading issues which is concerned in many other countries like Bangladesh. Data mining is considered as a reliable technique to analyze traffic accident record and identify factors that provide severity of an accident. The goal of this research to analyze and build classification model that predict an accidental location in the Dhaka-Aricha highway. So, road accidental data is collected from different highway police stations which keep traffic accident record of every road traffic accident on this road. Then, raw dataset is preprocessed and build a classification model with five data mining classification algorithms named Rotation Forest, NBTree, JRip, Naive Bayes and Ridor that analyze traffic accident records to predict risky accidental locations. After classifying this dataset, accuracies of classifiers are compared and the best outcome is showed among them. This results can be used to prevent road accidents in the areas and overcome the number of accidents on the Dhaka-Aricha highway.

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Section: Related Workmentioning

confidence: 99%

Predicting Accidental Locations of Dhaka-Aricha Highway in Bangladesh using Different Data Mining Techniques

Satu¹,

Akter²,

Arifen³

et al. 2017

IJCA

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“…The data preparation steps gave a clear vision of how the real data can be analyzed. The research work in [6] emphasizes the significance of Data Mining classification algorithms in predicting the factors which influence the road traffic accidents specific to injury severity. Further they applied feature selection methods to select the relevant road accident related factors and Meta classifier Arc-X4 to improve the accuracy of the classifier.…”

Section: Literature Surveymentioning

confidence: 99%

A Survey on Extracting Hidden Patterns within Road Accident Data using Machine Learning Techniques

Vasavi¹

2016

CAE

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Road Accidents may not be stopped altogether, but can be reduced. Driver emotions such as sad, happy, anger etc can be one reason for accidents. At the same time environment conditions such as weather, traffic on the road, load in the vehicle, type of road, health condition of driver, speed etc can also be the reasons for accidents. Hidden patterns in accidents can be extracted so as to find the common features between accidents. This paper presents the literature survey and the results of the framework from the research study on road accident data of major national highways that pass through Krishna district (18 stations) for the year 2013 by applying machine learning techniques into analysis. Results showed that the selected machine learning techniques are able to extract hidden patterns from the data. Density histograms are used for accident data visualization.

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“…The author in [13] used various data mining techniques and tells the random forest outperforms than other classification algorithms. In paper [14], author talks about the significance of data mining classification algorithm in predicting the factor which influences road traffic accident. The author in [15] used to explore the possible application of data mining technology for developing a classification model and the result shows that developed model could classify accidents within a reasonable accuracy.…”

Section: Literature Surveymentioning

confidence: 99%

A Review on Road Accident in Traffic System using Data Mining Techniques

2016

IJSR

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Road traffic accidents are a major public health concern, resulting in an estimated 1.2 million deaths and 50 million injuries worldwide each year. In the developing world, road traffic accidents are among the leading cause of death and injury. The objective of this study is to evaluate a set of variable that contribute to the degree of accident severity in traffic crashes. The issue of traffic safety has raised great concerns across the sustainable development of modern traffic and transportation. The study on road traffic accident cause can identify the key factors rapidly, efficiently and provide instructional methods to the traffic accident prevention and road traffic accident reduction, which could greatly reduce personal casualty by road traffic accidents. Using the methods of traffic data analysis, can improve the road traffic safety management level effectively.

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Vehicle Safety Device (Airbag) Specific Classification of Road Traffic Accident Patterns through Data Mining Techniques

Cited by 27 publications

References 8 publications

Predicting Accidental Locations of Dhaka-Aricha Highway in Bangladesh using Different Data Mining Techniques

Predicting Accidental Locations of Dhaka-Aricha Highway in Bangladesh using Different Data Mining Techniques

A Survey on Extracting Hidden Patterns within Road Accident Data using Machine Learning Techniques

A Review on Road Accident in Traffic System using Data Mining Techniques

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