Black Spot and Accidental Attributes Identification on State Highways and Ordinary District Roads Using Data Mining Techniques

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Gagandeep Kaur
Harpreet Kaur

Abstract

Road traffic accident is a causative aspect and a particular instance of traumatic event that constitute major harm to life and property. Therefore vaticinating the cause of occurrence of accident related information on roads is necessary. Statistical and empirical analysis on State Highways (SH’s) and Ordinary District Roads (ODR’s) accidental datasets has been performed. The need of the study is to scrutinize the traffic related dataset through Exploratory Visualization Techniques, K-means and KNN Algorithms using RStudio. This paper presents results by comparing the above said three mining techniques and predicts the cause of accident, accident prone location, analyze the time of accident, examine the reason of accident and anatomize the accused vehicle.

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References

Somayya Ebrahimkhani, Bahram Sadeghi Begham Farzaneh Moradkhani, "Road Accident Data Analysis: A Data Mining Approach," Indian Journal of Scientific Research, May 2014.

R.P. Kulkarni, S.U. Bobade, M.S. Patil, A.M. Talathi, I.Y. Sayyad, S.V.Apte R.R.Sorate, "Identification of Accident Black Spots on National Highway 4 (New Katraj Tunnel to Chandani Chowk)," vol. 12, no. 3, pp. 61-67, May. - Jun. 2015.

Monika Sharma Jyoti Yadav, "A Review of K-mean Algorithm," International Journal of Engineering Trends and Technology (IJETT), vol. 4, no. 7, pp. 2972-2976, July 2013.

Nathan S. Netanyahu,Angela Y. Wu Tapas Kanungo, "An Efficient k-Means Clustering Algorithm: Analysis and Implementation ," IEEE Transactions on pattern analysis and machine intelligence, vol. 24, July 2002.

Yanwei Yu, Lihong Wang,and Jinglei Liu Jianpeng Qi, "K*-Means: An Effective and Efficient K-means Clustering Algorithm," in International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking, 2016, pp. 242-249.

Marian Cristian Mih˘aescu,Mihai Mocanu Cosmin Marian Poteras, "An Optimized Version of the K-Means Clustering," in Federated Conference on Computer Science and Information Systems, 2014, pp. 695–699.

Mohammad Bolandraftar Sadegh Bafandeh Imandoust, "Application of K-Nearest Neighbor (KNN) Approach for Predicting Economic Events: Theoretical Background," Int. Journal of Engineering Research and Applications, vol. 3, pp. 605-610, Sep-Oct 2013.

Latifur Khan, Bhavani Thuraisingham Lei Wang, "An Effective Evidence Theory based K-nearest Neighbor (KNN) classification," in International Conference on Web Intelligence and Intelligent Agent Technology, 2008, pp. 797-801.

R. Srinivasa Rao Dr. NSSR Murthy, "Development of model for road accidents based on intersection parameters using regression models," International Journal of Scientific and Research Publications, vol. 5, no. 1, pp. 1-8, January 2015.

Sarbajit Bhattacharyya , Mrinal Roy , Pinak Paul Rupanjan Chakraborty, "Accident Analysis and the Suggestion of an Accident Prediction Model for Guwahati city," International Journal of Innovative Research in Science, vol. 4, no. 11, pp. 10774-10782, November 2015.

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