Abstract
The high impact of traffic accidents makes it imperative to formulate public policies to reduce their occurrence. In this task, knowing the cause of accidents is of paramount importance. The use of data mining and big data adapts to the complexity of the phenomenon under study. In order to classify some possible causes of traffic accidents, we built a data model to describe the behavior and dynamic of the participant agents in the traffic accident event in Colombia. This paper presents the application of MLP and Naïve Bayes algorithms to identify the possible immediate cause and the rules decision algorithm PART for the root cause of traffic accidents. Models have been tested aiming to obtain the goodness of fit by increasing metrics like Recall, Precision, ROC and Kappa index, and minimize the RMSE.
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References
Janani, G., Ramya Devi, N.: Road traffic accident analysis using data mining techniques. J. Inf. Technol. Appl., 84–91 (2017)
Mark, H., Eibe, F.: Practical Data Mining. University of Waikato (2011)
Xi, J., Gao, Z., Niu, S., Ding, T., Ning, G.: A hybrid algorithm of traffic accident data mining on cause analysis. Math. Problems Eng. Procedia Soc. Behav. Sci. 160, 607–614 (2012)
Luis, M., Leticia, B., Laura, B., Griselda, L.: Using data mining techniques to road safety improvement in spanish roads (2014)
Olutayo, V.A., Eleudire, A.A.: Traffic accident analysis using decision trees and neural networks. Inf. Technol. Comput. Sci. 02, 22–28 (2014)
Shetty, P., Sachin, P.C., Kashyap, S.V., Madi, V.: Analysis of road accidents using data mining techniques, vol. 4, theme 4 (2017)
Bigham, B.S.: Road accident data analysis: a data mining approach. Indian J. Sci. Res. (2014)
Wallen Waner, H.: Dream 3.0 (Driving reliability and error analysis method) (2008)
Alvaro, C.: Methodological guide to obtain occupational accident patterns using data mining. Universidad de Piura, Master thesis (2013)
Mulay, P., Mulat, S.: What you eat matters road safety: a data mining approach. Indian J. Sci. Technol. 9(15) (2016)
Mohamed, E.A.: Predicting causes of traffic road accidents using multi-class support vector machines. In: Proceeding of the 10th International Conference on Data Mining, 21–24 July 2014, pp. 37-42 (2014)
GOV.CO homepage. https://www.datos.gov.co/browse?tags=accidentalidad
Tuba, K., Ozcan, A.: SHARE technique: a novel approach to root cause analysis of ship accidents. Saf. Sci., 1–21 (2017)
WHO homepage. https://www.who.int/violence_injury_prevention/road_traffic/es/
Agencia Nacional de Seguridad Vial homepage. https://ansv.gov.co/observatorio/index.html
Bibing us homepage. http://bibing.us.es/proyectos/abreproy/12166/fichero/Volumen+1+-+Memoria+descriptiva+del+proyecto%252F3+-+Perceptron+multicapa.pdf
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Vélez Sánchez, H., Saavedra Angulo, H. (2021). Use of Data Mining for Root Cause Analysis of Traffic Accidents in Colombia. In: Auer, M., May, D. (eds) Cross Reality and Data Science in Engineering. REV 2020. Advances in Intelligent Systems and Computing, vol 1231. Springer, Cham. https://doi.org/10.1007/978-3-030-52575-0_56
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DOI: https://doi.org/10.1007/978-3-030-52575-0_56
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