Abstract
Objective: Analyze the road crashes in Cartagena (Colombia) and the factors associated with the collision and severity. The aim is to establish a set of rules for defining countermeasures to improve road safety. Methods: Data mining and machine learning techniques were used in 7894 traffic accidents from 2016 to 2017. The severity was determined between low (84%) and high (16%). Five classification algorithms to predict the accident severity were applied with WEKA Software (Waikato Environment for Knowledge Analysis). Including Decision Tree (DT-J48), Rule Induction (PART), Support Vector Machines (SVMs), Naïve Bayes (NB), and Multilayer Perceptron (MLP). The effectiveness of each algorithm was implemented using cross-validation with 10-fold. Decision rules were defined from the results of the different methods. Results: The methods applied are consistent and similar in the overall results of precision, accuracy, recall, and area under the ROC curve. Conclusions: 12 decision rules were defined based on the methods applied. The rules defined show motorcyclists, cyclists, including pedestrians, as the most vulnerable road users. Men and women motorcyclists between 20–39 years are prone in accidents with high severity. When a motorcycle or cyclist is not involved in the accident, the probable severity is low.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
World Health Organization (WHO): Global status report on road safety 2018 (2018). https://apps.who.int/iris/bitstream/handle/10665/276462/9789241565684-eng.pdf?ua=1
Savolainen, P., Mannering, F.: Probabilistic models of motorcyclists’ injury severities in single- and multi-vehicle crashes (in English). Accid. Anal. Prev. 39(5), 955–963 (2007)
Abdelwahab, H., Abdel-Aty, M.: Development of artificial neural network models to predict driver injury severity in traffic accidents at signalized intersections. Transp. Res. Rec.: J. Transp. Res. Board 1746, 6–13 (2001)
Hashmienejad, S.H.-A., Hasheminejad, S.M.H.: Traffic accident severity prediction using a novel multi-objective genetic algorithm. Int. J. Crashworthiness 22(4), 425–440 (2017)
Sohn, S., Shin, H.: Data mining for road traffic accident type classification. Ergonomics 44, 107–117 (2001)
Huang, H., Abdel-Aty, M.: Multilevel data and Bayesian analysis in traffic safety. Accid. Anal. Prev. 42(6), 1556–1565 (2010)
Li, Z., Liu, P., Wang, W., Xu, C.: Using support vector machine models for crash injury severity analysis. Accid. Anal. Prev. 45, 478–486 (2012)
Delen, D., Tomak, L., Topuz, K., Eryarsoy, E.: Investigating injury severity risk factors in automobile crashes with predictive analytics and sensitivity analysis methods. J. Transp. Health 4, 118–131 (2017)
Balasubramanian, V., Jagannath, M.: Detecting motorcycle rider local physical fatigue and discomfort using surface electromyography and seat interface pressure. Transp. Res. Part F 22, 150–158 (2014)
Shafiei, U.K.M., Karuppiah, K., Tmrin, S.B.M., Meng, G.Y., Rasdi, I., Alias, A.N.: The effectiveness of new model of motorcycle seat with built-in lumbar support (in English). Jurnal Teknologi 77(27), 97–103 (2015)
Ospina-Mateus, H., Jiménez, L.A.Q.: Understanding the impact of physical fatigue and postural comfort experienced during motorcycling: a systematic review. J. Transp. Health 12, 290–318 (2019)
World Health Organization (WHO): Seguridad de los vehículos de motor de dos y tres ruedas: manual de seguridad vial para decisores y profesionales (2017). https://apps.who.int/iris/bitstream/handle/10665/272757/9789243511924-spa.pdf?sequence=1&isAllowed=y
Segui-Gomez, M., Lopez-Valdes, F.J.: Recognizing the importance of injury in other policy forums: the case of motorcycle licensing policy in Spain (in English). Inj. Prev. Short Surv. 13(6), 429–430 (2007)
Schneider Iv, W.H., Savolainen, P.T., Van Boxel, D., Beverley, R.: Examination of factors determining fault in two-vehicle motorcycle crashes (in English). Accid. Anal. Prev. 45, 669–676 (2012)
Ivers, R.Q., et al.: Does an on-road motorcycle coaching program reduce crashes in novice riders? A randomised control trial (in English). Accid. Anal. Prev. 86, 40–46 (2016)
Donate-López, C., Espigares-Rodríguez, E., Jiménez-Moleón, J.J., de Dios Luna-del-Castillo, J., Bueno-Cavanillas, A., Lardelli-Claret, P.: The association of age, sex and helmet use with the risk of death for occupants of two-wheeled motor vehicles involved in traffic crashes in Spain. Accid. Anal. Prev. 42(1), 297–306 (2010)
Albalate, D., Fernández-Villadangos, L.: Motorcycle injury severity in Barcelona: the role of vehicle type and congestion (in English). Traffic Inj. Prev. 11(6), 623–631 (2010)
Clabaux, N., Brenac, T., Perrin, C., Magnin, J., Canu, B., Van Elslande, P.: Motorcyclists’ speed and “looked-but-failed-to-see” accidents (in English). Accid. Anal. Prev. 49, 73–77 (2012)
Sager, B., Yanko, M.R., Spalek, T.M., Froc, D.J., Bernstein, D.M., Dastur, F.N.: Motorcyclist’s lane position as a factor in right-of-way violation collisions: a driving simulator study (in English). Accid. Anal. Prev. 72, 325–329 (2014)
Rizzi, M., Strandroth, J., Holst, J., Tingvall, C.: Does the improved stability offered by motorcycle antilock brakes (ABS) make sliding crashes less common? In-depth analysis of fatal crashes involving motorcycles fitted with ABS (in English). Traffic Inj. Prev. 17(6), 625–632 (2016)
Clarke, D.D., Ward, P., Bartle, C., Truman, W.: The role of motorcyclist and other driver behaviour in two types of serious accident in the UK (in English). Accid. Anal. Prev. 39(5), 974–981 (2007)
López-Valdés, F.J., García, D., Pedrero, D., Moreno, J.L.: Accidents of motorcyclists against roadside infrastructure. In: IUTAM Symposium on Impact Biomechanics: From Fundamental Insights to Applications, vol. 124, pp. 163–170, Dublin (2005)
Brown, J., Schonstein, L., Ivers, R., Keay, L.: Children and motorcycles: a systematic review of risk factors and interventions. Inj. Prev. 24(2), 166–175 (2018)
Elliott, M.A., Baughan, C.J., Sexton, B.F.: Errors and violations in relation to motorcyclists’ crash risk (in English). Accid. Anal. Prev. 39(3), 491–499 (2007)
Truong, L.T., Nguyen, H.T., De Gruyter, C.: Mobile phone use while riding a motorcycle and crashes among university students. Traffic Inj. Prev. 20, 1–7 (2019)
Acknowledgements
Funding for first author was covered by (CEIBA)—Gobernación de Bolívar (Colombia). We thank the Administrative Department of Traffic and Transportation (DATT) in the accompaniment and support of the information required for this investigation.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Ospina-Mateus, H., Quintana Jiménez, L.A., López-Valdés, F.J., Morales-Londoño, N., Salas-Navarro, K. (2019). Using Data-Mining Techniques for the Prediction of the Severity of Road Crashes in Cartagena, Colombia. In: Figueroa-García, J., Duarte-González, M., Jaramillo-Isaza, S., Orjuela-Cañon, A., Díaz-Gutierrez, Y. (eds) Applied Computer Sciences in Engineering. WEA 2019. Communications in Computer and Information Science, vol 1052. Springer, Cham. https://doi.org/10.1007/978-3-030-31019-6_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-31019-6_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31018-9
Online ISBN: 978-3-030-31019-6
eBook Packages: Computer ScienceComputer Science (R0)