Study of Road Accident Prediction Model at Accident Blackspot Area: A Case Study at Selangor

Authors(4) :-Haikal Aiman Hartika, Mohd Zakwan Ramli, Muhamad Zaihafiz Zainal Abidin, Mohd Hafiz Zawawi

This study is focusing in the accident prediction model by using Multiple Linear Regression and Artificial Neural Network, as well as investigating the effectiveness of both predictive analyses. To meet these objectives, the historical data of accident was analysed with the on-site data for the purpose of relating them with the accident occurrence. Also, the accident historical data and the on-site data were analysed using two predictive models to predict the number of accident in current year. After the analysis, it is revealed that the outcomes obtained from both models were different with greater predicted value from the regression analysis due to greater errors being produced. Less predicted value, greater correlation and less error have been shown by the Artificial Neural Network analysis, concluding that it is more suitable for accident prediction.

Authors and Affiliations

Haikal Aiman Hartika
Civil Engineering Department, College of Engineering, Universiti Tenaga Nasional, Kajang, Selangor, Malaysia
Mohd Zakwan Ramli
Civil Engineering Department, College of Engineering, Universiti Tenaga Nasional, Kajang, Selangor, Malaysia
Muhamad Zaihafiz Zainal Abidin
Faculty of Architecture and Built Environment, Infrastructure University Of Kuala Lumpur, Kajang, Selangor, Malaysia
Mohd Hafiz Zawawi
Civil Engineering Department, College of Engineering, Universiti Tenaga Nasional, Kajang, Selangor, Malaysia

ANN, MLR, prediction model, and road accident.

  1. Road Transport Department Malaysia. Retrieved Mac 5, 2016, from http://www.jpj.gov.my/web/guest/pendaftaran-kenderaan-perdagangan.
  2. Mustakim, F., Aziz, A., and Samad, A. (2008). Blackspot Study and Accident Prediction Model Using Multiple Liner Regression. Transportation, 121-136. Retrieved from http://civil.neduet.edu.pk/ICCIDC-I/Conference Proceedings/Papers/013.pdf
  3. Oyedepo, O., and Makinde, O. (2010). Accident Prediction Models for Akure-Ondo Carriageway, Ondo State Southwest Nigeria; Using Multiple Linear Regressions.
    African Research Review, 4(2), 30-49. Retrieved from http://www.ajol.info/index.php/afrrev/article/view/58286
  4. Ramli, M. Z.,. (2011). Development of accident prediction model by using artificial neural network, Master thesis. Universiti Tun Hussein Onn Malaysia.
  5. Kamba, A. N., Rahmat, R. A. O. K., & Ismail, A. (2007). Why Do People Use Their Cars: A Case Study In Malaysia. Journal of Social Sciences, 3(3), 117-122. http://doi.org/10.3844/jssp.2007.117.122
  6. Mustakim, F. (2006). Treating Hazardous Location at Federal Route 50. Master of Science (Construction Management) Thesis. Universiti Teknologi Malaysia.
  7. Tian, R., Xiang, Q., & Hu, S. (2013). Research on Traffic Safety of Freeway Upgrade Section. Procedia - Social and Behavioral Sciences, 96(Cictp), 548-556. http://doi.org/10.1 016/j.sbspro.2013.08.063
  8. Odumosu, A. O., (2005) Demeanour Transposition as Strategy for Traffic Accident Reduction in Nigeria: Case Study of Niger State, Nigeria, Proc. 13 th International Conference on Road Safety on Four Continents, Warsaw, Poland, p. 18
  9. Ogwueleka, F. N., Misra, S., & Ogwueleka, T. C. (2014). An Artificial Neural Network Model for Road Accident Prediction?: A Case Study of a Developing Country. Acta Polytechnica Hungarica, 11(5), 177-197.
  10. Ali, G. A., & Tayfour, A. (2012). Characteristics and Prediction of Traffic Accident Casualties In Sudan Using Statistical Modeling and Artificial Neural Networks,
    1(4), 305-317.
  11. Bastos, Y. G. L., de Andrade, S. M., Soares, D. A., & Matsuo, T. (2005). Seat belt and helmet use among victims of traffic accidents in a city of Southern Brazil, 1997- 2000. Public Health, 119(10), 930-932. http://doi.org/10.1016/j.puhe.2005.01.008
  12. Oyedepo, O., & Makinde, O. (2010). Accident Prediction Models for Akure-Ondo Carriageway, Ondo State Southwest Nigeria; Using Multiple Linear Regressions.
    African Research Review, 4(2), 30-49. Retrieved from http://www.ajol.info/index.php/afrrev/article/view/58286
  13. Abdelwahab, Hassan T., and Mohamed A. Abdel-Aty. "Development of artificial neural network models to predict driver injury severity in traffic accidents at signalized intersections." Transportation Research Record: Journal of the Transportation Research Board 1746, no. 1 (2001): 6-13.
  14. Akgüngör, A., & Do?an, E. (2009). An application of modified Smeed, adapted Andreassen and artificial neural network accident models to three metropolitan cities of Turkey. Scientific Research and Essay, 4(9), 906-913. Retrieved from http://www.researchgate.net/publication/228512198_An_application_of_modifie d_Smeed_adapted_Andreassen_and_artificial_neural_network_accident_models _to_three_metropolitan_cities_of_Turkey/file/3deec52b9692eb6454.pdf
  15. Hejmanowski, R., & Witkowski, W. T. (2015). Suitability assessment of artificial neural network to approximate surface subsidence due to rock mass drainage.
    Journal of Sustainable Mining, 14(2), 101 -107. http://doi.org/10.1016/j.jsm.2015.08.014

Publication Details

Published in : Volume 3 | Issue 5 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 466-470
Manuscript Number : IJSRSET1734115
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Haikal Aiman Hartika, Mohd Zakwan Ramli, Muhamad Zaihafiz Zainal Abidin, Mohd Hafiz Zawawi, " Study of Road Accident Prediction Model at Accident Blackspot Area: A Case Study at Selangor, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 5, pp.466-470, July-August-2017.
Journal URL : http://ijsrset.com/IJSRSET1734115

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