Improving Road Safety in India Using Data Mining Techniques

  • GauravEmail author
  • Zunaid AlamEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 799)


Road accidents are very common in India. World Health Organization (WHO) has revealed that India the worst road traffic accident rate worldwide. According to the report, poor driving pattern, drunk driving, badly maintained roads and vehicles are the main triggering factors to road casualties. Statistics shows that one serious road accident in the country occurs every minute. The national capital, Delhi is among the deadliest. To achieve aim of reducing road accidents, novel and robust prevention strategies for improved road severity have to be developed. In this work, we propose use of data mining frame work to analyze traffic on National Highways of India. Using real data set of National Highway of India, we will mine important patterns for accidental data on National Highways of India and, identify key causes to road casualties. The discovered knowledge can be used by Ministry of road transport & highways of India to take effective decisions to reduce road severity.


Data mining Association rules Road safety 


  1. 1.
    Zhong, R., Wang, H.: Research of commonly used association rules mining algorithm in data mining. In: IEEE International Conference on Internet Computing and Information Services (2011). ISBN 978-0-7695-4539-4/11Google Scholar
  2. 2.
    Kumar, S., Toshniwal, D.: Analysing road accident data using association rule mining. In: IEEE International Conference on Computing, Communication and Security, December 2015. ISBN 978-1-4673-9354-6/15Google Scholar
  3. 3.
    Shruthi, P., Vanketesh, V.T., Viswakanth, B., Ramesh, C., Sujatha, P.L., Dominic, I.R.: Analysis of fatal road traffic accidents in a metropolitan city of South India. J. Indian Acad. Forensic Med. 35(4) 2013Google Scholar
  4. 4.
    Raut, U.M., Nalawade, D.B., Kale, K.V.: Mapping and analysis of accident black spot in Aurangabad city using geographic information system. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 6(1) (2016)Google Scholar
  5. 5.
    Shah, K.D., Sachdeva, S.N.: A comparative study of accident safety on Haryana road. IOSR J. Mech. Civil Eng., 13–16. e-ISSN 2278-1684, p-ISSN 2320-334XGoogle Scholar
  6. 6.
    Prince Mary, S., Baburaj, E.: An efficient approach to perform pre-processing. Indian J. Comput. Sci. Eng. 4(5) (2013). ISSN 0976-5166Google Scholar
  7. 7.
    Aubrecht, P., Koub, Z.: A universal data preprocessing system. In: Popelínský, L. (ed.) DATAKON 2003, Brno, pp. 1–3, 18–21 October 2003Google Scholar
  8. 8.
    Pandey, K.K., Pradhan, N.: An analytical and comparative study of various data preprocessing method in data mining. Int. J. Emerg. Technol. Adv. Eng. 4(10) (2014). ISSN 2250-2459Google Scholar
  9. 9.
    Aleem, A.S., Asif, K.H., Ali, A., Awan, S.M.: Pre processing methods of data mining. In: IEEE/ACM 7th International Conference on Utility and Cloud Computing (2014). ISBN 978-1-4799-7881-6/14Google Scholar
  10. 10.
    Somkunwar, R.: A study on various data mining approaches of association rules. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2(9) (2012)Google Scholar
  11. 11.
    Beshah, T., Ejigu, D., Abraham, A., Snasel, V., kromer, P.: Mining pattern from road accident data: role of road user’s behavior and implications for improving road safety. Int. J. Tomography Simul. 22(1) (2013). ISSN 2319-3336Google Scholar
  12. 12.
    Liang, G.J.: Automatic traffic accident detection based on Internet of things and Support vector machine. Int. J. Smart Home 9(4), 97–106 (2015)Google Scholar

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.SGT UniversityGurugramIndia

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