Analysis of Roadway Traffic using Data Mining Techniques : A Review

Authors

  • Nisha A. Solanke  Computer Science & Engineering, Bapurao Deshmukh College of Engineering, Sevagram, Maharashtra, India
  • Prof A. D. Gotmare  Computer Science & Engineering, Bapurao Deshmukh College of Engineering, Sevagram, Maharashtra, India

Keywords:

Data Mining, Association Rule, Classification Rule, Apriori Algorithm, Naïve Bayes Algorithm

Abstract

Roadway traffic safety is a major concern for transportation governing agencies as well as ordinary citizens. Data Mining is taking out of hidden patterns from huge database. It is commonly used in a marketing, surveillance, fraud detection and scientific discovery. In data mining, machine learning is mainly focused as research which is automatically learnt to recognize complex patterns and make intelligent decisions based on data. Globalization has affected many countries. There has been a drastic increase in the economic activities and consumption level, leading to expansion of travel and transportation. The increase in the vehicles, traffic lead to road accidents. Considering the importance of the road safety, government is trying to identify the causes of road accidents to reduce the accidents level. The exponential increase in the accidents data is making it difficult to analyze the constraints causing the road accidents. The paper describes how to mine frequent patterns causing road accidents from collected data set. We find associations among road accidents and predict the type of accidents for existing as well as for new roads. We make use of association and classification rules to discover the patterns between road accidents and as well as predict road accidents for new roads.

References

  1. Zhexue Huang, "Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values", Data Mining and Knowledge Discovery 2, 283–304 (1998).
  2. Sachin Kumar and Durga Toshniwal, "A data mining framework to analyse road accident data", Journal of Big Data (2015) 2:26 DOI 10.1186/s40537-015-0035-y.
  3. S. Krishnaveni ans Dr. M. Hemalatha, "A perspective analysis of Traffic Accident Using Data Mining Techniques", International Journal of Computer Application.
  4. Olutayo V.A and Eludire A.A, "Traffic Accident Analysis Using Decision Trees and Neural Networks", I.J. Information Technology and Computer Science, 2014, 02, 22-28 Published Online January 2014 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijitcs. 2014.02.03.
  5. K. Geetha and C. Vaishnavi, "Analysis on Traffic Accident Injury Level Using Classification", International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 2, February 2015, ISSN: 2277 128X.
  6. Sachin Kumar and Durga Toshniwal, "A data mining approach to characterize road accident locations", J. Mod. Transport. (2016) 24(1):62–72 DOI 10.1007/s40534-016-0095-5.
  7. Tibebe Beshah, Shawndra Hill, "Mining Road Traffic Accident Data to Improve Safety: Role of Road- elated Factors on Accident Severity in Ethiopia"
  8. Quinlan, J. R. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, 1993. [9] K. Jayasudha and Dr. C. Chandrasekar, "An overview of Data Mining in Road Traffic and Accident Analysis", Journal of Computer Applications, Vol – II, No.4, Oct – Dec 2009.
  9. Miao Chong, Ajith Abraham and Marcin Paprzycki, "Traffic Accident Analysis Using Machine Learning Paradigms", Informatica 29 (2005) 89–98.
  10. M. Sowmya and Dr.P. Ponmuthuramalingam, "Analyzing the Road Traffic and Accidents with Classification Techniques", International Journal of Computer Trends and Technology (IJCTT) – volume 5 number 4 –Nov 2013.
  11. Amira A El Tayeb, Vikas Pareek, and Abdelaziz Araar.
  12. Applying association rules mining algorithms for traffic accidents in dubai. International Journal of Soft Computingand Engineering, September 2015.
  13. KMA Solaiman, Md Mustafizur Rahman, and Nashid Shahriar. Avra Bangladesh collection, analysis & visualization of road  accident data in Bangladesh. In Proceedings of InternationalConference on Informatics, Electronics & Vision, pages 1-6.IEEE, 2013.
  14. Eric M Ossiander and Peter Cummings. Freeway speed limits and traffic fatalities in washington state. Accident Analysis & Prevention, 34(1):13-18, 2002.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2018-01-31

Issue

Volume 4, Issue 1, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Nisha A. Solanke, Prof A. D. Gotmare, " Analysis of Roadway Traffic using Data Mining Techniques : A Review, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 1, pp.44-48, January-February-2018.