Abstract
Road accidents may not be stopped altogether, but can be reduced. Driver emotions such as sad, happy, and anger can be one reason for accidents. At the same time, environment conditions such as weather, traffic on the road, load in the vehicle, type of road, health condition of driver, and speed can also be the reasons for accidents. Hidden patterns in accidents can be extracted so as to find the common features between accidents. This paper presents the results of the framework from the research study on road accident data of major national highways that pass through Krishna district for the year 2013 by applying machine learning techniques into analysis. These datasets collected from police stations are heterogeneous. Incomplete and erroneous values are corrected using data cleaning measures, and relevance attributes are identified using attribute selection measures. Clusters that are formed using K-medoids, and expectation maximization algorithms are then analyzed to discover hidden patterns using a priori algorithm. Results showed that the selected machine learning techniques are able to extract hidden patterns from the data. Density histograms are used for accident data visualization.
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
Road safety and traffic management : Report of the committee Planning Commission, Government of India in February 2007 (2007)
Rayle L, Pai M. Scenarios for future urbanization: carbon dioxide emissions from passenger travel in three Indian cities. Transportation Research Record: Journal of the Transportation Research Board, 2193:124–131 (2010)
http://www.deccanchronicle.com/130629/news-current-affairs/article/andhra-pradesh-ranked-3rd-road-accidents last accessed June 29th 2013
Road Accidents in India Issues & Dimensions, Ministry of Road Transport & Highways Government of India (2014)
SAMI AYRAMO, PASI PIRTALA, Mining road traffic accidents, Reports of the Department of Mathematical Information Technology Series C. Software and Computational Engineering No. C. 2/2009 (2009)
S. SHANTHI, DR.R. GEETHA RAMANI, Classification of Vehicle Collision Patterns in Road Accidents using Data Mining Algorithms, International Journal of Computer Applications (0975–8887) Volume 35– No.12, December 2011 (2011)
S. SHANTHI, R. GEETHA RAMANI, Feature Relevance Analysis and Classification of Road Traffic Accident Data through Data Mining Techniques, Proceedings of the World Congress on Engineering and Computer Science 2012 Vol I WCECS (2012)
Luis MartÃn, Leticia Baena, Laura Garach, Griselda López, Juan de Oña Using Data Mining Techniques to Road Safety Improvement in Spanish Roads, Volume 160, Pages 607–614, XI Congreso de Ingenieria del Transporte (CIT 2014)
Tibebe Beshah, Shawndra Hill, Mining Road Traffic Accident Data to Improve Safety: Role of Road- related Factors on Accident Severity in Ethiopia, AAAI Spring Symposium Series (2010)
Amira A. El Tayeb, Vikas Pareek, Abdelaziz Araar Applying Association Rules Mining Algorithms for Traffic Accidents in Dubai, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-5 Issue-4, (2015)
K. Geetha, 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, (2015)
Jiawei Han and Micheline Kamber, Data Mining Concepts and Techniques, 2 ed, Elsevier publishers
Acknowledgements
I thank University Grants Commission (UGC), for funding this project. I also thank police authorities, Andhra Pradesh, for providing the required information. I am also thankful to the management of Siddhartha Academy for providing me resources and environment for successfully completing this project. Finally, I thank my students who helped me during the implementation of this project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vasavi, S. (2018). Extracting Hidden Patterns Within Road Accident Data Using Machine Learning Techniques. In: Mishra, D., Azar, A., Joshi, A. (eds) Information and Communication Technology . Advances in Intelligent Systems and Computing, vol 625. Springer, Singapore. https://doi.org/10.1007/978-981-10-5508-9_2
Download citation
DOI: https://doi.org/10.1007/978-981-10-5508-9_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5507-2
Online ISBN: 978-981-10-5508-9
eBook Packages: EngineeringEngineering (R0)