Abstract
Road accident is one of the major reasons for loss of human lives, especially in developing nations with poor road infrastructure and a driver needs to constantly negotiate with several adverse conditions to ensure safety. In this paper, we study several such adverse conditions that are relevant to safe driving and propose a novel method for identifying them as well as characterizing driving behavior for such conditions. Experimental results reveal that our proposed methodology is promising and more flexible than prior work in this area. In particular, our prediction results reveal that our methodology is an aggressive one where most of the bad driving behaviors are determined at the cost of a few instances of good behavior being falsely characterized as bad ones.
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Notes
- 1.
WISQARS: www.cdc.gov/injury/wisqars.
- 2.
National Crime Records Bureau record: http://ncrb.nic.in/adsi2008/accidental-deaths-08.pdf.
- 3.
- 4.
In all our experiments we have used \(r = 2.5\) for the clustering operation, both for segmentation as well as for driving behavior classification.
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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Banerjee, D., Banerjee, N., Chakraborty, D., Iyer, A., Mittal, S. (2014). How’s My Driving? A Spatio-Semantic Analysis of Driving Behavior with Smartphone Sensors. In: Stojmenovic, I., Cheng, Z., Guo, S. (eds) Mobile and Ubiquitous Systems: Computing, Networking, and Services. MobiQuitous 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 131. Springer, Cham. https://doi.org/10.1007/978-3-319-11569-6_51
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DOI: https://doi.org/10.1007/978-3-319-11569-6_51
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