Neeraj Dhanraj Bokde ¹, Aditya Gupta ¹, Kishore Kulat ¹

Affiliations
1 Visvesvaraya National Institute of Technology Nagpur (VNIT), Nagpur - 440010, Maharashtra, IN

Abstract

Objectives: To observe the road traffic accidents pattern across the states in India and to conclude whether the expenditure on road and transportation infrastructure is really justified with the traffic safety across the country. To decide the road safety policies across the states in India using backward elimination approach of regression model. Methods/Analysis: This study attempts to show statistical relations between road traffic accidents with predictive variables; number of vehicles registered, total length of roads, total number of road accidents and total expenditure on transportation infrastructure in the states of India. Time series data covering the period 2001 to 2013 was used on yearly road traffic accidents and other predictive variables for all 28 states of India. Findings: In recent decades, road accidents are becoming one of the most growing concerns in India. As mentioned in report of Ministry of Road Transport & Highways Government of India, road accidents impose significant costs which are about 3% GDP for India since 1999 to 2000. In 2004, India was 9th leading cause of death and expected to be 5th leading cause of death by 2030 worldwide. These facts are enough to catch attention of Government agencies and researchers towards safer traffic solutions. The results from the analysis shows few findings like expenditure on transportation infrastructure may not be an important predictive variable for road traffic accidents for pan India situations. Finally, if all the states of India partitioned in different clusters according to the behavior of states, the study states that there exists a strong positive correlation between road traffic accidents, number of vehicles registered and total length of roads. The relationship found to be statistically significant at 5% level of significance for each cluster of states. Applications/Improvements: The results obtained in study can assist transportation departments and Government bodies to implement better strategies across the country to ensure road traffic safety and reduce losses in terms of money and infrastructure costs.

Keywords

Policies in India, Regression Analysis, Road Accidents, Transportation, Road Safety

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Aditya Gupta ¹, Neeraj Bokde ¹, Dushyant Marathe ¹, Kishore ¹

Affiliations
1 Electronics and Communication, Visvesvaraya National Institute of Technology, Nagpur - 440010, Maharashtra, IN

Abstract

Objectives: A novel video based fire detection algorithm based on rule base technique using RGB and HSV color space and spatial analysis based on wavelet analysis is proposed. Methods/Statistical Analysis: Rule base technique utilizing RGB and HSV color space for extraction of fire pixels in the frame was used. Threshold based spatial energy methodology is used for differentiating fire and fire like objects. Wavelet analysis is performed for calculation of spatial energy. Texture analysis using Local Binary Pattern (LBP) is also performed when fire or fire like candidate having spatial energy near to threshold of fire pixel. Findings: The usage of RGB color space alone for identification of fire in the video frames is not sufficient as they suffer from false detection. Two novel rules based on HSV plane is proposed which have improved the detection ability of system when compare to previous studies. But still suffers from false detection. Spatial energy methodology based on differentiating fire and fire like objects performs well and has achieved greater efficiency with low false detection rate of 4% on standard datasets. Texture analysis using Local Binary Pattern (LBP) is also performed in rare case when fire candidate is having spatial energy near to that of fire like object category. This has helped in reducing the computational complexity of the system. The system shows 100% accurate results. Improvements: The results obtained for different standard datasets using the proposed hybrid spatial and texture base analysis shows 100% accuracy with zero false positive and false negative rates which is not observed in any of the present articles.

Keywords

Fire Detection, Local Binary Pattern (LBP), Spatial Analysis, Texture Analysis, Wavelet Analysis

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