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Line Encoding Based Method to Analyze Performance of Indian States in Road Safety

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Computational Intelligence in Pattern Recognition

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 999))

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Road accidents are becoming a global crisis which does not only cost human life but also affect the economic condition of a nation. Therefore it is gaining the interest of several researchers to analyze the influential factors behind road accidents and suggest the preventive measures. A large country like India is also suffering from a substantial amount of road accidents and try to incorporate improve road safety measures. In this paper, we evaluate the performances of different Indian states in road safety measures based on the recorded road accident data. The current analysis is based on a novel line encoding method which categorizes Indian states into three categories, i.e., best performer, average performer, and stragglers. Results have efficiently identified the states that reduce road accidents and the potential states which need to improve on road safety to a great extent. The outcome after ranking the states based on our approach shows there is a high linear correlation between accident rate with population and number of vehicles whereas accident and literacy rate shares an inverse correlation. The satisfactory results based on our approach definitely enlight the interdisciplinary research domains.

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Correspondence to Samya Muhuri .

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Muhuri, S., Chakraborty, S., Das, D. (2020). Line Encoding Based Method to Analyze Performance of Indian States in Road Safety. In: Das, A., Nayak, J., Naik, B., Pati, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. Advances in Intelligent Systems and Computing, vol 999. Springer, Singapore.

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