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An Efficient Approach for Accident Severity Classification in Smart Transportation System

  • Research Article-Computer Engineering and Computer Science
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Abstract

Essential emergency services can be provided, and many lives can be saved if the severity of the road accident is analyzed well in time. Several works have been proposed to ascertain accident severity in intelligent transportation system based on traditional machine learning (ML) approaches such as Logistic Regression, Support Vector Machines (SVM), Random Forests, etc. The motive of this research is to propose an efficient and reliable approach for classifying the severity of road accidents through combined techniques of the feature space of extreme learning machine (ELM) and SVM, named as E-SVM, by making the best use of their characteristics. ELM performs feature mapping of input data, and further, the radial basis function kernel is utilized for training the SVM model, which performs the classification process. The Extra-Trees classifier used for feature selection leads to a reduced dataset of significant features which contributes towards efficient accident severity classification. The experimental results show that the proposed approach is better as compared to the other state-of-the-art ML classifiers both in terms of computational time and system performance, hence justifying its usage in real-life applications.

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Notes

  1. https://gnss.asia/new/ecall-emergency-alert-system-officially-launched-and-mandatory-for-new-eu-vehicles

  2. http://www.or.unimore.it/site/home/online-resources/machine-learning-for-severity-classification-of-accidents-involving-ptw.html

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Acknowledgements

The authors acknowledge the financial support provided by the Department of Science and Technology (DST), Government of India, under Innovation in Science Pursuit for Inspired Research (INSPIRE) Fellowship, INSPIRE Code- IF190242, for carrying out this research.

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  1. Department of Computer Science and Engineering, Thapar Institute of Engineering & Technology, Patiala, Punjab, 147004, India

    Ravneet Kaur, Rajendra Kumar Roul & Shalini Batra

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  1. Ravneet Kaur
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Kaur, R., Roul, R.K. & Batra, S. An Efficient Approach for Accident Severity Classification in Smart Transportation System. Arab J Sci Eng 48, 9645–9659 (2023). https://doi.org/10.1007/s13369-022-07274-7

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