Loading [a11y]/accessibility-menu.js
Machine Learning for Severity Classification of Accidents Involving Powered Two Wheelers | IEEE Journals & Magazine | IEEE Xplore

Machine Learning for Severity Classification of Accidents Involving Powered Two Wheelers


Abstract:

Road traffic safety is one of the major challenges for the future of smart cities and transportation networks. Despite several solutions exist to reduce the number of fat...Show More

Abstract:

Road traffic safety is one of the major challenges for the future of smart cities and transportation networks. Despite several solutions exist to reduce the number of fatalities and severe accidents happening daily in our roads, this reduction is smaller than expected and new methods and intelligent systems are needed. The emergency Call is an initiative of the European Commission aimed at providing rapid assistance to motorists thanks to the implementation of a unique emergency number. In this work, we study the problem of classifying the severity of accidents involving Powered Two Wheelers, by exploiting machine learning systems based on features that could be reasonably collected at the moment of the accident. An extended study on the set of features allows to identify the most important factors that enable to distinguish accident severity. The system we develop achieves around 90% of precision and recall on a large, publicly available corpus, using only a set of eleven features.
Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: 21, Issue: 10, October 2020)
Page(s): 4308 - 4317
Date of Publication: 17 September 2019

ISSN Information:

Funding Agency:


Contact IEEE to Subscribe

References

References is not available for this document.