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2023 | OriginalPaper | Buchkapitel

An Improved Machine Learning Algorithm for Crash Severity and Fatality Insight in VANET Network

verfasst von : S. Bharathi, P. Durgadevi

Erschienen in: Intelligent Cyber Physical Systems and Internet of Things

Verlag: Springer International Publishing

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Abstract

A vehicular ad hoc network (VANET) is a wireless network that connects a group of moving or stationary vehicles together. VANETs were primarily used to provide safety and comfort to drivers in automotive environments until recently. Clustering is an important concept in vehicular ad hoc network (VANET) where several vehicles join to form a group based on common features. Clustering increases the complexity of data. The assessment of road accident strategies in Machine learning is presented in this paper. A road collision is the most unwanted and unexpected occurrence that may happen to a vehicle, due to the fact that they happen regularly. The goal of this study was to investigate the correlation between the concentration of collisions and injury. There are several factors that influence crashes, including weather, road conditions, driver distraction, and misread vehicle signals.

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Vorheriges Kapitel Chatbots: A Survey of the Technology

Nächstes Kapitel Network Monitoring of Cyber Physical System

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Titel: An Improved Machine Learning Algorithm for Crash Severity and Fatality Insight in VANET Network
verfasst von: S. Bharathi
P. Durgadevi
Verlag: Springer International Publishing
Buch: Intelligent Cyber Physical Systems and Internet of Things
Print ISBN: 978-3-031-18496-3

Electronic ISBN: 978-3-031-18497-0

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-3-031-18497-0_50

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