Driver Usage Risk Profiling by Analyzing Vehicle Driving Behavior using Machine Learning Model Based on Vehicular Cloud Telematics Data

Kumar, Anuj (2018) Driver Usage Risk Profiling by Analyzing Vehicle Driving Behavior using Machine Learning Model Based on Vehicular Cloud Telematics Data. Masters thesis, Dublin, National College of Ireland.

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Abstract

This paper is a novel approach to assist the vehicle insurance companies for calculating the annual insurance premium cost for the vehicle owner by developing Vehicle Prediction System (VPS) using Vehicular Cloud and Machine learning Models. By the development of new technologies in recent years, the potential to handle the Vehicle sensing data is increased. This Proposed system is using real-time operational information from a vehicle including engine Revolutions per minute (RPM), vehicle speed, throttle position, Mass Air Flow (MAF), engine load, time advance through On-Board Diagnostic (OBD) interface. By utilising Cloud infrastructure and Machine learning algorithms, the proposed system will make use of vehicle data to create a drive behaviour prediction model to calculate the risk profile of insurance policyholder. Using Cloud Computing technology, a massive amount of Telematics data can be handle generated by these vehicular sensors and Machine learning algorithms can be used to create a risk profile of the vehicle owner by measuring the driving behaviour. This proposed model is using Unsupervised and Supervised machine learning methods to measure the driving behaviour. This platform can be beneficial for the policy subscriber as this prediction model will be used by the insurance companies to improve the User-based insurance (UBI) and Pay-as-you drive (PAYD) pricing model by offering lucrative price to their insurance subscribers.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Dan English
Date Deposited:	04 Jun 2020 12:28
Last Modified:	04 Jun 2020 12:28
URI:	https://norma.ncirl.ie/id/eprint/4245

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