This paper proposes ananalytical solution for binary classification of driving behaviourinto safe or rash.A methodology is designed and developed which consists of cleaning and scrubbing of raw driving data throughidentification of best set of parameters, iterative cluster-analysis, creation of target variables by benchmarking against theoretical relations and eventually performing supervised regression using support vector machine on the prepared dataset to classify a fresh driving data point into safe or rash driving. A bad and careless driving is depicted as ‘rash driving’ while a good and efficient driving is depicted as ‘safe driving’. The proposed methodology has the potential of applying to real-world driver profiling system.

Classification, rash driving analysis, on board diagnostic, driver profiling, hierarchical clustering, principal component analysis, support vector machine

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