Driving pattern analysis to determine driver behaviors for local authority based on cloud using OBD II

Abstract

Aggressive driving is the main cause of road accidents and it is affected by driving behavior which endanger not only the driver himself but also the people around. It is very significant step to identify such behaviors of the drivers by the local authorities which would help in correcting the behaviors or to understand the root cause of the accidents by analyzing the data recorded by the On Board Diagnostic( OBD ) II device. An aggressive driving behavior is characterized by sudden change inmaneuverings of vehicle which eventually yields non uniform parameters values returned by the ECU (Engine Control Unit) system without any specific reason. In this research work, the real time data is recorded from ECU using OBD II and the accelerometer. The Artificial Intelligenceis used in grouping the different types of data toidentifythe behaviors data on the basis of similarity of datapoints.The purpose of this research work is to identify such drivers and reduce the risk of further accidents.The work identifies the behaviors as bad, normal and aggressive behavior. As the clustering is made on basis crowded data which signifies the similar driving patterns for most of the time in the course of recording, therefore, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) unsupervised learning algorithm was used. The data will be sent to the cloud so that it can be accessed by the authority from any place for further action.ANOVA test is conducted usingIBMSPSS(Statistical Package for the Social Sciences) package to compare and determine the best method to collect data by comparing the means between groups.