International Conference on Computer and Knowledge Engineering

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Driving Violation Detection Using Vehicle Data and Environmental Conditions

Authors :

Masood Ghasemi¹ Mahmood Fathy² Mohammad Shahverdy³

1- Department of Computer Engineering, Islamic Azad university, , Science and Research Branch 2- Iran University of Science and Technology 3- Iran University of Science and Technology

Keywords :

Traffic Violation,Support Vector Machine,Inter-Vehicular Network,Intelligent transportation system

Abstract :

Nowadays, the costs of car accidents have a catastrophic impact on human societies. To this end, a number of research have been conducted in order to design systems that are able to detect driving violations. Similarly, the present study was conducted to propose an approach that is able to detect and classify the driver’s behavior into two categories, which are labeled as traffic offender and non-offender, using the information collected via vehicle sensors and devices, such as cellphones. Therefore, the velocity signals, acceleration, engine Revolutions Per Minute (RPM), speed limits, and traffic being dispatched from the vehicle, cellphone, OpenStreetMap and google map were utilized to detect the driver's violation. Further, Support Vector Machine (SVM) was used to classify the driver as offender or non-offender, and the violation will be reported to the police via Inter-Vehicular networks.

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