Weigh-in-motion Using Machine Learning and Telematics

Abstract

Driving overloaded vehicle causes road infrastructural damages, accidents, air pollution by excessive fuel consumption, and unusual expenses. Measuring the gross weight of a vehicle on a particular road segment without interrupting the traffic flow is a problem worth researching, and its solutions have several economic benefits. This paper proposes an alternative way of finding an overloaded vehicle in motion, by introducing a novel approach in inferring the weight of a vehicle on a road segment using Telematics data and Machine Learning.