Emergency and Non-Emergency Vehicle Classification using Machine Learning

Emergency and Non-Emergency Vehicle Classification using Machine Learning

ASWATHY T G

20MCAR0105

PROF. DR. GANESH D

DEPARTMENT OF COMPUTER APPLICATION

JAIN KNOWLEDGE CAMPUS, BANGALORE

JAIN UNIVERSITY BANGALORE, INDIA.

ABTRACT

A highly populated country like India faces too much traffic jam. Sometimes emergency vehicles like ambulances, fire engine get stuck in the traffic causing threat to life in many cases. It is important to give priority to this vehicle and help to clear its path. But it is difficult or sometimes impossible for traffic police to handle this. So, differentiating a vehicle into an emergency and non-emergency category can be an important component in traffic monitoring as well as self-drive car systems can easy understand the emergency vehicle as reaching on time to their destination is critical for these services. In case of automatic vehicles, they need an alert input message like this to clear the path to emergency vehicles. on other hand, this is useful for all types of vehicle to get sudden alert to clear the path to emergency vehicles. For this reason, we need an automated system that will be able to detect an emergency vehicle in heavy traffic road, let the controller know or automatically navigate other vehicles to clear its path. In this work, we have proposed an automated system to detect emergency vehicle using the Machine Learning.

KEYWORDS: Intelligent Transport System (ITS), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Decision Tree, Recurrent Neural Network (RNN), space invariant artificial neural networks (SIANN)