A Comparative Study of Neural Networks for Emergency Vehicle Detection in Traffic

Abstract

This study explores the application of Neural Networks for efficient emergency vehicle identification. Utilizing a dataset of emergency and non-emergency vehicle images, the model demonstrates high accuracy in classification. A noteworthy use case involves real-time integration with traffic systems, where the identification of an emergency vehicle triggers an automatic change of traffic lights to green, facilitating swift and unimpeded passage.