Due to its dense population, India frequently experiences traffic congestion, which puts lives in danger by trapping vehicles like ambulances, police cars, and fire trucks which run on road for emergency purpose. It becomes crucial to give these vehicles priority and allow for their easy passage. However, it becomes challenging or even impossible for traffic police to effectively handle such circumstances. Therefore, there is a requirement for an automated system that can locate emergency vehicles in high-traffic areas, alert the controller, or drive itself to direct other vehicles to make room. This study suggests an automated method for identifying emergency vehicles from CCTV footage that makes use of deep convolutional neural networks (CNN). The objective is to effectively identify and classify emergency vehicles in real-time, leveraging the power of advanced object detection techniques. With an accuracy of 91.73% and a loss of 0.2120, the suggested technique outperformed existing optimizers in accurately recognizing and classifying emergency vehicles.
Emergency vs Non-Emergency Vehicle Classification: Enhancing Intelligent Traffic Management Systems
01.09.2023
534333 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Intelligent Traffic Management in Emergency Situations
Springer Verlag | 2021
|Automatic Intelligent Traffic Controlling for Emergency Vehicle Rescuing
Springer Verlag | 2016
|Intelligent traffic accident emergency management system and method
Europäisches Patentamt | 2023
|