Emergency Vehicle

Research on emergency vehicle technology focuses on improving their rapid and safe transit through congested areas. Current efforts concentrate on real-time detection systems using audio analysis (e.g., via deep neural networks or simpler algorithms like extreme learning machines) and visual data processing (e.g., convolutional neural networks with output smoothing), often integrated with intelligent traffic management systems employing edge computing for reduced latency. These advancements aim to reduce response times in emergencies and improve overall traffic efficiency by prioritizing emergency vehicles, impacting both public safety and the efficiency of autonomous driving systems.