Vehicle Perception

Vehicle perception, the ability of autonomous vehicles to understand their surroundings, aims to create robust and reliable systems for safe and efficient navigation. Current research emphasizes improving accuracy and efficiency through cooperative perception using vehicle-to-everything (V2X) communication and sensor fusion (e.g., camera-LiDAR, camera-radar), often employing advanced architectures like transformers and convolutional neural networks. These advancements are crucial for enhancing autonomous vehicle safety and reliability, addressing challenges like occlusions and adverse weather conditions, and ultimately contributing to the development of safer and more efficient transportation systems.