Cooperative Driving Automation

Cooperative Driving Automation (CDA) aims to improve the safety and efficiency of autonomous vehicles by enabling them to share information and coordinate their actions. Current research heavily focuses on developing robust cooperative perception systems, often leveraging infrastructure-based sensors like roadside LiDAR in conjunction with vehicle-based sensors, and employing advanced algorithms such as deep learning for object detection and tracking, and large language models for decision-making and conflict resolution. This field is significant because it addresses limitations of individual vehicle autonomy in complex traffic scenarios, paving the way for safer and more efficient transportation systems.