Automated Driving System

Automated driving systems (ADS) research centers on developing and rigorously evaluating self-driving vehicles, aiming to improve road safety and efficiency. Current research emphasizes robust data acquisition and processing techniques, including the use of cooperative perception from multiple vehicles and advanced algorithms for object detection and tracking, often incorporating deep learning and fuzzy logic. A key focus is establishing standardized and transparent methods for benchmarking ADS safety performance against human drivers, using both real-world data and sophisticated simulation models that incorporate realistic driver behavior and vehicle dynamics. These efforts are crucial for building public trust and informing regulatory decisions regarding the deployment of ADS technology.