Advancing Automated Testing on Proving Grounds: Rapid Obstacle Detection in Highly Dynamic Driving

Automated vehicle testing is crucial for ensuring safety, consistency, and efficiency as the number and complexity of vehicle tests on proving grounds increase. In dynamic tests with high speeds and sharp curves, early and long-range obstacle detection is essential for maintaining safety. Therefore, a Rapid and Long-range Detector (RLD) algorithm is necessary to seamlessly integrate into a sensor network, which includes vehicle and Roadside Unit (RSU) sensors, to monitor robot-guided vehicles. This paper presents a new method, based on a given approach, for rapid and comprehensive obstacle detection with minimal latency, using trajectory and motion data from robot-guided vehicles. This method uses point cloud-based sensors for reliable and precise detection. Our approach has proven to be effective and robust in a series of experiments involving a range of highly dynamic driving scenarios under different conditions. These results provide a solid foundation for ensuring safe and automated vehicle testing on proving grounds.