An Ensemble Learning Framework for Vehicle Trajectory Prediction in Interactive Scenarios

Precisely modeling interactions and accurately predicting trajectories of surrounding vehicles are essential to the decision-making and path-planning of intelligent vehicles. This paper proposes a novel framework based on ensemble learning to improve the performance of trajectory predictions in interactive scenarios. The framework is termed...

Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery

In urban environments, the complex and uncertain intersection scenarios are challenging for autonomous driving. To ensure safety, it is crucial to develop an adaptive decision making system that can handle the interaction with other vehicles. Manually designed model-based methods are reliable in common scenarios. But in uncertain environments,...

Thin-Film Lithium Niobate Acoustic Delay Line Oscillators

In this work, thin-film lithium niobate (LiNbO₃) acoustic delay line (ADL) based oscillators are experimentally investigated for the first time for the application of single-mode oscillators and frequency comb generation. The design space for the ADL-based oscillator is first analyzed, illustrating that the key to low phase noise...