Forecast Trajectory

Forecast trajectory research focuses on accurately predicting the future paths of moving entities, from vehicles and pedestrians to power system energy production. Current efforts concentrate on developing sophisticated models, including those based on transformers, recurrent neural networks (like LSTMs), and novel energy function optimizations, to capture complex spatiotemporal dynamics and social interactions. These advancements are crucial for improving applications ranging from autonomous driving and robotics to urban planning and power grid management, enabling safer, more efficient, and robust systems. The field is also exploring the integration of rule-based systems with data-driven approaches to enhance safety and generalizability.