A Review of Deep Learning-Based Trajectory Prediction for Autonomous Vehicles

Abstract

Trajectory prediction is one of the key technologies of the autonomous driving system. The accurate and efficient prediction can assist the autonomous driving system in making correct decisions and ensuring driving safety. This paper summarizes the research on trajectory prediction for autonomous vehicles based on deep learning. First, trajectory prediction models’ input representation and output types are analyzed. Then, deep learning-based trajectory prediction methods are reviewed with their advantages and limitations. Finally, future research directions are proposed to address the shortcomings of existing methods in terms of multi-agent interaction modeling and generalization capability.