Spatial-Channel Transformer Network for Trajectory Prediction on the Traffic Scenes

Understand

Predicting motion of surrounding agents is critical to real-world applications of tactical path planning for autonomous driving.

• Due to the complex temporal dependencies and social interactions of agents, on-line trajectory prediction is a challenging task.
• With the development of attention mechanism in recent years, transformer model has been applied in natural language sequence processing first and then image processing.
• In this paper, we present a Spatial-Channel Transformer Network for trajectory prediction with attention functions.