Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention

Understand

In autonomous driving, accurately interpreting the movements of other road users and leveraging this knowledge to forecast future trajectories is crucial.

• This is typically achieved through the integration of map data and tracked trajectories of various agents.
• Numerous methodologies combine this information into a singular embedding for each agent, which is then utilized to predict future behavior.
• However, these approaches have a notable drawback in that they may lose exact location information during the encoding process.