  Level 5 Autonomous Driving, a technology that a fully automated vehicle (AV)
requires no human intervention, has raised serious concerns on safety and
stability before widespread use. The capability of understanding and predicting
future motion trajectory of road objects can help AV plan a path that is safe
and easy to control. In this paper, we propose a network architecture that
parallelizes multiple convolutional neural network backbones and fuses features
to make multi-mode trajectory prediction. In the 2020 ICRA Nuscene Prediction
challenge, our model ranks 15th on the leaderboard across all teams.
