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

ParallelNet: Multi-mode Trajectory Prediction by Multi-mode Trajectory Fusion