TPNet: Trajectory Proposal Network for Motion Prediction

04/26/2020
by   Liangji Fang, et al.
13

Making accurate motion prediction of the surrounding traffic agents such as pedestrians, vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion prediction methods have attempted to learn to directly regress the exact future position or its distribution from massive amount of trajectory data. However, it remains difficult for these methods to provide multimodal predictions as well as integrate physical constraints such as traffic rules and movable areas. In this work we propose a novel two-stage motion prediction framework, Trajectory Proposal Network (TPNet). TPNet first generates a candidate set of future trajectories as hypothesis proposals, then makes the final predictions by classifying and refining the proposals which meets the physical constraints. By steering the proposal generation process, safe and multimodal predictions are realized. Thus this framework effectively mitigates the complexity of motion prediction problem while ensuring the multimodal output. Experiments on four large-scale trajectory prediction datasets, i.e. the ETH, UCY, Apollo and Argoverse datasets, show that TPNet achieves the state-of-the-art results both quantitatively and qualitatively.

READ FULL TEXT

page 1

page 3

page 8

03/22/2021

Multimodal Motion Prediction with Stacked Transformers

Predicting multiple plausible future trajectories of the nearby vehicles...
08/31/2022

Class-Aware Attention for Multimodal Trajectory Prediction

Predicting the possible future trajectories of the surrounding dynamic a...
07/09/2021

Probabilistic Trajectory Prediction with Structural Constraints

This work addresses the problem of predicting the motion trajectories of...
11/26/2021

Hierarchical Motion Encoder-Decoder Network for Trajectory Forecasting

Trajectory forecasting plays a pivotal role in the field of intelligent ...
03/05/2021

FloMo: Tractable Motion Prediction with Normalizing Flows

The future motion of traffic participants is inherently uncertain. To pl...
06/03/2020

MultiNet: Multiclass Multistage Multimodal Motion Prediction

One of the critical pieces of the self-driving puzzle is understanding t...
02/17/2022

CSCNet: Contextual Semantic Consistency Network for Trajectory Prediction in Crowded Spaces

Trajectory prediction aims to predict the movement trend of the agents l...