DeepAI
Log In Sign Up

Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty

04/26/2021
by   Boris Ivanovic, et al.
3

Reasoning about the future behavior of other agents is critical to safe robot navigation. The multiplicity of plausible futures is further amplified by the uncertainty inherent to agent state estimation from data, including positions, velocities, and semantic class. Forecasting methods, however, typically neglect class uncertainty, conditioning instead only on the agent's most likely class, even though perception models often return full class distributions. To exploit this information, we present HAICU, a method for heterogeneous-agent trajectory forecasting that explicitly incorporates agents' class probabilities. We additionally present PUP, a new challenging real-world autonomous driving dataset, to investigate the impact of Perceptual Uncertainty in Prediction. It contains challenging crowded scenes with unfiltered agent class probabilities that reflect the long-tail of current state-of-the-art perception systems. We demonstrate that incorporating class probabilities in trajectory forecasting significantly improves performance in the face of uncertainty, and enables new forecasting capabilities such as counterfactual predictions.

READ FULL TEXT
01/09/2020

Trajectron++: Multi-Agent Generative Trajectory Forecasting With Heterogeneous Data for Control

Reasoning about human motion through an environment is an important prer...
10/07/2021

Propagating State Uncertainty Through Trajectory Forecasting

Uncertainty pervades through the modern robotic autonomy stack, with nea...
11/02/2022

Heterogeneous Trajectory Forecasting via Risk and Scene Graph Learning

Heterogeneous trajectory forecasting is critical for intelligent transpo...
07/21/2021

Rethinking Trajectory Forecasting Evaluation

Forecasting the behavior of other agents is an integral part of the mode...
07/07/2022

CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationships

As machine learning models become increasingly prevalent in motion forec...
03/13/2013

The Bounded Bayesian

The ideal Bayesian agent reasons from a global probability model, but re...
03/05/2019

A Prediction Tournament Paradox

In a prediction tournament, contestants "forecast" by asserting a numeri...