DeepAI
Log In Sign Up

MPA: MultiPath++ Based Architecture for Motion Prediction

06/20/2022
by   Stepan Konev, et al.
6

Autonomous driving technology is developing rapidly and nowadays first autonomous rides are being provided in city areas. This requires the highest standards for the safety and reliability of the technology. Motion prediction part of the general self-driving pipeline plays a crucial role in providing these qualities. In this work we present one of the solutions for Waymo Motion Prediction Challenge 2022 based on MultiPath++ ranked the 3rd as of May, 26 2022. Our source code is publicly available on GitHub.

READ FULL TEXT

page 1

page 2

page 3

06/05/2022

MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving

To plan a safe and efficient route, an autonomous vehicle should anticip...
12/15/2021

Estimating Uncertainty For Vehicle Motion Prediction on Yandex Shifts Dataset

Motion prediction of surrounding agents is an important task in context ...
11/18/2022

Rationale-aware Autonomous Driving Policy utilizing Safety Force Field implemented on CARLA Simulator

Despite the rapid improvement of autonomous driving technology in recent...
07/29/2022

Perspectives on the System-level Design of a Safe Autonomous Driving Stack

Achieving safe and robust autonomy is the key bottleneck on the path tow...
11/01/2020

Beelines: Evaluating Motion Prediction Impact on Self-Driving Safety and Comfort

The commonly used metrics for motion prediction do not correlate well wi...
08/03/2022

MixNet: Structured Deep Neural Motion Prediction for Autonomous Racing

Reliably predicting the motion of contestant vehicles surrounding an aut...
09/21/2022

Stochastic Future Prediction in Real World Driving Scenarios

Uncertainty plays a key role in future prediction. The future is uncerta...