Estimating Uncertainty For Vehicle Motion Prediction on Yandex Shifts Dataset

• URL: http://arxiv.org/abs/2112.08355v1
• Date: Wed, 15 Dec 2021 18:58:55 GMT
• Title: Estimating Uncertainty For Vehicle Motion Prediction on Yandex Shifts Dataset
• Authors: Alexey Pustynnikov, Dmitry Eremeev
• Abstract summary: This work focuses on developing models which are robust to distributional shift and able to measure uncertainty of their predictions. In this work we present the approach that significantly improved provided benchmark and took 2nd place on the leaderboard.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Motion prediction of surrounding agents is an important task in context of autonomous driving since it is closely related to driver's safety. Vehicle Motion Prediction (VMP) track of Shifts Challenge focuses on developing models which are robust to distributional shift and able to measure uncertainty of their predictions. In this work we present the approach that significantly improved provided benchmark and took 2nd place on the leaderboard.

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