An Empirical Analysis of Trajectory Prediction Techniques for Motion Prediction in Waymo Dataset

Abstract

The Waymo is the prime and most varied autonomous driving dataset that improves and enhances itself every year. Motion Prediction is a considerable challenge in 2023. This manuscript analyses five considerable methods namely MTR-A, Wayformer, DenseTNT, Golfer and MultiPath++ for their technology applied. The analysis revealed that the Transformer network could achieve a state of the art trajectory prediction as well as scale to many workloads.