基于Waymo数据集的运动预测轨迹预测技术实证分析

3C Tecnología Pub Date : 2023-06-25 DOI:10.17993/3ctecno.2023.v12n2e44.49-63

Devansh Arora, Parul Arora, Ritika Wason

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引用次数: 0

摘要

Waymo是最好的、最多样化的自动驾驶数据集，每年都在改进和增强自己。2023年，运动预测是一个相当大的挑战。本文分析了五种重要的方法，即MTR-A, Wayformer, DenseTNT, Golfer和MultiPath++的技术应用。分析表明，Transformer网络可以实现最先进的轨迹预测，并可扩展到许多工作负载。

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

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.

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3C Tecnología

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