Motion Prediction for Autonomous Vehicles from Lyft Dataset using Deep Learning

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原文链接

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外文摘要：Autonomous Vehicles are expected to change the future of worldwide transportation system。 As self-driving cars are facing a lot of engineering challenges， it is one of the hottest topics in recent research。 One such challenge is to build models to predict the movements of traffic agents such as cars， cyclists， pedestrians etc around the self-driving cars。 The objective of this paper is to analyse the prediction efficiency of various deep learning models by calculating root mean square error score。 This deep learning models takes a current state of the surrounding and depending on that predict the motion for the agents。

外文关键词：

Autonomous Vehicles (AV)Deep Learning (DL)Artificial Intelligence (AI)

作者：

Sampurna Mandal、Swagatam Biswas、Valentina E. Balas、Rabindra Nath Shaw、Ankush Ghosh

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作者单位：

School of Engineering and Applied Science, The Neotia University, India

Aurel Vlaicu University of Arad, Romania

Galgotias University, India

会议名称：

IEEE International Conference on Computing Communication and Automation

会议地点：

Greater Noida(IN)

会议母体文献：

2020 IEEE 5th International Conference on Computing Communication and Automation

页码：

768-773

出版时间：

2020

DOI：

10.1109/ICCCA49541.2020.9250790