Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture

In this paper, we propose a deep learning based vehicle trajectory prediction technique which can generate the future trajectory sequence of surrounding vehicles in real time. We employ the encoder-decoder architecture which analyzes the pattern underlying in the past trajectory using the long short...

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Bibliographic Details

Published in:	2018 IEEE Intelligent Vehicles Symposium (IV) pp. 1672 - 1678
Main Authors:	Park, Seong Hyeon, Kim, ByeongDo, Kang, Chang Mook, Chung, Chung Choo, Choi, Jun Won
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.06.2018
Subjects:	Computer architecture Decoding Machine learning Microprocessors Real-time systems Task analysis Trajectory
Online Access:	Get full text
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