Intelligent Vehicle Moving Trajectory Prediction Based on Residual Attention Network

Intelligent Vehicle Moving Trajectory Prediction Based on Residual Attention Network

Skilled drivers have the driving behavioral characteristic of pre-sighted following, and similarly intelligent vehicles need accurate prediction of future trajectories. The LSTM (Long Short-Term Memory) is a common model of trajectory prediction. The existing LSTM models pay less attention to the in...

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Bibliographic Details
Main Authors: Zhengcai Yang, Zhenhai Gao, Fei Gao, Chuan Shi, Lei He, Shirui Gu
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:World Electric Vehicle Journal
Subjects:
vehicle engineering
trajectory prediction
attention mechanism
residual connection
Long Short-Term Memory
interactive features
Online Access:https://www.mdpi.com/2032-6653/13/3/47

Internet

https://www.mdpi.com/2032-6653/13/3/47

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