Bidirectional Long Shot-Term Memory-Based Interactive Motion Prediction of Cut-In Vehicles in Urban Environments

Bidirectional Long Shot-Term Memory-Based Interactive Motion Prediction of Cut-In Vehicles in Urban Environments

This paper presents an interactive motion predictor to infer the intention of cut-in vehicles using a bidirectional long short-term memory (Bi-LSTM) module. The proposed predictor consists of three modules: maneuver recognition, trajectory prediction, and interaction. The driving data for training a...

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Bibliographic Details
Main Authors: Yonghwan Jeong, Kyongsu Yi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Autonomous vehicle
interactive motion prediction
machine learning
bidirectional long short-term memory
motion planning
Online Access:https://ieeexplore.ieee.org/document/9094191/

Internet

https://ieeexplore.ieee.org/document/9094191/

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