Surround Vehicle Motion Prediction Using LSTM-RNN for Motion Planning of Autonomous Vehicles at Multi-Lane Turn Intersections

Surround Vehicle Motion Prediction Using LSTM-RNN for Motion Planning of Autonomous Vehicles at Multi-Lane Turn Intersections

This paper presents a surround vehicle motion prediction algorithm for multi-lane turn intersections using a Long Short-Term Memory (LSTM)-based Recurrent Neural Network (RNN). The motion predictor is trained using the states of subject and surrounding vehicles, which are collected by sensors mounte...

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Bibliographic Details
Main Authors: Yonghwan Jeong, Seonwook Kim, Kyongsu Yi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Open Journal of Intelligent Transportation Systems
Subjects:
Autonomous vehicle
intersection driving data
motion prediction
machine learning
recurrent neural network
long short-term memory
Online Access:https://ieeexplore.ieee.org/document/8957421/

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