Prediction of brake pedal aperture for automatic wheel loader based on Deep LSTM RNN

Author:

Yong-Kang Su1,Jun-Ren Shi1,Chang-Hao Piao1,Ke-Xin Li1,Ying-Jie Tang1,Yu-Fei Liang1

Affiliation:

1. Chongqing University of Posts and Telecommunication,Chongqing,China

Funder

Research and Development

Publisher

IEEE

Reference19 articles.

1. A Recurrent Neural Network Solution for Predicting Driver Intention at Unsignalized Intersections[J];alex;IEEE l of Robotics and Automation,2018

2. Machine Learning Velocity Prediction-based Energy Management of Parallel Hybrid Electric Vehicle

3. Test Method for Evaluating the Energy Efficiency of Wheel Loaders[J];marcel;ATZoffhighway worldwide,2018

4. Intention Recognition and Trajectory Prediction for Vehicles Using LSTM Network[J];xue-wu;China Journal of Highway and Transport,2019

5. Phase independent finding and classification of wheel-loader work-cycles[J];michael;Automation in Construction,2020

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