A Full Transfer Learning LSTM-Based Fractional Order Optimization Method of GM(<i>r</i>,2) for Inferring Driving Intention-Reference-Cited by-同舟云学术

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A Full Transfer Learning LSTM-Based Fractional Order Optimization Method of GM(r,2) for Inferring Driving Intention

Published:2024-09 Issue:9 Volume:25 Page:10741-10753
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Lian Yufeng¹^ORCID,Sun Zhongbo¹^ORCID,Liu Shuaishi¹^ORCID,Nie Zhigen²^ORCID

Affiliation:

1. School of Electrical and Electronic Engineering and the Institute of Robotics and Engineering, Changchun University of Technology, Changchun, China

2. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China

Funder

National Natural Science Foundation of China

Science and Technology Development Project of Jilin Province

Science and Technology Projects of Jilin Province Education Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10659279/10471312.pdf?arnumber=10471312

Reference43 articles.

1. Effect of the Uncertainty Level of Vehicle-Position Information on the Stability and Safety of the Car-Following Process

2. Comparison and Evaluation of Algorithms for LiDAR-Based Contour Estimation in Integrated Vehicle Safety

3. Driver’s Intention Identification With the Involvement of Emotional Factors in Two-Lane Roads

4. Driver Intention Recognition: State-of-the-Art Review

5. Driving Intention Inference Based on a Deep Neural Network with Dropout Regularization from Adhesion Coefficients in Active Collision Avoidance Control Systems

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