Balanced Training for the End-to-End Autonomous Driving Model Based on Kernel Density Estimation-Reference-Cited by-同舟云学术

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Balanced Training for the End-to-End Autonomous Driving Model Based on Kernel Density Estimation

Published:2024-06-02 Issue: Volume:35 Page:2361-2366
ISSN:
Container-title:2024 IEEE Intelligent Vehicles Symposium (IV)
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Author:

Yao Tong¹,Yuan Wei²,Zhang Songan²,Wang Chunxiang¹

Affiliation:

1. Shanghai Jiao Tong University,Key Laboratory of System Control and Information Processing, Ministry of Education of China,Department of Automation,Shanghai,China,200240

2. Shanghai Jiao Tong University,Global Institute of Future Technology,Shanghai,China,200240

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10587320/10588370/10588649.pdf?arnumber=10588649

Reference20 articles.

1. A Survey of Deep RL and IL for Autonomous Driving Policy Learning

2. End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners

3. TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving

4. MMFN: Multi-Modal-Fusion-Net for End-to-End Driving

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