A Unified On-Demand Driving Behavior Model Based on Automated Machine Learning (AutoML)-Reference-Cited by-同舟云学术

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A Unified On-Demand Driving Behavior Model Based on Automated Machine Learning (AutoML)

Published:2023-11-17 Issue: Volume:32 Page:5831-5836
ISSN:
Container-title:2023 China Automation Congress (CAC)
language:
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Author:

Li Jiaxin¹,Ren Haoyan²,Chai Chen¹,Shi Xiupeng³

Affiliation:

1. College of Transportation Engineering, Tongji University,The Key Laboratory of Road and Traffic Engineering, Ministry of Education,Shanghai,China,201804

2. School of Mathematical Sciences, Tongji University,Shanghai,China,200092

3. College of Microelectronics, Shanghai University,Shanghai,China,201899

Funder

Chinese National Science Foundation

Fundamental Research Funds for the Central Universities

Science and Technology Commission of Shanghai Municipality

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10450150/10449968/10451127.pdf?arnumber=10451127

Reference19 articles.

1. A generative car-following model conditioned on driving styles

2. Modeling Human Driving Behavior Through Generative Adversarial Imitation Learning

3. A Learning-Based Discretionary Lane-Change Decision-Making Model With Driving Style Awareness

4. Modeling driver’s evasive behavior during safety–critical lane changes: Two-dimensional time-to-collision and deep reinforcement learning

5. Vehicle Turning Behavior Modeling at Conflicting Areas of Mixed-Flow Intersections Based on Deep Learning

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