Cross-Scenario Maneuver Decision with Adaptive Perception for Autonomous Driving

Author:

Fu Yuan1ORCID,Liu Shuncheng1ORCID,Xia Yuyang1ORCID,Guo Fangda2ORCID,Zheng Kai1ORCID

Affiliation:

1. University of Electronic Science and Technology of China, Chengdu, China

2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

Funder

Shenzhen Municipal Science and Technology R&D Funding Basic Research Program

Municipal Government of Quzhou

Key Laboratory of Data Intelligence and Cognitive Computing, Longhua District, Shenzhen

National Natural Science Foundation of China

Publisher

ACM

Reference39 articles.

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2. Mariusz Bojarski , Philip Yeres , Anna Choromanska , Krzysztof Choromanski , Bernhard Firner , Lawrence Jackel , and Urs Muller . 2017. Explaining how a deep neural network trained with end-to-end learning steers a car. arXiv preprint arXiv:1704.07911 ( 2017 ). Mariusz Bojarski, Philip Yeres, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Lawrence Jackel, and Urs Muller. 2017. Explaining how a deep neural network trained with end-to-end learning steers a car. arXiv preprint arXiv:1704.07911 (2017).

3. Greg Brockman , Vicki Cheung , Ludwig Pettersson , Jonas Schneider , John Schulman , Jie Tang , and Wojciech Zaremba . 2016. Openai gym. arXiv preprint arXiv:1606.01540 ( 2016 ). Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba. 2016. Openai gym. arXiv preprint arXiv:1606.01540 (2016).

4. Jianyu Chen , Bodi Yuan , and Masayoshi Tomizuka . 2019. Model-free deep reinforcement learning for urban autonomous driving. In 2019 IEEE intelligent transportation systems conference (ITSC) . IEEE , 2765--2771. Jianyu Chen, Bodi Yuan, and Masayoshi Tomizuka. 2019. Model-free deep reinforcement learning for urban autonomous driving. In 2019 IEEE intelligent transportation systems conference (ITSC). IEEE, 2765--2771.

5. SUMO’s Lane-Changing Model

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