Learning Automated Driving in Complex Intersection Scenarios Based on Camera Sensors: A Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

Learning Automated Driving in Complex Intersection Scenarios Based on Camera Sensors: A Deep Reinforcement Learning Approach

Author:

Li Guofa¹^ORCID,Lin Siyan¹^ORCID,Li Shen²^ORCID,Qu Xingda¹^ORCID

Affiliation:

1. College of Mechatronics and Control Engineering, Institute of Human Factors and Ergonomics, Shenzhen University, Shenzhen, Guangdong, China

2. Department of Civil Engineering, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

Shenzhen Fundamental Research and Discipline Layout project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference47 articles.

3. Bidirectional LSTM-CRF models for sequence tagging;huang;arXiv 1508 01991,2015

5. Human learning in Atari;tsividis;Proc AAAI Assoc Spring Symp Sci Intell Comput Principles Natural Artif Intell,2017

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