AADS: Augmented autonomous driving simulation using data-driven algorithms-Reference-Cited by-同舟云学术

AADS: Augmented autonomous driving simulation using data-driven algorithms

Published:2019-03-13 Issue:28 Volume:4 Page:
ISSN:2470-9476
Container-title:Science Robotics
language:en
Short-container-title:Sci. Robot.

Author:

Li W.¹²³^ORCID,Pan C. W.⁴⁵^ORCID,Zhang R.⁶^ORCID,Ren J. P.⁶^ORCID,Ma Y. X.⁷^ORCID,Fang J.¹²^ORCID,Yan F. L.¹²^ORCID,Geng Q. C.⁸^ORCID,Huang X. Y.¹²^ORCID,Gong H. J.³,Xu W. W.⁶,Wang G. P.⁴^ORCID,Manocha D.⁹^ORCID,Yang R. G.¹²^ORCID

Affiliation:

1. Baidu Research, Beijing, China.

2. National Engineering Laboratory of Deep Learning Technology and Application, Beijing, China.

3. Nanjing University of Aeronautics and Astronautics, Nanjing, China.

4. Beijing Engineering Technology Research Center of Virtual Simulation and Visualization, Peking University, Beijing, China.

5. Deepwise AI Lab, Beijing, China.

6. Zhejiang University, Hangzhou, China.

7. University of Hong Kong, Hong Kong, China.

8. Beihang University, Beijing, China.

9. University of Maryland, College Park, MD, USA.

Abstract

A scalable simulation system combines augmented images with synthesized traffic to enable training and testing of autonomous driving.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Mechanical Engineering

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