Towards Defensive Autonomous Driving: Collecting and Probing Driving Demonstrations of Mixed Qualities-Reference-Cited by-同舟云学术

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Towards Defensive Autonomous Driving: Collecting and Probing Driving Demonstrations of Mixed Qualities

Published:2022-10-23 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Oh Jeongwoo¹,Lee Gunmin¹,Park Jeongeun²,Oh Wooseok¹,Heo Jaeseok¹,Chung Hojun¹,Kim Do Hyung³,Park Byungkyu³,Lee Chang-Gun³,Choi Sungjoon²,Oh Songhwai¹

Affiliation:

1. ASRI, Seoul National University,Department of Electrical and Computer Engineering,Seoul,Korea,08826

2. Korea University,Department of Artificial Intelligence,Seoul,Korea,02841

3. Seoul National University,Department of Computer Science and Engineering,Seoul,Korea,08826

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9981026/9981028/09981110.pdf?arnumber=9981110

Reference37 articles.

1. MixGAIL: Autonomous Driving Using Demonstrations with Mixed Qualities

2. Probabilistic 3D multi-object tracking for autonomous driving;chiu;CoRR,2020

3. iCurb: Imitation Learning-Based Detection of Road Curbs Using Aerial Images for Autonomous Driving

4. Mixture density networks;bishop;University of Birmingham,0

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