Risk-Aware High-level Decisions for Automated Driving at Occluded Intersections with Reinforcement Learning-Reference-Cited by-同舟云学术

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Risk-Aware High-level Decisions for Automated Driving at Occluded Intersections with Reinforcement Learning

Published:2020-10-19 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE Intelligent Vehicles Symposium (IV)
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Author:

Kamran Danial,Lopez Carlos Fernandez,Lauer Martin,Stiller Christoph

Funder

UNICA

Federal Ministry of Education and Research of Germany (BMBF)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9304518/9304528/09304606.pdf?arnumber=9304606

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1. Physics-Informed Particle-Based Reinforcement Learning for Autonomy in Signalized Intersections;International Journal of Intelligent Transportation Systems Research;2024-06-14

2. AF-DQN: A Large-Scale Decision-Making Method at Unsignalized Intersections with Safe Action Filter and Efficient Exploratory Training Strategy;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. Integrating occlusion awareness in urban motion prediction for enhanced autonomous vehicle navigation;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

4. Decision Making for Autonomous Driving Stack: Shortening the Gap from Simulation to Real-World Implementations;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

5. Trustworthy autonomous driving via defense-aware robust reinforcement learning against worst-case observational perturbations;Transportation Research Part C: Emerging Technologies;2024-06

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