(Re)2H2O: Autonomous Driving Scenario Generation via Reversely Regularized Hybrid Offline-and-Online Reinforcement Learning
Author:
Affiliation:
1. Tsinghua University,Department of Automation,Beijing,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10186382/10186383/10186559.pdf?arnumber=10186559
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3. An unsupervised random forest clustering technique for automatic traffic scenario categorization;kruber;2018 21st International Conference on Intelligent Transportation Systems (ITSC),2018
4. Full velocity difference model for a car-following theory
5. Initial Scene Configurations for Highway Traffic Propagation
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