Name
Title | ||
|---|---|---|
Adaptive Decision-Making for Automated Vehicles Under Roundabout Scenarios Using Optimization Embedded Reinforcement Learning |
Abstract | ||
|---|---|---|
The roundabout is a typical changeable, interactive scenario in which automated vehicles should make adaptive and safe decisions. In this article, an optimization embedded reinforcement learning (OERL) is proposed to achieve adaptive decision-making under the roundabout. The promotion is the modified actor of the Actor–Critic framework, which embeds the model-based optimization method in reinforce... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TNNLS.2020.3042981 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | DocType | Volume |
Decision making,Erbium,Adaptation models,Acceleration,Automotive engineering,Space vehicles,Reinforcement learning | Journal | 32 |
Issue | ISSN | Citations |
12 | 2162-237X | 1 |
PageRank | References | Authors |
0.35 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxiang Zhang | 1 | 11 | 15.58 |
| Bingzhao Gao | 2 | 48 | 11.76 |
| Lulu Guo | 3 | 25 | 7.45 |
| Hongyan Guo | 4 | 44 | 4.59 |
| Hong Chen | 5 | 280 | 56.04 |