Name
Title | ||
|---|---|---|
Enhancing Transferability of Deep Reinforcement Learning-Based Variable Speed Limit\endgraf Control Using Transfer Learning |
Abstract | ||
|---|---|---|
The study aims to evaluate the performance of the transfer learning algorithm to enhance the transferability of a deep reinforcement learning-based variable speed limits (VSL) control. The Double Deep Q Network (DDQN)-based VSL control strategy is proposed for reducing total time spent (TTS) on freeways. A real merging bottleneck is developed in the simulation and considered for the VSL control as... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TITS.2020.2990598 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | DocType | Volume |
Neural networks,Traffic control,Training,Merging,Testing,Task analysis,Optimal control | Journal | 22 |
Issue | ISSN | Citations |
7 | 1524-9050 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zemian Ke | 1 | 0 | 0.34 |
| Zhibin Li | 2 | 41 | 6.93 |
| Zehong Cao | 3 | 0 | 0.34 |
| Pan Liu | 4 | 36 | 6.75 |