Deep reinforcement learning-based energy-efficient decision-making for autonomous electric vehicle in dynamic traffic environments
Autonomous driving techniques are promising for improving the energy efficiency of electrified vehicles (EVs) by adjusting driving decisions and optimizing energy requirements. Conventional energy-efficient autonomous driving methods resort to longitudinal velocity planning and fixed-route scenes, w...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/178365 |