Name
Title | ||
|---|---|---|
Multi-Objective End-to-End Self-Driving Based on Pareto-Optimal Actor-Critic Approach |
Abstract | ||
|---|---|---|
The end-to-end control method is one of the ways to realize autonomous driving. Existing end-to-end self-driving approaches commonly just consider one objective, for instance, safety or fuel efficiency. To optimize multiple objectives simultaneously, Pareto-optimal driving policies need to be obtained to satisfy different driving requirements. However, it is difficult to obtain the Pareto-optimal ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ITSC48978.2021.9564464 | 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) |
Keywords | DocType | ISBN |
Simulation,Conferences,Decision making,Reinforcement learning,Safety,Fuels,Task analysis | Conference | 978-1-7281-9142-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tinghan Wang | 1 | 1 | 0.68 |
| Yugong Luo | 2 | 30 | 6.08 |
| Jinxin Liu | 3 | 2 | 1.04 |
| Keqiang Li | 4 | 583 | 52.39 |