PPR-1812.03079
Paper
ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst
| id | |
|---|---|
| updated | |
| type | paper |
| title | ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst |
| authors | Mayank Bansal, A. Krizhevsky, A. Ogale |
| venue | RSS 2019 |
| arxiv | 1812.03079 |
| doi | 10.15607/RSS.2019.XV.031 |
| tier | 0 |
| lifecycle | EXTRACTED |
| epistemic | n/a |
| ingested | 2026-09-03 |
| version | arXiv:1812.03079 |
| source-hash | sha256:0000000000000000000000000000000000000000000000000000000000000000 |
| admitted-under | A2-direct-edge |
| admission-note | G2DP 引用本工作作模仿学习训练的参照（Bansal et al., RSS 2019）：『学最佳示范、合成最坏失败』的数据配方。 |
| citation-count-s2 | 886 |
以模仿学习训练驾驶策略（Bansal, Krizhevsky & Ogale, RSS 2019）：只模仿表现最好的人类示范，并合成最差失败情形扩充训练数据。
与 G2DP 的关系（PPR-2606.26017）：G2DP 引用本工作作模仿学习训练的参照（Bansal et al., RSS 2019）：『学最佳示范、合成最坏失败』的数据配方。
关联（1）
- PPR-2606.26017 G2DP: Diffusion Planning with Spatio-Temporal Grid Guidance