Exploring imitation learning for autonomous driving with feedback synthesizer and differentiable rasterization

J Zhou, R Wang, X Liu, Y Jiang, S Jiang… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
We present a learning-based planner that aims to robustly drive a vehicle by mimicking
human drivers' driving behavior. We leverage a mid-to-mid approach that allows us to …
被引用次数：33 相关文章

Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization

J Zhou, R Wang, X Liu, Y Jiang, S Jiang, J Tao… - arXiv preprint arXiv …, 2021 - arxiv.org
We present a learning-based planner that aims to robustly drive a vehicle by mimicking
human drivers' driving behavior. We leverage a mid-to-mid approach that allows us to …

Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization

J Zhou, R Wang, X Liu, Y Jiang, S Jiang, J Tao… - 2021 IEEE/RSJ …, 2021 - dl.acm.org
We present a learning-based planner that aims to robustly drive a vehicle by mimicking
human drivers' driving behavior. We leverage a mid-to-mid approach that allows us to …
[PDF] github.io

[PDF][PDF] Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization

J Zhou, R Wang, X Liu, Y Jiang, S Jiang, J Tao, J Miao… - songshiyu01.github.io
We present a learning-based planner that aims to robustly drive a vehicle by mimicking
human drivers' driving behavior. We leverage a mid-to-mid approach that allows us to …

Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization

J Zhou, R Wang, X Liu, Y Jiang, S Jiang, J Tao… - arXiv e …, 2021 - ui.adsabs.harvard.edu
We present a learning-based planner that aims to robustly drive a vehicle by mimicking
human drivers' driving behavior. We leverage a mid-to-mid approach that allows us to …