ChauffeurNet:

ChauffeurNet : Learning to Drive by Imitating the Best and Synthesizing the Worst. Reproduction the result according to this paper[https://arxiv.org/pdf/1812.03079.pdf]. I just implement it on the basis of my comprehension，because the paper didn't introduce the neural network in every detail. The model is implemented by Keras with Tensorflow backend.

Roadmap:

1.Model and train and prediction with mocked data.[done] 2.Data pipeline for real data. 3.Train it in real world data. 4.Other approachs in paper. 5.Test it in simulation. I want the model can be used in different simulation environment. Welcome other contributors to integrate different open source or private simulators. I will combine my company's simulator and some simple simulators first. 6.Test it in Real world on china's urban road.

Model options:

1.use conv layers like U-Net(Conv+Upsampling/Deconv) [done] 2.Conv + Full Connect like artari-net 3.Fully Conv 4.Fully Conv + GRU

Links:

https://github.com/Iftimie/ChauffeurNet

Install:

anaconda3, python 3.6, keras 2.2.4, tensorflow 1.12.0

Run:

python chaffeur_net/chaffeur_net_main.py ###rnn_cell is reserverd. we should not use it now!