022-model-based-imitation-learning-for-urban-driving

https://github.com/szu-advtech-2023/022-model-based-imitation-learning-for-urban-driving

Repository

https://github.com/SZU-AdvTech-2023/022-Model-Based-Imitation-Learning-for-Urban-Driving/blob/main/

##  Setup
- Create the [conda](https://docs.conda.io/en/latest/miniconda.html) environment by running `conda env create`.
- Download [CARLA 0.9.11](https://github.com/carla-simulator/carla/releases/tag/0.9.11).
- Install the carla package by running `conda activate mile` followed by `easy_install ${CARLA_ROOT}/PythonAPI/carla/dist/carla-0.9.11-py3.7-linux-x86_64.egg`.
- We also need to add `${CARLA_ROOT}/PythonAPI/carla/` to the `PYTHONPATH`. This can be done by creating a file in the conda environment `~/miniconda3/envs/mile/etc/conda/activate.d/env_vars.sh` containing:
```
#!/bin/bash

export CARLA_ROOT=""
export PYTHONPATH="${CARLA_ROOT}/PythonAPI/carla/"
```

##  Evaluation

- Download the model [pre-trained weights](https://github.com/wayveai/mile/releases/download/v1.0/mile.ckpt).
- Run `bash run/evaluate.sh ${CARLA_PATH} ${CHECKPOINT_PATH} ${PORT}`, with 
 `${CARLA_PATH}` the path to the CARLA .sh executable,
`${CHECKPOINT_PATH}` the path to the 
pre-trained weights, and `${PORT}` the port to run CARLA (usually `2000`).

##  Data Collection
- Run `bash run/data_collect.sh ${CARLA_PATH} ${DATASET_ROOT} ${PORT} ${TEST_SUITE}`, with 
 `${CARLA_PATH}` the path to the CARLA .sh executable,
`${DATASET_ROOT}` the path where to save data, `${PORT}` the port to run CARLA (usually `2000`), and `${TEST_SUITE}` the path to the config specifying from which town to collect data (e.g. `config/test_suites/lb_data.yaml`).

##  Training
To train the model from scratch:
- Organise the dataset folder as described in [DATASET.md](DATASET.md).
- Activate the environment with `conda activate mile`.
- Run `python train.py --config mile/configs/mile.yml DATASET.DATAROOT ${DATAROOT}`, with `${DATAROOT}`
the path to the dataset.

##  Training RL
python train_rl.py

##  Credits
Thanks to the authors of [End-to-End Urban Driving by Imitating a Reinforcement Learning Coach](https://github.com/zhejz/carla-roach)
for providing a gym wrapper around CARLA making it easy to use, as well as an RL expert to collect data.

Owner

Citation (citation.txt)

@article{REPO022,
    author = "Hu, Anthony and Corrado, Gianluca and Griffiths, Nicolas and Murez, Zachary and Gurau, Corina and Yeo, Hudson and Kendall, Alex and Cipolla, Roberto and Shotton, Jamie",
    journal = "Advances in Neural Information Processing Systems",
    pages = "20703--20716",
    title = "{Model-Based Imitation Learning for Urban Driving}",
    volume = "35",
    year = "2022"
}

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