/frenet-trajectory-planning-framework

Primary LanguagePython

frenet-trajectory-planning-in-CARLA

This project introduces a framework for long-term short-term decision-making and planning for self-driving cars on the Frenet frame. We have utilized the Frenet frame for both the driving route definition and the trajectory generation. We have also provided a forward and inverse transformation from Cartesian to Frenet coordinates.

Installation

  • Simulation works as server-client. CARLA launches as server and uses 2000:2002 ports as default. Client can connect to server from port 2000, default, and interract with environment.

Client Installation

  1. git clone https://github.com/MajidMoghadam2006/frenet-trajectory-planning-framework.git
  2. cd frenet-trajectory-planning-framework/
  3. pip3 install -r requirements.txt (requires Python 3.7 or newer)

Simulation Server Installation

Use pre-compiled carla versions - (CARLA 9.9.2 Recommended)

  1. Download the pre-compiled CARLA simulator from CARLA releases page
  2. Now you can run this version using ./CarlaUE4.sh command
  3. Create a virtual Python environemnt, e.g. using conda create -n carla99, and activate the environment, i.e. conda activate carla99
  4. If easy_install is not installed already, run this: sudo apt-get install python-setuptools
  5. Navigate to PythonAPI/carla/dist
  6. Install carla as a python package into your virtual environment (get help): easy_install --user --no-deps carla-X.X.X-py3.7-linux-x86_64.egg

Now you may import carla in your python script.

Some Features

  • Simulation parameters are configured at /tools/cfgs/config.yaml

Example execution:

  • We need to start two different terminals.

Terminal-1

Terminal-2

  • cd frenet-trajectory-planning-framework/

  • python3 run.py --cfg_file=tools/cfgs/config.yaml --env=CarlaGymEnv-v1 --play_mode=1

  • Execution parameters are configured in program arguments:

---cfg_file: specifies the config file ---env: Gym environment ID

  • --play_mode: Display mode: 0:off, 1:2D, 2:3D, default=0 ---carla_host: IP of the host server (default: 127.0.0.1) ---carla_port: TCP port to listen to (default: 2000) ---tm_port: Traffic Manager TCP port to listen to (default: 8000) ---carla_res: Window resolution (default: 1280x720)

  • Carla requires a powerful GPU to produce high fps. In order to increase performance you can run following as an alternative:

  • DISPLAY= ./CarlaUE4.sh -carla-server -fps=20 -world-port=2000 -windowed -ResX=1280 -ResY=720 -carla-no-hud -quality-level=Low

Important Directories

  • Env and simulation Config File: tools/cfgs/config.yaml
  • Gym Environment: carla_gym/envs/ # Gym environment interface for CARLA, To manipulate observation, action, reward etc. (suitable for RL training)
  • Modules: tools/modules.py # Pretty much wraps everything

To cite this repository in publications:

  title={An Autonomous Driving Framework for Long-term Decision-making and Short-term Trajectory Planning on Frenet Space},
  author={Moghadam, Majid and Elkaim, Gabriel Hugh},
  journal={arXiv preprint arXiv:2011.13099},
  year={2020}
}