Skip to main content

A simple and scalable simulator for platoon formation.

Project description

PlaFoSim - A simple and scalable simulator for platoon formation

Code Version PyPI Version PyPI - Python Version License DOI

PlaFoSim's logo "Platoon Formation Simulator", or "PlaFoSim" for short, is an open source simulator for platoon formation, aiming for simplicity, flexibility, and scalability. PlaFoSim aims to facilitate and accelerate the research of platoon maneuvers and formation for individually driven vehicles. While the main focus of the simulator is on the assignment process, simulation of advertisements and maneuvers is implemented in a more abstract way.

PlaFoSim has been published at IEEE VNC 2021:

Julian Heinovski, Dominik S. Buse and Falko Dressler, "Scalable Simulation of Platoon Formation Maneuvers with PlaFoSim," Proceedings of 13th IEEE Vehicular Networking Conference (VNC 2021), Poster Session, Virtual Conference, November 2021, pp. 137–138.

NOTE: This project is under active development.


Installation

  • Install Python (>=3.7,<=3.9)
  • Install PlaFoSim from pypi: pip install plafosim

NOTE: The project is developed and tested only on Linux.

Running a Simulation

NOTE: Since PlaFoSim is a command-line interface (CLI) application, running PlaFoSim requires using a shell.

Quickstart

Run PlaFoSim with:

plafosim

You can use PlaFoSim's help to get a list of available parameters:

plafosim -h, --help

Or, run a simulation with the default configuration (-d):

plafosim -d

Live GUI

You can visualize the simulation via a simple live GUI based on sumo-gui, using the argument gui:

plafosim --gui

A screenshot of PlaFoSim's live GUI showing 2 platoons and various individual vehicles. Copyright © 2021 IEEE.

More options for the live GUI can be found within the GUI properties section of the help.

NOTE: This requires installation of SUMO (>=1.6.0) and declaration of the SUMO_HOME variable (see documentation).

Advanced Simulation Control

You can use a variety of different parameters to customize the scenario and the simulation itself. E.g., use the parameter vehicles to configure the number of vehicles in the simulation:

plafosim --vehicles 1000

The available parameters are grouped into different categories:

- road network properties
- vehicle properties
- trip properties
- communication properties
- platoon properties
- formation properties
- infrastructure properties
- simulation properties
- GUI properties
- result recording properties

You can find a list of available parameters for each category in the help:

plafosim -h, --help

Examples

# Configure a 100km freeway with ramps at every 10km
plafosim --road-length 100 --ramp-interval 10

# Configure random (normally distributed) desired driving speed of 130km/h
plafosim --random-desired-speed true --desired-speed 36

# Configure random trips for 500 vehicles
plafosim --vehicles 500 --random-depart-position true --random-arrival-position true --depart-desired true

# Pre fill the freeway with 1000 vehicles
plafosim --vehicles 1000 --pre-fill true

# Configure 50% of the vehicles with Advanced Cruise Control (ACC) and a headway time of 1.5s
plafosim --penetration 0.5 --acc-headway-time 1.5

# Enable a simple, distributed platoon formation algorithm [1] in order to form platoons every 30s
plafosim --formation-algorithm SpeedPosition --formation-strategy distributed --execution-interval 30

Faster Simulation

You can speed up the simulation performance by enabling Python's optimization PYTHONOPTIMIZE, e.g., in order to disable assertions:

PYTHONOPTIMIZE=1 plafosim

See the Python documention for more details.

Re-Playing a Simulation

The simulation can write a trace file including the mobility details of every simulated vehicle (default results_vehicle_traces.csv). You can replay the simulation in the GUI (see above) based on the trace file by using the corresponding binary:

plafosim-replay results_vehicle_traces.csv

To see all options of this script, run:

plafosim-replay -h, --help

NOTE: This requires installation of SUMO (>=1.6.0) and declaration of the SUMO_HOME variable.

Recording of Screenshots and Video from a Simulation

PlaFoSim offers functionality to automatically record a screenshot of the GUI in every simulation step with

plafosim --gui --screenshot-file screenshot

These screenshots can be used to create a video by using an integrated script based on ffmpeg:

plafosim-img2video 'screenshot_*.png' video.mp4

NOTE: This requires installation of ffmpeg.

Documentation

Documentation is available via this README and via the official documentation.

Extending PlaFoSim

You can extend and customize PlaFoSim flexibly by modifying its source code. For this, you first need ot install it from source.

Installing from Source

  • Install poetry: pip install poetry
  • Clone this repository: git clone https://github.com/heinovski/plafosim.git
  • Navigate to newly created directory of the cloned repository in the command-line
  • Install PlaFoSim from source in editable mode: poetry install
  • Run PlaFoSim in the virtual environment: poetry run plafosim You can also activate the virtual enviroment first with poetry shell and run the commands as usual (see above).

Adding a new Formation Algorithm

In order to add a new formation algorithm, you need to follow these steps:

  • Create a new sub-class of FormationAlgorithm (see formation_algorithm.py) within the sub-directory algorithms. You can use the Dummy algorithm (see algorithms/dummy.py) as an example.
  • Add specific arguments for your algorithm to the argument parser group within the new sub-class if necessary.

You should now be able to use your new algorithm with

plafosim --formation-algorithm dummy_algorithm_name

Contributing to the Project

In order to contribute, please follow these steps:

  • Install PlaFoSim from source (see Extending PlaFoSim)
  • Make desired changes and adjust the documentation if required
  • Run the tests located in tests as well as the validation scripts located in scripts (see .drone.yml for details)
  • Submit a Pull Request (PR)

Documenting

When making changes to the code, make sure to add or adjust corresponding documentation in form of python docstrings. Those should use the Numpy docstring format for Sphinx and follow the style guide by numpydoc to ensure consistency and compatibility. See also the style guide by pandas. You can build the documentation using Sphinx make -C docs.

Testing

When adding methods and functions, make sure to add corresponding unit tests for py.test. The tests are located under tests and can be executed with ./scripts/run-pytest.sh. This will also generate a test coverage report.

Validation

To validate the behavior of PlaFoSim, it is compared to SUMO 1.6.0 by means of simulation results (e.g., vehicle traces). The corresponding scripts are located under scripts and executed withn CI/CD pipelines. You can have a look at .drone.yml for details regarding the execution.

Profiling

You can profile the runtime of PlaFoSim's code by using cProfile:

poetry run python -m cProfile -o profile.out -m plafosim.cli.plafosim

You can visualize the results of the profiling run by using SnakeViz:

snakeviz profile.out

Contributors & Citing

PlaFoSim was originally designed and built by Julian Heinovski with the help of Dominik S. Buse. It is currently maintained by Julian Heinovski. The list of all authors can be found here.

If you are working with PlaFoSim, we would appreciate a citation of our paper:

Julian Heinovski, Dominik S. Buse and Falko Dressler, "Scalable Simulation of Platoon Formation Maneuvers with PlaFoSim," Proceedings of 13th IEEE Vehicular Networking Conference (VNC 2021), Poster Session, Virtual Conference, November 2021, pp. 137–138.

@inproceedings{heinovski2021scalable,
    author = {Heinovski, Julian and Buse, Dominik S. and Dressler, Falko},
    doi = {10.1109/VNC52810.2021.9644678},
    title = {{Scalable Simulation of Platoon Formation Maneuvers with PlaFoSim}},
    pages = {137--138},
    publisher = {IEEE},
    issn = {2157-9865},
    isbn = {978-1-66544-450-7},
    address = {Virtual Conference},
    booktitle = {13th IEEE Vehicular Networking Conference (VNC 2021), Poster Session},
    month = {11},
    year = {2021},
}

License

PlaFoSim is licensed under the terms of the GNU General Public License 3.0 or later.

# Copyright (c) 2020-2024 Julian Heinovski <heinovski@ccs-labs.org>
#
# SPDX-License-Identifier: GPL-3.0-or-later
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

plafosim-0.17.3.tar.gz (95.4 kB view details)

Uploaded Source

Built Distribution

plafosim-0.17.3-1-py3-none-any.whl (122.5 kB view details)

Uploaded Python 3

File details

Details for the file plafosim-0.17.3.tar.gz.

File metadata

  • Download URL: plafosim-0.17.3.tar.gz
  • Upload date:
  • Size: 95.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.0 CPython/3.8.10 Linux/5.4.0-169-generic

File hashes

Hashes for plafosim-0.17.3.tar.gz
Algorithm Hash digest
SHA256 8cf9af80ff1e630084c8aaf5b86a48271bb0741b2840eda6fd8f00d85bc15e3b
MD5 89d02d3cd52b8bbcd2553ca0b7377805
BLAKE2b-256 e7ffe4644a569288d83e1b3c8d47cc55101b9b053efe177eb440130f998f5589

See more details on using hashes here.

File details

Details for the file plafosim-0.17.3-1-py3-none-any.whl.

File metadata

  • Download URL: plafosim-0.17.3-1-py3-none-any.whl
  • Upload date:
  • Size: 122.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.0 CPython/3.8.10 Linux/5.4.0-169-generic

File hashes

Hashes for plafosim-0.17.3-1-py3-none-any.whl
Algorithm Hash digest
SHA256 3f4a56826cc03549463fd4ff06e8b11efe75842a66b8c607185ef694b3830edc
MD5 3ebad7af92ada2494eac6a2063070dc5
BLAKE2b-256 cd6594ed010918b7fe6bfef9adf81fd9edb9f79af9f63c827700a4ac1974c83f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page