traffic-flow-models 0.1.2

Traffic flow models and simulator

Macroscopic Traffic Flow Models

A Python library for simulating and analyzing macroscopic traffic flow on highway networks. This package implements two widely-used traffic flow models—Cell Transmission Model (CTM) and METANET—along with network infrastructure components, ramp metering controllers (ALINEA), and visualization tools.

Features

• Traffic Flow Models: CTM (first-order) and METANET (second-order) macroscopic models
• Network Components: Flexible highway network structure with cells, onramps, and offramps
• Control Strategies: ALINEA ramp metering controller
• Visualization: Network topology plotting and simulation result visualization

Installation

Requirements: Python 3.13 or later

# Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install package
pip install -e .

# For development (includes pytest)
pip install -e ".[dev]"

On macOS, you may need to install Python 3.13 explicitly:

brew install python@3.13
python3.13 -m venv venv
source venv/bin/activate
pip install -e ".[dev]"

Project Structure

traffic_flow_models/
├── src/
│   ├── traffic_flow_models/     # Main package
│   │   ├── model/               # Traffic flow models (CTM, METANET)
│   │   ├── network/             # Network components
│   │   └── controller/          # Control strategies (ALINEA)
│   └── demo/                    # Demo scripts
└── tests/                       # Unit tests

Quick Start

Run a pre-configured demo simulation:

python -m src.demo.ctm_simulation
python -m src.demo.metanet_simulation

Testing

pytest

Development

Contributions are welcome! Please ensure that:

1. All tests pass (pytest)
2. Code is formatted with Black
3. New features include appropriate tests

Release

To release a new version of the macroscopic traffic flow package, please make sure that all tests and builds are passing and follow these steps:

0. Prerequisites

Ensure that the master branch is up to date with all changes that should be released. Also, make sure you have the necessary permissions to push tags to the repository.

1. Update version in pyproject.toml

Update the version of the package in the pyproject file according to the next release version according to the conventional commit guidelines. To make sure you update the version correctly, you can run the following command:

git cliff bump

⚠️ CAUTION: Do not commit the changelog changes yet, as these will be handled automatically by the release workflow. Only commit the version change in pyproject.toml. If the version in the pyproject configuration and the changelog are not in sync, the release workflow will fail.

2. Commit the change

git commit -m "chore(release): bump pip package version for release"

3. Create and push tag (triggers workflow)

git tag -a v1.0.0 -m "chore(release): version 1.0.0"
git push origin v1.0.0

4. GitHub Actions automatically:

├─ Validates all versions match

├─ Generates changelog

├─ Builds distribution packages

├─ Publishes to PyPI

└─ Creates GitHub release

Usage Examples

Creating a Network

from traffic_flow_models import Network, Onramp

network = Network()
network.add_cell(length=0.5, lanes=3, lane_capacity=2000,
                 free_flow_speed=100, jam_density=180)
network.add_cell(length=0.5, lanes=3, lane_capacity=2000,
                 free_flow_speed=100, jam_density=180,
                 onramp=Onramp(lanes=1, lane_capacity=2000,
                              free_flow_speed=100, jam_density=180))

Running Simulations

from traffic_flow_models import CTM, METANET
import numpy as np

# CTM simulation
ctm = CTM()
density, flow, speed, *_ = network.simulate(
    duration=1.0, dt=10.0/3600, model=ctm,
    mainline_demand=lambda t: 4000,
    onramp_demand=lambda t, n: np.array([0, 2000] + [0]*(n-2)),
    plot_results=True
)

# METANET simulation
metanet = METANET(tau=22/3600, nu=15, kappa=10, delta=1.4, phi=10, alpha=2)
density, flow, speed, *_ = network.simulate(
    duration=1.0, dt=10.0/3600, model=metanet,
    mainline_demand=lambda t: 4000,
    onramp_demand=lambda t, n: np.array([0, 2000] + [0]*(n-2)),
    plot_results=True
)

ALINEA Ramp Metering

from traffic_flow_models import AlineaController

onramp = Onramp(lanes=1, lane_capacity=2000, free_flow_speed=100,
                jam_density=180,
                controller=AlineaController(gain=5.0, setpoint=20.0,
                                           measurement_cell=3))

License

This project is licensed under the GNU Affero General Public License version 3 (AGPL-3.0). See the LICENSE file in the repository for the full license text.

References

• CTM: Daganzo, C. F. (1994). The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory. Transportation Research Part B, 28(4), 269-287.
• METANET: Messmer, A., & Papageorgiou, M. (1990). METANET: A macroscopic simulation program for motorway networks. Traffic Engineering & Control.
• ALINEA: Papageorgiou, M., Hadj-Salem, H., & Blosseville, J. M. (1991). ALINEA: A local feedback control law for on-ramp metering. Transportation Research Record, 1320, 58-64.