physics-based-pedestrian-modeling 0.1.4

Python package to create physics-based pedestrian models from crowd measurements

Data-driven physics-based modeling of pedestrian dynamics

Project Overview

Python package to create physics-based pedestrian models from pedestrian trajectory measurements. This package is an implementation of the data-driven generalized pedestrian model presented in:

Pouw, C. A. S., van der Vleuten, G., Corbetta, A., & Toschi, F. (2024). Data-driven physics-based modeling of pedestrian dynamics. To appear xx.

Getting started

Install the package from PyPI

pip install physics-based-pedestrian-modeling

Download the configuration files into your working directory.

Run the main script for one of the available parameter files (listed below)

python main.py params=single_paths

Features

Preprocessing of trajectories

Calculate slow dynamics

Learn potential from the preprocessed trajectories

Learn the potential

Simulate new trajectories using the learned potential

Simulate new trajectories

Parameter Files

Configuration of parameter files is handled by . Default parameter files are provided for the following cases:

• single_paths: Trajectories in a narrow corridor.
• parallel_paths: Trajectories in a wide corridor.
• curved_paths_synthetic: Trajectories along a closed elliptical path.
• intersecting_paths: Trajectories intersecting in the origin.
• station_paths: Complex trajectories in a train station.

Featured Notebooks

A couple of usage notebooks are available for the following cases:

• Narrow corridor paths
• Station paths
• User input paths

Documentation

• Documentation: https://c-pouw.github.io/physics-based-pedestrian-modeling.

License

• Free software: 3-clause BSD license