Python package to create physics-based pedestrian models from crowd measurements
Project description
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. Preprint, https://arxiv.org/abs/2407.20794
Documentation
- Documentation: https://c-pouw.github.io/physics-based-pedestrian-modeling.
Usage Notebooks
- Quick-start notebook demonstrating the generalized pedestrian model.
This notebook can be used to create models for all the environments discussed in the paper that rely ona public data set without the need to install anything locally.
Installation
You can install the package from PyPI
pip install physics-based-pedestrian-modeling
Using the CLI
Run the main processing script for one of the available environments by overwriting the params
variable with the configuration file name of the environment. The configuration file names associated to every environment are specified below. These parameter configurations are handled by Hydra, see their documentation for more details .
physped_cli params=CONFIGURATION_FILE_NAME
Similarly, we can overwrite all the other parameter directly from the command line. For instance, if we want to process the narrow corridor trajectories with a different noice intensity, e.g. sigma=0.7, we can simply run
physped_cli params=narrow_corridor params.model.sigma=0.7
Creating the model for multiple parameter values can be achieved by adding -m
and listing the variables. For example
physped_cli -m params=narrow_corridor params.model.sigma=0.5,0.7,0.9
Available environments
Every environment discussed in the paper that relies a on public data set can be modeled using the cli by overwriting the 'params' variable with one of the following configuration file names:
Narrow corridor
Trajectories of walking paths in a narrow corridor.
Configuration file name: narrow_corridor
Intersecting walking paths
Trajectories of intersecting walking paths.
Configuration file name: intersecting_paths
Train station platform
Trajectories of walking paths in the Amsterdam Zuid train station on platform 1 and 2.
Configuration file name: asdz_pf12
License
- Free software: 3-clause BSD license
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file physics_based_pedestrian_modeling-0.3.2.tar.gz
.
File metadata
- Download URL: physics_based_pedestrian_modeling-0.3.2.tar.gz
- Upload date:
- Size: 52.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.2 CPython/3.8.10 Linux/5.15.0-117-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 23df2ab8af8f18e18b111fd178dc368a1297dc9a4987cc211d25b19d25283af9 |
|
MD5 | 3e641a8daa6d2c3b2be71771ecea0aff |
|
BLAKE2b-256 | 98a712a1e05f0d7b3c53965b29b7f35f27f42396678b8581479ab992d17ce25e |
File details
Details for the file physics_based_pedestrian_modeling-0.3.2-py3-none-any.whl
.
File metadata
- Download URL: physics_based_pedestrian_modeling-0.3.2-py3-none-any.whl
- Upload date:
- Size: 75.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.2 CPython/3.8.10 Linux/5.15.0-117-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0253448c4a257f080b5dbe4f94f0b4d7a08b065e2687b5729d57fc2c8a99aa1a |
|
MD5 | 3df012b807fe4361a557e2a4294c9667 |
|
BLAKE2b-256 | d291d0562412f02033de61713c2c1135d0ded2b0c3de17c36129e326b2b61f25 |