Park & Drive Potential

Installation

Install uv and then set up the python project like this:

uv sync # set up project + dependencies
uv run pytest # run unit tests to see if installation was successful

Usage

1. Prepare a GeoPackage containing layers for

   • the MATSim network (line geometry)
   • park & drive stations to be checked (point geometry)
   • cities & large towns (point geometry) for visualization purposes
   • barriers (any geometry) for limiting buffers around the park & drive stations

2. Extract all trips from a calibrated MATSim population file to a CSV file

   • Must include info about subtours
   • Must include routes (as a list of link ids) for all car trips
   • Header: personId,age,sex,isEmployed,fullTimeWork,highEducation,highIncome,subtourNr,subtourLen,tripNr,mode,departureSecondsOfDay,arrivalSecondsOfDay,nextActivityStartSecondsOfDay,activityChain,links,inEducation,retired (subtourNr and tripNr must be 1-based)
   • E.g. adjust this exemplary script

3. Run the analysis:

   uv run main.py

Methodology & Results

The inner workings and outputs/results of the tool will be described in detail in Quantifying Park & Drive Potential: A Quick Location Planning Tool, an upcoming paper submitted at Transport Research Arena (TRA) 2026.

Acknowledgements

This research was funded by the Austrian Research Promotion Agency (FFG) under grant 4906625, project INTRO (Integrierte Mobilitätsknoten).