Python library for METROPOLIS2

This repository contains Python tools to work with METROPOLIS2 input and output data.

Requirements

• Minimum supported Python version: 3.9.

How to use

1. Clone the repository:

   git clone https://github.com/Metropolis2/metropy
   

2. Install the dependencies listed in requirements.txt. The recommended way is to create a Python virtual environment, activate it and install the dependencies on it:

   python -m venv venv/
   source venv/bin/activate # On MacOS / Linux
   venv\Scripts\Activate.ps1 # On Windows
   pip install -r requirements.txt
   

3. Change the variables inside config.toml to the desired paths and values.
4. Set the working directory of the terminal emulator to the directory where config.toml and metropy/ are located.
5. Run the tools as Python modules. For example, to import a road-network from OpenStreetMap, use

   python -m metropy.road_network.osm
   

Tools available

• OpenStreetMap network import: metropy.road_network.osm
• OpenStreetMap network import (for walking trips): metropy.road_network.osm_walk
• Road-network post-processing: metropy.road_network.postprocess
• Identify a restricted area on the road network: metropy.road_network.restriction_area
• METROPOLIS2 road-network writer: metropy.road_network.write_metropolis_edges
• Request routing queries from TomTom API: metropy.calibration.tomtom_requests
• Map matching of routing results to the road network: metropy.calibration.map_matching
• Post-processing for the map matching results: metropy.calibration.post_map_matching
• Free-flow travel time calibration: metropy.calibration.free_flow_calibration.py
• Edge capacities calibration: metropy.calibration.capacities_calibration.py
• Departure-time distribution calibration: metropy.calibration.departure_time_calibration.py
• France synthetic population import: metropy.synthetic_population.france
• Generating vehicles for the population from French vehicle fleet data: metropy.synthetic_population.french_vehicle_fleet
• Identifying the origin / destination zone of trips: metropy.synthetic_population.french_zones
• Predict mode choice for the synthetic population: metropy.demand.predict_modes
• Predict activities' desired start time and duration: metropy.demand.desired_times
• Draw mode-specific stochastic shocks: metropy.demand.draw_mode_epsilons
• Plotting a household from the synthetic population: metropy.synthetic_population.plot_household
• Generating a population from an origin-destination matrix: metropy.od_matrix.disaggregate
• Splitting road network in main and secondary parts: metropy.routing.road_split
• Walking distance computation: metropy.routing.walking_distance
• Public-transit routing with OpenTripPlanner: metropy.routing.opentripplanner
• Run a simulation with only the road trips: metropy.run.road_only
• Run a simulation to retrieve the travel time of the TomTom requests from the results of a simulation: metropy.run.tomtom_routes
• Compute stop-to-stop public-transit flows: metropy.public_transit.analyze_flows
• Compute public-transit chevelus: metropy.public_transit.chevelus
• Compute pollutant emissions and fuel consumption with the EMISENS model: metropy.emissions.emisens
• Compute fuel consumption from free-flow routes: metropy.emissions.fuel_consumption
• Compute pollutant concentration with a Gaussian Plume model: metropy.emissions.dispersion
• Compute population exposure to pollution: metropy.emissions.exposure
• Compare METROPOLIS2 free-flow travel times with travel-survey data: metropy.travel_survey.free_flow_travel_time
• Estimate desired activity start time and duration from travel-survey data: metropy.travel_survey.desired_times
• Retrieve the departure-time distribution of trips in travel-survey data: metropy.travel_survey.departure_time_distribution
• Compute congestion results for each edge: metropy.road_results.edge_values

Acknowledgments

Many thanks to Kokouvi Joseph Djafon for his work on the calibration tools.

Many thanks to Romuald Le Frioux for his work on METRO-TRACE (emissions, dispersion and exposure).