This small repo is made for demand data generation and transformation, currently exclusively for the input format used in the Amodsim project. You can generate random demand, or transform a public taxi trips dataset. To install the required packages for this repo, run pip install -r requirements.txt.

Instructions:

As a prerequisite for the random demand generation, you need a map in the geojson format. You can obtain such a map using the Roadmaptools library.

Random Demand

1. Open the script generate_random_demand.py and configure the settings on the top
   • map_path: path to the geojson file
   • demand_file_path path to the output file
   • start_time and end_time in minutes
   • the size of the demand
2. Run the script.

Transforming an Existing Dataset

1. Find data you want prior to 2016. You can use for example this dataset this New York dataset from 2014 which contains data of trips in New York in 2014. You can also search your fo your own dataset, just be aware of required data format. Searching for combination of "New York taxi csv data 20xx" should give you a relevant output.
2. Unzip the downloaded file.
3. Edit config.py.
   • Change DATA_DIR to the path where the downloaded data are stored
   • Change MAP_ENVELOPE to values you used to generate the map. This ensures that created demand fits into the map.
   • Don't change DATA_TO_EXTRACT unless you know why you want to change it. It corresponds to Amodsim data format.
4. run the script: python3 trips_process.py

Following these steps, a trips.txt file with the demand in SiMoD format should appear in the DATA_DIR directory.

Random Parcel Demand Generation

1. Set your working directory in OUTPUT_DIR and change MAP_ENVELOPE to the one you are currently using for your simulation.
2. You can change the values in AVERAGE_PACKAGES to achieve different parcel generation across the categories
3. Run the script: python3 generate_parcels.py

Following these steps, a parcel.txt file with the demand in SiMoD format should appear in the DATA_DIR directory.