utdf2gmns 0.3.0

A tool to convert utdf file to GMNS format.

utdf2gmns

Introduction

A tool to convert utdf file to GMNS format: synchro utdf format to gmns signal timing format at movement layer

Required Data Input Files:

• UTDF.csv
• node.csv (GMNS format)
• movement.csv (GMNS format)
• Future plan: remove node.csv and movement.csv, directly convert utdf.csv file to GMNS format.

Produced outputs

If input folder have UTDF.csv only, outputs are:

• A dictionary store utdf data with keys: Networks, Node, Links, Timeplans, Lanes, and utdf_intersection
• A file named utdf2gmns.pickle to store dictionary object.

If input folder have extra node.csv and movement.csv, outputs are:

• Two files named: movement_utdf.csv and utdf_intersection.csv

Sample results: datasets

Package dependencies:

• geocoder==1.38.1
• pandas==1.4.4

Data Conversion Steps:

Step 1: Read UTDF.csv file and perform geocoding, then produce utdf_geo, utdf_lane, and utdf_phase_timeplans.

Step 2: Match four files (utdf_geo, node, utdf_lane, utdf_pahse_timeplans, movement) to produce movement_utdf

Installation

pip install utdf2gmns

Simple Example

import utdf2gmns as ug
import pandas as pd


if__name__=="__main__":

    city =" Bullhead City, AZ"

    # option = 1, generate movement_utdf.csv directly
    # option = 2, generate movement_utdf.csv step by step (more flexible)
    option = 1

    if option == 1:
        # NOTE: Option 1, generate movement_utdf.csv directly

	# the folder contain UTDF.csv, node.csv and movement.csv
        path =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4"

        res = ug.generate_movement_utdf(path, city,isSave2csv=True)

    if option == 2:
        # NOTE: Option 2, generate movement_utdf.csv step by step (more flexible)
        path_utdf =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4\UTDF.csv"
        path_node =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4\node.csv"
        path_movement =r"C:\Users\roche\Desktop\coding\data_bullhead_seg4\movement.csv"

        # Step 1: read UTDF.csv
        utdf_dict_data = ug.generate_utdf_dataframes(path_utdf, city)

        # Step 1.1: get intersection data from UTDF.csv
        df_intersection = utdf_dict_data["utdf_intersection"]

        # Step 1.2: geocoding intersection data
        df_intersection_geo = ug.generate_coordinates_from_intersection(df_intersection)

        # Step 2: read node.csv and movement.csv
        df_node = pd.read_csv(path_node)
        df_movement = pd.read_csv(path_movement)

        # Step 3: match intersection_geo and node
        df_intersection_node = ug.match_intersection_node(df_intersection_geo, df_node)

        # Step 4: match movement and intersection_node
        df_movement_intersection = ug.match_movement_and_intersection_node(df_movement, df_intersection_node)

        # Step 5: match movement and utdf_lane
        df_movement_utdf_lane = ug.match_movement_utdf_lane(df_movement_intersection, utdf_dict_data)

        # Step 6: match movement and utdf_phase_timeplans
        df_movement_utdf_phase = ug.match_movement_utdf_phase_timeplans(df_movement_utdf_lane, utdf_dict_data)

TODO LIST

• Print out how many intersections being geocoded.
• Print out check log.
• Number of lanes of the movements from synchro file.
• Add function to verify whether geocoded for utdf_geo
• Print geocoding details (in percentage)
• Add three kwargs in function generate_movement_utdf
• Print out how many movements being matched or not matched for signalized intersecton nodes.
• Check reasonable capacity.
• Check each movement is reasonable (like 15s of green time...). other attributes.
• Check number of lanes correctness between osm2gmns file and synchro file per movements.
• Add signal info to micro-link.cs
• Add cycle length and green time for each movement.
• Add detailed information for user to load coordinated intersection data.

Call for Contributions

The utdf2gmns project welcomes your expertise and enthusiasm!

Small improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact us through email:

Xiangyong Luo :  [e-mail]

Dr. Xuesong Simon Zhou :  [e-mail]

Writing code isn't the only way to contribute to utdf2gmns. You can also:

• review pull requests
• help us stay on top of new and old issues
• develop tutorials, presentations, and other educational materials
• develop graphic design for our brand assets and promotional materials
• translate website content
• help with outreach and onboard new contributors
• write grant proposals and help with other fundraising efforts

For more information about the ways you can contribute to utdf2gmns, visit our GitHub. If you' re unsure where to start or how your skills fit in, reach out! You can ask by opening a new issue or leaving a comment on a relevant issue that is already open on GitHub.

How to Cite

If you use utdf2gmns in your work or research, please use the following entry:

Luo, X. and Zhou, X. (2022, December 17). UTDF2GMNS. Retrieved from https://github.com/xyluo25/utdf2gmns