Science Score: 67.0%
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Low similarity (14.1%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Khoshkhah
- Language: Python
- Default Branch: main
- Size: 51.4 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Parallel Dynamic Calibration Tool for City-Scale Microscopic Traffic Simulation using SUMO
Installation
To install and run the calibration tool, follow these steps:
Clone the repository to your local machine:
git clone https://github.com/Khoshkhah/NRTCalib.gitInstall SUMO.
Install the required dependencies. You can use pip to install them: pip install -r requirements.txt
Usage
The calibration tool has to be started via calib.py, which is a command line application. It has the necessary following parameters:
-n network file address, that is a sumo network file.
-m the measurment filename contains sensor data. it is a table file contains three columns "edge", "count" and "interval" that are seperated by comma.
-dod the init distributed origin destination matrix filename. it is a table file contains five columns "fromnode", "tonode", "interval","weighttrip" and "tripid" that are seperated by comma.
-is the size of each interval in seconds. that is a integer number.
For more information of these input look at the sample grid in the examples/grid directory.
For getting the other optional arguments use the help command:
python calib.py --help
Also for running the calibration tool, you can use a configuration xml file like grid.cfg:
python calib.py -c examples/grid/config.cfg
High-level architecture of the calibration method for one frame
Examples and Sample Data
We have provided examples and sample data in the examples directory. You can explore them to understand how to use the tool effectively. All input data and a 24-hour calibrated microscopic traffic simulation for the case study of Tartu City is available at zenodo.org
Contact Information
For any questions, feedback, or inquiries, please feel free to reach out to us: - Email: kaveh.khoshkhah(at)ut.ee
The calibration tool originates from an implementation of this paper Leveraging IoT Data Stream for Near-Real-Time Calibration of City-Scale Microscopic Traffic Simulation. A preprint version of the paper can be downloaded at link.
Owner
- Login: Khoshkhah
- Kind: user
- Repositories: 1
- Profile: https://github.com/Khoshkhah
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Khoshkhah"
given-names: "Kaveh"
email: "kaveh.khoshkhah@ut.ee"
orcid: "https://orcid.org/0000-0003-4777-804X"
- family-names: "Pourmoradnasseri"
given-names: "Mozhgan"
- family-names: "Hadachi"
given-names: "Amnir"
title: "NRTCalib"
doi: 10.5281/zenodo.8125656
date-released: 2023-07-07
url: "https://github.com/Khoshkhah/NRTCalib"
preferred-citation:
type: article
authors:
- family-names: "Khoshkhah"
given-names: "Kaveh"
email: "kaveh.khoshkhah@ut.ee"
orcid: "https://orcid.org/0000-0003-4777-804X"
- family-names: "Pourmoradnasseri"
given-names: "Mozhgan"
- family-names: "Hadachi"
given-names: "Amnir"
doi: "10.48550/arXiv.2210.17315"
journal: "preprint"
title: "Leveraging IoT Data Stream for Near-Real-Time Calibration of City-Scale Microscopic Traffic Simulation"
year: 2022