Skip to main content

"Dynamic Traffic Simulation Package with Multi-Resolution Modelling" (DLSim-MRM) is an open source, high-fidelity multi-resolution (i.e., macroscopic, mesoscopic, and microscopic simulation) traffic simulation package which users jointly apply varying temporal and spatial resolutions to solve a single question or set of questions that mirror the physical world with complex intersections. Users can perform traffic assignments and feed results from one model to another while maintaining consistency between the model assumptions. DLSim-MRM typically takes the following steps for simulation based on General Modeling Network Specification (GMNS) format:

  1. Use demand forecasting models to determine overall trip patterns in a regional network, including trip generation, trip distribution, mode split, and initial O-D matrices.
  2. Use mesoscopic simulation-based dynamic traffic assignment (DTA) to realistically assign traffic to the network by accounting for strategic traveler behavior.
  3. Use microscopic analysis of traffic at the corridor level or subnetwork level.

DLSim-MRM uses 3 open-source packages; OSM2GMNS, Path4GMNS and Vol2Timing with the additional developments along the multi-resolution modelling and dyanmic traffic simulation.

-OSM2GMNS can help users easily convert networks from OpenStreetMap to .csv files with standard GMNS format for visualization, traffic simulation and planning purpose.

-Path4GMNS is an open-source AMS library for efficiently macroscopic and mesoscopic traffic assignment based on General Modeling Network Specification (GMNS) format.

-Vol2Timing is a python tool aims to offer a light-weight computational engine to generate optimize signal control timing data, and analyze the effectiveness of signal control strategies.

Installation:

DLSim has been published on PyPI, and can be installed by using package manager pip to install DLSim.

pip install DLSim

If you need a specific version of DLSim, say, 0.2.1,

$ pip install dlsim==0.2.11

Usage

Find the shortest path (based on distance) and output it in the format of a sequence of node/link IDs.

from DLSim import DLSim

# load the DLSim class
DL = DLSim()

# check the working directory
DL.check_working_directory()

# check all the required files exist
DL.check_DLSim_input_files()

# load and update settings
DL.DLSim_settings

# perform kernel network assignment simulation
DL.perform_kernel_network_assignment_simulation()



Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

License

Metadata

Release files for DLSim 0.2.12

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for DLSim 0.2.12
File Size Uploaded Provenance
dlsim-0.2.12.tar.gz 401.3 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for DLSim 0.2.12
File Interpreter ABI Platform
DLSim-0.2.12-py3-none-any.whl Python 3 none any Details

Total release size: 802.1 kB

Release files / dlsim-0.2.12.tar.gz

Download URL dlsim-0.2.12.tar.gz
Size 401.3 kB
Tags Source
SHA-256 checksum
How to use checksums
892fbd38dbc22e0a6ac6aaba12abee18292bc01eacec0d7421fd6cb72258f85f
BLAKE2b-256 checksum
How to use checksums
ad7e776353eeec82c72885e050ce12bc767417c73141815810aa80720bbffd48
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.11.7

Release files / DLSim-0.2.12-py3-none-any.whl

Download URL DLSim-0.2.12-py3-none-any.whl
Size 400.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
8105fb73ff8d0743ebf9e38fc024ebdb2d8602716ee206f0ee0dfa199fa2cdf1
BLAKE2b-256 checksum
How to use checksums
c396d7c4182350b4d1c6e4699bdd8d92d4c12049968e272ac97762a6818d79bb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.11.7

Security for DLSim 0.2.12

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page