This is a Python implementation of the MCTA approach proposed by [1] and expanded upon in [2-5].
The following table describes the use of each mcta module. Examples of its use can be found in the jupyter files test_mcta.ipynb and test_mcta_runtime.ipynb
| File | Description |
|---|---|
| mcta_cli.py | MCTA Command Line Interface (CLI). This is where you should start. |
| mcta.py | MCTA module. This is where the main MCTA logic reside. |
| mcta_edit.py | MCTA network modification module |
| mcta_rw.py | MCTA input/output data read/write module |
| mcta_vis.py | MCTA visualization module |
ga.py and ga_batch_run.py implements a genetic algorithm metaheuristic on top of MCTA. resutls are graphed using ga_polts.ipynb.
A module for estimating emissions based on road network traffic conditions. Estimation methedology is based on: Bureau of Public Roads (BPR) curve, COPERT_v5, and TRANSYT7f.
[1] Crisostomi, E., Kirkland, S., & Shorten, R. (2011). A Google-like model of road network dynamics and its application to regulation and control. International Journal of Control, 84(3), 633–651. https://doi.org/10.1080/00207179.2011.568005
[2] Salman, S., & Alaswad, S. (2017). Urban road network crisis response management: Time-sensitive decision optimization. Proceedings of the 2017 Industrial and Systems Engineering Conference, 1307–1313. Retrieved from Scopus. http://amz.xcdsystem.com/iisePapers/iise/2018/papers/SubmitFinalPaper_1350_0304110129.pdf
[3] Salman, S., & Alaswad, S. (2018). Alleviating road network congestion: Traffic pattern optimization using Markov chain traffic assignment. Computers & Operations Research, 99, 191–205. https://doi.org/10.1016/j.cor.2018.06.015
[4] Salman, S., & Alaswad, S. (2019). Mitigating the Impact of Congestion Minimization on Vehicles’ Emissions in a Transportation Network. Proceedings for th 25th International Joint Conference on Industrial Engineering and Operations Management. http://doi.org/10.24867/IJIEM-2020-1-251
[5] Salman, S. & Alaswad, S. (2021). Designing Reduced Congestion Road Networks via an Elitist Adaptive Chemical Reaction Optimization. Computers & Industrial Engineering, Accepted on Oct 31, 2021. https://doi.org/10.1016/j.cie.2021.107788