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Mohammad Amin Abedini presents 'A Machine-Learning Framework for Clustering and Calibration of Roadway Performance Models with Application in Large-Scale Traffic Assignment'

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Please join us for the in-person seminar by Mohammad Amin Abedini on Friday September 16th from 11 AM to 12 PM at the ITS lab. Free coffee will be offered!

The roadway performance model is one component of travel demand model systems, whose primary purpose is to replicate the congestion effect in traffic assignment. One of the main challenges of developing these performance models is the availability of data, which historically was largely lacking. Thanks to emerging data sources, this study proposes a multi-stage machine-learning-based framework to clean, classify and calibrate roadway performance models of various roadway functional classes in the Greater Toronto and Hamilton Area (GTHA). Recurrent spatial and temporal trends of roadway performance are further investigated, and distinctive patterns are observed for road segments with specific physical attributes.

About the speaker

head shot of Mohammad Amin Abedini
Mohammad Amin Abedini

Mohammad Amin Abedini holds a BSc in Civil engineering from Shiraz University, Iran. Later, he joined Professor Miller’s research group at the University of Toronto in 2020 as an MASc student. His research interest is focused on advancing transportation models using new data sources and analytics techniques

Presented by University of Toronto ITE Student Chapter, UT-ITE.

Free. All are welcome

If any specific accommodations are needed, please contact Requests should be made as early as possible.


September 16, 2022
11:00 am to 12:00 pm EDT
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ITS Lab and Testbed, SF3103
Sandford Fleming Building, University of Toronto, 10 King's College Road, 3rd Floor, Room SF3103
Toronto, ON M5S 1A4 Canada


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