Micro Transit Demand Management (microTDM) with Big Data and Artificial Intelligence

Many typical transit operating costs are lumpy and expensive; the addition of an extra bus on a route at rush hour can cost up to a million dollars over the course of the year. At the same time, an extra bus is sometimes added to satisfy demand for a relatively small number of transit users. This project seeks to understand how micro transit demand management (microTDM) can change the behavior of a small number of transit users to obviate the need for costly, additional buses. To get there, we’ll use Big Data and Artificial Intelligence to ask who to incentives, when and with what? BusPas Inc. will benefit from participation in this project by being able to use the results of this research, as well mechanisms developed by the project applicants in BusPas’s implementation of microTDM. Doing so will place BusPas and Canada at the cutting edge of smart cities technologies as they relate to transit system management in the world.

Faculty Supervisor:

Zachary Patterson;Nizar Bouguila;Owen Waygood


Ashkan Amirnia;Zixiang Xian;Ravi Teja Vemuri;Shahrzad Ranjbar;Bingwei Ge


BusPas Inc



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