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UTTRI Update, February 4, 2021
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NEWS

U of T researchers develop app to track environmental health of neighbourhoods

head shot of Dr. Jeffrey BrookUTTRI associated faculty Professor Jeffrey Brook was featured in U of T News on February 3 for his work developing an app that allows users to learn about air quality, greenery, walkability and other factors contributing to the environmental health of their neighbourhoods.

The E-Best (Equity in the Built Environment Surveillance Tool) project involves a multi-university team and will be rolled out in stages over the next four years. 

The app is tentatively named “Good Score.” Brook hopes that it will empower citizens as well as inform research.

Read the full story U of T News story about the research project and the app.

Farber, Palm on transport equity and new mobility

head shot of Dr. Steven Farberhead shot of Dr. Matthew PalmUTTRI associated faculty Professor Steven Farber (left) and Professor Matthew Palm (right) of Worcester State University took part in “New Mobility, Covid-19, and the Future of Sustainable Urban Transport” presented by the Conference Board of Canada’s Roundtable on Shared Mobility on January 27, 2021.

Their discussion ranged from the uneven impact of the pandemic on public transit users to how emerging mobility technologies could be harnessed to solve pressing problems.

Read more about the discussion and the Roundtable on Shared Mobility.

Modelling mobility services: Calderón

head shot of Dr. Francisco Calderón

Dr. Francisco Calderón Peralvo presented “Modelling Mobility Services within Agent-Based Travel Demand Model Systems and Implementation of a Ridehailing Case Study” on January 22, 2021 for the UT-ITE seminar series.

Conventional travel demand model systems simulate a typical day by looking at each vehicle, activity, type of transit, and travel distances. However, these models only consider demand and supply interaction. Given that ridehailing is a dynamic, complex service, Calderón adds a third dimension: service provision.

Read more about Dr. Calderón's presentation.

Alfaseeh: Predicting GHG emissions with deep learning

head shot of Dr. Lama AlfaseehDr. Lama Alfaseeh, postdoctoral researcher at Ryerson University, presented “Prediction of Greenhouse Gas Emission in Downtown Toronto Using Deep Sequence Learning” on January 15, 2020 for the UT-ITE seminar series.

Transportation systems contribute the largest amounts of greenhouse gas (GHG) emissions in the US and Canada. GHG emissions, which include carbon dioxide, methane, and nitrous oxide, are more harmful to the environment than carbon dioxide alone. Predictive models for routing vehicles proactively have potential in tackling this problem.

Read more about Dr. Alfaseeh's presentation.

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Disclaimer: The information in this newsletter is true to the best of our knowledge at time of posting. All listings are made without guarantee on the part of UTTRI, and we disclaim any liability in connection with the use of this information.

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