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Machine learning analysis sheds light on who benefits from protected bike lanes - U of T Engineering News

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U of T Engineering analysis optimizes the placement of cycling infrastructure in Toronto according to different strategies — and finds a trade-off between equity and efficiency By Tyler Irving Posted Oct 15, 2024 Share this post: A new analysis from U of T Engineering researchers leverages machine learning to help answer a thorny question: where should new protected bike lanes be placed to provide maximum benefit? “Right now, some people have really good access to protected biking infrastructure: they can bike to work, to the grocery store or to entertainment venues,” says Madeleine Bonsma-Fisher, a postdoctoral fellow in the Department of Civil & Mineral Engineering and lead author of a new paper published in the Journal of Transport Geography. “More lanes could increase the number of destinations they can reach, and previous work shows that will increase the number of cycle trips taken. “However, many people have little or no access to protected cycling infrastructure at all, limitin

Machine learning analysis sheds light on who benefits from protected bike lanes - U of T Engineering News Machine learning analysis sheds light on who benefits from protected bike lanes U of T Engineering analysis optimizes the placement of cycling infrastructure in Toronto according to different strategies — and finds a trade-off between equity and efficiency By Tyler Irving Posted Oct 15, 2024 Share this post: Copy link Share on Facebook Facebook Share on Linkedin Linkedin Toronto aims to have 75% of school/work trips under 5 kilometres walked, biked or by transit by 2030. Protected bike lan

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