Fostering cycling as mode of transport: Difference between revisions
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''This page is about the applications of machine learning (ML) in the context of urban cycling. For an overview of utility cycling more generally, please see the [https://en.wikipedia.org/wiki/Utility_cycling Wikipedia page] on this topic.'' |
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Cycling is a low-carbon, healthy way to commute in cities, but inhabitants often use this mode less than they would like to due to inappropriate biking infrastructure, which makes cycling more complicated and dangerous. ML can be used in the planning and management of new biking infrastructure, in particular in the context of shared bike services. |
Cycling is a low-carbon, healthy way to commute in cities, but inhabitants often use this mode less than they would like to due to inappropriate biking infrastructure, which makes cycling more complicated and dangerous. ML can be used in the planning and management of new biking infrastructure, in particular in the context of shared bike services. |
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Latest revision as of 08:24, 9 September 2021
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This page is about the applications of machine learning (ML) in the context of urban cycling. For an overview of utility cycling more generally, please see the Wikipedia page on this topic.
Cycling is a low-carbon, healthy way to commute in cities, but inhabitants often use this mode less than they would like to due to inappropriate biking infrastructure, which makes cycling more complicated and dangerous. ML can be used in the planning and management of new biking infrastructure, in particular in the context of shared bike services.