Understanding mobility patterns: Difference between revisions
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Large amounts of geolocated traces are being collected that enable the analysis of mobility patterns. This can be useful for better managing existing as well as planning future transport systems. Machine learning (ML) offers great potential to progress the following areas.
To better understand existing transport systems, '''ML''' '''can be used to detect the structure of a transport network as well as its
Furthermore, '''ML applied to''' '''
Next to that, '''ML can be used to assess the impact of a''' '''local context (such as the urban form) on mobility'''. Building up on this, planning strategies can be derived which support a low carbon transport future.
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