Buildings and Cities: Difference between revisions

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=== Urban transportation ===
''Main article: [[Transportation]]''
 
Urban transportation is of high relevance to mitigating climate change in cities, as mobility within cities represents a large share of the total final energy use in the transportation sector (40% in 2010<ref>{{Cite book|title=Policy Pathways: A Tale of Renewed Cities. International Energy Agency|last=IEA|first=|publisher=|year=2013|isbn=|location=Paris|pages=98}}</ref>). Transportation topics are treated as a separate [[Transportation|section]] of the wiki, where areas of particular relevance include:
* '''[[Understanding mobility patterns]]'''
 
* '''[[Enabling low-carbon shared mobility]]'''
* '''[[Understanding mobility patterns]]''' For shared mobility to be a low-carbon option, it needs to effectively enable to reduce the number of kilometers travelled by pooling users. ML can help real-time decision for example for ride-hailing services.
* '''[[Electric vehicle charging infrastructure]]'''
* '''[[Enabling low-carbon shared mobility]]''' 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.
* '''[[Fostering urban cycling]]'''
* '''[[Electric vehicle charging infrastructure]]''' Deploying electric vehicles at scale requires an adequate charging infrastructure, with various planning, scheduling and management issues. ML can help for example with predicting usage of the infrastructure and load prediction.
* '''[[Supporting public transportation network expansion]]'''
* '''Fostering urban cycling'''
* '''Supporting public transportation network expansion'''
 
 
=== Urban transportation ===