Traffic forecasting in smart cities

Traffic forecasting plays a key role in mitigating traffic congestion in urban areas. The main objective of this master thesis is to perform traffic forecasting in urban contexts by developing machine learning models trained with simulated Floating Car Data.

Country

Spain

Related Organizations

Keywords

urban traffic forecast, :Informàtica [Àrees temàtiques de la UPC], aprenentatge profund, City planning -- Environmental aspects, Machine learning, Urbanisme -- Aspectes ambientals, Aprenentatge automàtic, deep learning, Àrees temàtiques de la UPC::Informàtica, predicció de tràfic urbà, dades de vehicle connectat, floating car data

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average