Exploring the potential of Google Popular Times for transit demand estimation

Reference : Exploring the potential of Google Popular Times for transit demand estimation


	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/53469

Title :	Exploring the potential of Google Popular Times for transit demand estimation
Language :	English
Author, co-author :	Vitello, Piergiorgio [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
	Fiandrino, Claudio [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Connors, Richard [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
	Viti, Francesco [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Publication date :	2023
Peer reviewed :	Yes
Event name :	Transportation Research Board (TRB) 102nd Annual Meeting
Event date :	from 08-01-2023 to 12-01-2023
Keywords :	[en] Public transport ; Crowdsensing ; Machine learning
Permalink :	http://hdl.handle.net/10993/53469
FnR project :	FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017

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