Towards Privacy-Neutral Travel Time Estimation from Mobile Phone Signalling Data

Derrmann, Thierry; Frank, Raphaël; Faye, Sébastien; Castignani, German; Engel, Thomas

Reference : Towards Privacy-Neutral Travel Time Estimation from Mobile Phone Signalling Data


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/28013

Title :	Towards Privacy-Neutral Travel Time Estimation from Mobile Phone Signalling Data
Language :	English
Author, co-author :	Derrmann, Thierry [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Frank, Raphaël [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Faye, Sébastien [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Castignani, German [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Engel, Thomas [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	Sep-2016
Main document title :	Proceedings of the 2016 IEEE International Smart Cities Conference (ISC2)
Peer reviewed :	Yes
Audience :	International
Event name :	IEEE International Smart Cities Conference (ISC2)
Event date :	from 12-09-2016 to 15-09-2016
Event place (city) :	Trento
Event country :	Italy
Abstract :	[en] Today’s mobile penetration rates enable cellular signaling data to be useful in diverse fields such as transportation planning, the social sciences and epidemiology. Of particular interest for these applications are mobile subscriber dwell times. They express how long users stay in the service range of a base station. In this paper, we want to evaluate whether dwell time distributions can serve as predictors for road travel times. To this end, we transform floating car data into synthetic dwell times that we use as weights in a graph-based model. The model predictions are evaluated using the floating car ground truth data. Additionally, we show a potential link between handover density and travel times. We conclude that dwell times are a promising predictor for travel times, and can serve as a valuable input for intelligent transportation systems.
Research centres :	SnT
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/28013
FnR project :	FnR ; FNR5825301 > Thomas Engel > MAMBA > MultimodAl MoBility Assistance > 01/04/2014 > 31/03/2017 > 2013

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