A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)

Autor: Tom Bellemans, Patrick Bonnel, Angelo Furno, Stéphane Galland, Mariem Fekih, Zbigniew Smoreda
Přispěvatelé: Transportation Research Institute, Hasselt University, Orange Labs [Issy les Moulineaux], France Télécom, Laboratoire Aménagement Économie Transports (LAET), Université Lumière - Lyon 2 (UL2)-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE ), École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon-Université Gustave Eiffel, Connaissance et Intelligence Artificielle Distribuées [Dijon] (CIAD), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)
Rok vydání: 2020
Předmět:
LYON
BIG DATA
TRAVEL DEMAND ESTIMATION
Computer science
Population
Big data
TRACES
DUREE DU TRAJET
0211 other engineering and technologies
TELEPHONE MOBILE
Transportation
BIG DATA ANALYSIS
02 engineering and technology
MOBILE PHONE
Development
computer.software_genre
HOME DETECTION
Data-driven
Unique identifier
[SPI.GCIV.IT]Engineering Sciences [physics]/Civil Engineering/Infrastructures de transport
Phone
11. Sustainability
0502 economics and business
TRAFIC ROUTIER
education
TRAVEL SURVEY
Civil and Structural Engineering
PLANIFICATION
050210 logistics & transportation
education.field_of_study
TRAITEMENT DES DONNEES
business.industry
05 social sciences
021107 urban & regional planning
ORIGIN-DESTINATION MATRIX
PASSIVE CELLULAR SIGNALLING DATA
FRAMEWORK
RECUEIL DE DONNEES
Travel survey
Mobile phone
PATTERNS
Cellular network
Data mining
TRAJECTORIES
business
computer
TRIP EXTRACTION
Zdroj: Transportation
Transportation, Springer Verlag, 2020, 32p. ⟨10.1007/s11116-020-10108-w⟩
ISSN: 1572-9435
0049-4488
DOI: 10.1007/s11116-020-10108-w
Popis: Spatiotemporal data, and more specifically origin-destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes. Traditionally, high-cost and hard-to-update household travel surveys are used to produce large-scale origin-destination flow information of individuals' whereabouts. In this paper, we propose a methodology to estimate origin-destination (O-D) matrices based on passively-collected cellular network signalling data of millions of anonymous mobile phone users in the Rhone-Alpes region, France. Unlike Call Detail Record (CDR) data which rely only on phone usage, signalling data include all network-based records providing higher spatiotemporal granularity. The explored dataset, which consists of time-stamped traces from 2G and 3G cellular networks with users' unique identifier and cell tower locations, is used to first analyse the cell phone activity degree indicators of each user in order to qualify the mobility information involved in these records. These indicators serve as filtering criteria to identify users whose device transactions are sufficiently distributed over the analysed period to allow studying their mobility. Trips are then extracted from the spatiotemporal traces of users for whom the home location could be detected. Trips have been derived based on a minimum stationary time assumption that enables to determine activity (stop) zones for each user. As a large, but still partial, fraction of the population is observed, scaling is required to obtain an O-D matrix for the full population. We propose a method to perform this scaling and we show that signalling data-based O-D matrix carries similar estimations as those that can be obtained via travel surveys.
Databáze: OpenAIRE
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