Journal ArticleDOI
Deriving origin destination data from a mobile phone network
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TLDR
A technique was developed that makes use of the global system for mobile communications (GSM) mobile phone network, and the flow of mobile phones in a cell-phone network is measured and correlated to traffic flow.Abstract:
Acquiring high-quality origin-destination (OD) information for traffic in a geographic area is both time consuming and expensive while using conventional methods such as household surveys or roadside monitoring. These methods generally present only a snapshot of traffic situation at a certain point in time, and they are updated in time intervals of up to several years. A technique was developed that makes use of the global system for mobile communications (GSM) mobile phone network. Instead of monitoring the flow of vehicles in a transportation network, the flow of mobile phones in a cell-phone network is measured and correlated to traffic flow. This methodology is based on the fact that a mobile phone moving on a specific route always tends to change the base station nearly at the same position. For a first pilot study, a GSM network simulator has been designed, where network data can be simulated, which is then extracted from the phone network, correlated, processed mathematically and converted into an OD matrix. Primary results show that the method has great potential, and the results inferred are much more cost-effective than those generated with traditional techniques. This is due to the fact that no change has to be made in the GSM network, because the information that is needed can readily be extracted from the base station database, that is the entire infrastructure needed is already in placeread more
Citations
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Journal ArticleDOI
Human mobility: Models and applications
Hugo Barbosa,Marc Barthelemy,Gourab Ghoshal,Charlotte R James,Maxime Lenormand,Thomas Louail,Ronaldo Menezes,José J. Ramasco,Filippo Simini,Marcello Tomasini +9 more
TL;DR: This survey reviews the approaches developed to reproduce various mobility patterns, with the main focus on recent developments, and organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility.
Journal ArticleDOI
Estimating Origin-Destination Flows Using Mobile Phone Location Data
TL;DR: Using an algorithm to analyze opportunistically collected mobile phone location data, the authors estimate weekday and weekend travel patterns of a large metropolitan area with high accuracy.
Journal ArticleDOI
Development of origin–destination matrices using mobile phone call data
Md. Shahadat Iqbal,Charisma F. Choudhury,Charisma F. Choudhury,Charisma F. Choudhury,Pu Wang,Pu Wang,Marta C. González +6 more
TL;DR: This research proposes a methodology to develop OD matrices using mobile phone Call Detail Records (CDR) and limited traffic counts to determine the scaling factors that result best matches with the observed traffic counts.
Journal ArticleDOI
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore
TL;DR: This research provides an innovative data mining framework that synthesizes the state-of-the-art techniques in extracting mobility patterns from raw mobile phone CDR data, and design a pipeline that can translate the massive and passive mobile phone records to meaningful spatial human mobility patterns readily interpretable for urban and transportation planning purposes.
Journal ArticleDOI
The path most traveled: Travel demand estimation using big data resources
Jameson L. Toole,Serdar Çolak,Bradley Sturt,Lauren P. Alexander,Alexandre G. Evsukoff,Marta C. González +5 more
TL;DR: This work presents a flexible, modular, and computationally efficient software system that estimates multiple aspects of travel demand using call detail records from mobile phones in conjunction with open- and crowdsourced geospatial data, census records, and surveys.
References
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Journal ArticleDOI
Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis
TL;DR: The ‘Mobile Landscapes' project is presented: an application in the metropolitan area of Milan, Italy, based on the geographical mapping of cell phone usage at different times of the day, which enables a graphic representation of the intensity of urban activities and their evolution through space and time.
Journal ArticleDOI
Location based services—new challenges for planning and public administration?
Rein Ahas,Ülar Mark +1 more
TL;DR: The Social Positioning Method (SPM) as mentioned in this paper studies social flows in time and space by analyzing the location coordinates of mobile phones and the social identification of the people carrying them.
Proceedings ArticleDOI
Extracting origin destination information from mobile phone data
Joanna White,Ivan Wells +1 more
TL;DR: This paper focuses on the development of a model to estimate the number of vehicles travelling between points on a network over a given period of time using origin destination matrices, which have a wide variety of other uses.
Operational parameters affecting the use of anonymous cell phone tracking for generating traffic information
Randall Cayford,Tigran Johnson +1 more
TL;DR: In this article, the E911 initiative mandated by the FCC presents the possibility that a traffic surveillance system based on the movements of cell phones could generate travel information for all roads in an urban street network, which depends on the interaction of several parameters including: the accuracy of the locations, the frequency with which location measurements are taken, and the number of locations available to support traffic monitoring in a given area.
Journal ArticleDOI
Accuracy of speed measurements from cellular phone vehicle location systems
TL;DR: Simulation methods are used to investigate the accuracy of vehicle speed measurements derived from anonymous tracking of cellular phone calls to suggest that such a surveillance system would be capable of stratifying observed vehicle speeds into at least three categories, such as low, medium, and high.