Search results for "Origin-Destination matrices"

showing 2 items of 2 documents

Evaluation of the Use of a City Center through the Use of Bluetooth Sensors Network

2019

In order to achieve the objectives of Smart Cities, public administrations need to take measures to regulate mobility, which undoubtedly requires a high level of information and sensorization. Until the implementation of the connected vehicle takes place, it is still necessary to install sensors to obtain information about mobility. Bluetooth sensors are becoming a useful tool due to the low cost of equipment and installation. The use of Bluetooth sensors in cities, with short distances between sensors, makes it necessary to propose new classification algorithms that allow the trips of pedestrians and vehicles to be differentiated. This article presents the study carried out in the city of …

Computer scienceGeography Planning and DevelopmentReal-time computinglcsh:TJ807-8300211 other engineering and technologieslcsh:Renewable energy sourcestraffic management02 engineering and technologyManagement Monitoring Policy and Lawvehicle and pedestrian travel timelaw.inventionBluetoothlawSmart city0502 economics and businessDesenvolupament sostenibleDisseny urbàlcsh:Environmental scienceslcsh:GE1-350050210 logistics & transportationRenewable Energy Sustainability and the EnvironmentMAC addressbluetooth sensorlcsh:Environmental effects of industries and plants05 social sciences021107 urban & regional planningvalencia city centerlcsh:TD194-195smart cityOrder (business)mobility studies using BTCirculacióOrigin-Destination matricesMobile deviceSustainability
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Suitability Of Cellular Network Signaling Data For Origin-Destination Matrix Construction: A Case Study Of Lyon Region (France)

2019

TRB 2019, 98th Annual Meeting Transportation Research Board, Washigton, D.C., ETATS-UNIS, 13-/01/2019 - 17/01/2019; Spatiotemporal data, and more specifically origin-destination matrices, are critical inputs to mobility studies for transportation planning and urban management purposes. In this paper, we propose a methodology to infer origin-destination (O-D) matrices based on passively-collected cellular signaling data of millions of anonymized mobile phone users in the Rhône-Alpes region, France. This dataset, which consists of records time-stamped with users' unique identifier and tower locations, is used to first analyze the cell phone activity degree indicators of each user in orde…

PASSIVE CELLULAR SIGNALING DATAPLANIFICATIONLYONTRAITEMENT DES DONNEESZONE URBAINERESEAU DE TRANSPORTTELEPHONE MOBILERESEAU DE TELECOMMUNICATIONS[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationMODELISATIONITINERAIRE ROUTIERHOME DETECTIONORIGIN-DESTINATION MATRICESDETECTIONTRAITEMENT DU SIGNALTECHNOLOGIE SANS FILLOCALISATIONVOYAGERECUEIL DE DONNEESSIMULATION[INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationTRAVEL SURVEYTRIP EXTRACTION
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