Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43564
Title: Using massive vehicle positioning data to improve control and planning of public road transport
Authors: Padrón, Gabino 
García, Carmelo R. 
Quesada-Arencibia, A. 
Alayón, Francisco 
Pérez, Ricardo 
UNESCO Clasification: 120304 Inteligencia artificial
3327 Tecnología de los sistemas de transporte
Keywords: Mobile positioning systems
Automated data collection systems
Intelligent transportation systems
Pattern recognition
Issue Date: 2014
Journal: Sensors 
Abstract: This study describes a system for the automatic recording of positioning data for public transport vehicles used on roads. With the data provided by this system, transportation-regulatory authorities can control, verify and improve the routes that vehicles use, while also providing new data to improve the representation of the transportation network and providing new services in the context of intelligent metropolitan areas. The system is executed autonomously in the vehicles, by recording their massive positioning data and transferring them to remote data banks for subsequent processing. To illustrate the utility of the system, we present a case of application that consists of identifying the points at which vehicles stop systematically, which may be points of scheduled stops or points at which traffic signals or road topology force the vehicle to stop. This identification is performed using pattern recognition techniques. The system has been applied under real operating conditions, providing the results discussed in the present study.
URI: http://hdl.handle.net/10553/43564
ISSN: 1424-8220
DOI: 10.3390/s140407342
Source: Sensors (Switzerland)[ISSN 1424-8220],v. 14 (4), p. 7342-7358
Appears in Collections:Artículos
Thumbnail
PDF
Adobe PDF (607,76 kB)
Show full item record

SCOPUSTM   
Citations

8
checked on Apr 21, 2024

WEB OF SCIENCETM
Citations

7
checked on Feb 25, 2024

Page view(s)

64
checked on Oct 15, 2022

Download(s)

63
checked on Oct 15, 2022

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.