Floating car data augmentation based on infrastructure sensors and neural networks

Naranjo Hernández, José Eugenio; Zato Recellado, Jose Gabriel; Serradilla García, Francisco y Jiménez Alonso, Felipe (2012). Floating car data augmentation based on infrastructure sensors and neural networks. "IEEE Transactions on Intelligent Transportation Systems", v. 13 (n. 1); pp. 107-114. ISSN 1524-9050.

Descripción

Título: Floating car data augmentation based on infrastructure sensors and neural networks
Autor/es:
  • Naranjo Hernández, José Eugenio
  • Zato Recellado, Jose Gabriel
  • Serradilla García, Francisco
  • Jiménez Alonso, Felipe
Tipo de Documento: Artículo
Título de Revista/Publicación: IEEE Transactions on Intelligent Transportation Systems
Fecha: Marzo 2012
Volumen: 13
Materias:
Palabras Clave Informales: Floating car data, neural networks, traffic flow, datos de movimiento, redes neuronales, flujo del tráfico.
Escuela: E.U. de Informática (UPM) [antigua denominación]
Departamento: Sistemas Inteligentes Aplicados [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.

Más información

ID de Registro: 15677
Identificador DC: http://oa.upm.es/15677/
Identificador OAI: oai:oa.upm.es:15677
URL Oficial: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Depositado por: Memoria Investigacion
Depositado el: 06 Jun 2013 14:38
Ultima Modificación: 04 Mar 2015 16:30
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