Floating car data augmentation based on infrastructure sensors and neural networks

Naranjo Hernández, José Eugenio and Zato Recellado, Jose Gabriel and Serradilla García, Francisco and 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.

Description

Title: Floating car data augmentation based on infrastructure sensors and neural networks
Author/s:
  • Naranjo Hernández, José Eugenio
  • Zato Recellado, Jose Gabriel
  • Serradilla García, Francisco
  • Jiménez Alonso, Felipe
Item Type: Article
Título de Revista/Publicación: IEEE Transactions on Intelligent Transportation Systems
Date: March 2012
ISSN: 1524-9050
Volume: 13
Subjects:
Freetext Keywords: Floating car data, neural networks, traffic flow, datos de movimiento, redes neuronales, flujo del tráfico.
Faculty: E.U. de Informática (UPM)
Department: Sistemas Inteligentes Aplicados [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview

Abstract

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.

More information

Item ID: 15677
DC Identifier: http://oa.upm.es/15677/
OAI Identifier: oai:oa.upm.es:15677
Official URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Deposited by: Memoria Investigacion
Deposited on: 06 Jun 2013 14:38
Last Modified: 04 Mar 2015 16:30
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM