|Table of Contents|

Moving vehicle location method based on traffic wireless sensor network(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2013年01期
Page:
114-120
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Moving vehicle location method based on traffic wireless sensor network
Author(s):
LAI Lei;  QU Shi-ru
School of Automation, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China
Keywords:
intelligent transportation system;  vehicle location;  wireless sensor network;  particle swarm optimization;  time difference of arrival;  Kalman filter
PACS:
U495
DOI:
-
Abstract:
To improve the location reliability and accuracy, moving vehicle location system based on traffic wireless sensor network was studied. Based on the law that vehicle location changed along with its speed, a variable interval quantum particle swarm optimization algorithm was proposed, by which the measured vehicle location parameters could be used for the rough estimation of vehicle coordinates. For the noise interferences and signal delay, the rough estimated values of vehicle coordinates were always prone to error. The current statistical model was introduced into the algorithm under the motion constraints of vehicle, and the extended Kalman filter was used to eliminate the location errors. The proposed method was tested by the evaluation indexes of speed and accuracy. Tested result indicates that the location reliability is improved for that the enormous sum nodes of wireless sensor network can be disposed. The variable interval introduced into the quantum particle swarm optimization increases the convergence speed by 39.13%. The Kalman filter corrects the errors, and improves location precision by 56.48%. The proposed algorithm demonstrates the superiority in terms of location reliability and accuracy. 1 tab, 8 figs, 19 refs.

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Last Update: 2013-03-30