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Title: Experimental Analysis of Wireless Positioning Accuracy for Vehicular Ad Hoc Network Technology Application
Accession Number: 01371101
Record Type: Component
Abstract: Vehicular ad-hoc networks (VANets) form when vehicles are equipped with devices capable of short-range wireless communication. Accurate wireless positioning of VANets is a challenging task, which requires a robust wireless positioning algorithm. In this study, the trilateral and quadrilateral algorithms are proposed to estimate the moving vehicle node¡¯s position in VANets based on the wireless signal¡¯s ¡°distance-loss¡± model and geometric relationship. Furthermore, a wireless positioning experimental platform was created to test the positioning algorithm applications in field. The test field is an open area with one moving node and four fixed nodes. The experimental results show that when the moving node is inside the fixed nodes, the positioning accuracy is much higher than the case that the moving node is outside the fixed nodes; when the moving node is located in the middle of the experimental field, the positioning accuracy is higher than located at the corner areas in the test field; and the quadrilateral positioning method has a better positioning accuracy.
Supplemental Notes: This paper was sponsored by TRB committee AHB15 Intelligent Transportation Systems
Monograph Title: Monograph Accession #: 01362476
Report/Paper Numbers: 12-2003
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Wang, JiangfengYan, XuedongShao, ChunfuWei, LiyingPagination: 17p
Publication Date: 2012
Conference:
Transportation Research Board 91st Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References; Tables
TRT Terms: Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment; I70: Traffic and Transport; I90: Vehicles
Source Data: Transportation Research Board Annual Meeting 2012 Paper #12-2003
Files: TRIS, TRB
Created Date: Feb 8 2012 5:07PM
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