DocumentCode
3432645
Title
Intelligent transport navigation system using LookAhead Continuous KNN
Author
Geng Zhao ; Kefeng Xuan ; Taniar, D. ; Rahayu, W. ; Srinivasan, Bama
Author_Institution
Clayton Sch. of IT, Monash Univ. Australia, Clayton, VIC
fYear
2009
fDate
10-13 Feb. 2009
Firstpage
1
Lastpage
6
Abstract
One of the most popular queries in vehicle navigation, continuous k nearest neighbor, has been widely addressed. However, none of them focuses on continuous lookahead k nearest neighbor. Hence, in this paper, we propose a new approach, called continuous lookahead K nearest neighbor (CLKNN). CLKNN query is different from the traditional continuous k nearest neighbor, whereby in our CLKNN, mobile users concerns with only the interest points in the forward space of query point according to a predefined moving direction. Interest points, which are behind the moving query point, are not of interest anymore. We propose algorithms for lookahead KNN as well as continuous lookahead KNN. The former is used for static query point, whereas the latter is used for moving query point. Our experiments verify the applicability of the proposed approach to solve queries which involve lookahead k nearest neighbors continuously.
Keywords
automated highways; computerised navigation; query processing; continuous lookahead K nearest neighbor; intelligent transport navigation system; query point; vehicle navigation; Delay; Euclidean distance; Filters; Fuels; Intelligent systems; Intelligent vehicles; Navigation; Nearest neighbor searches; Roads; Vehicle safety;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology, 2009. ICIT 2009. IEEE International Conference on
Conference_Location
Gippsland, VIC
Print_ISBN
978-1-4244-3506-7
Electronic_ISBN
978-1-4244-3507-4
Type
conf
DOI
10.1109/ICIT.2009.4939586
Filename
4939586
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