DocumentCode :
2837641
Title :
Reverse Nearest Neighbors Query for Moving Objects in Road Network
Author :
Xu Lin ; Zhang Tong
Author_Institution :
Transp. Res. Center, Wuhan Univ., Wuhan, China
fYear :
2009
fDate :
11-13 Dec. 2009
Firstpage :
1
Lastpage :
4
Abstract :
With the increasing popularity of all kinds of applications which depends on continuously changing positions of moving objects such as location-based services (LBS) and intelligent transportation system (ITS), reverse nearest neighbors search/query (RNN) for moving objects in road network has began to receive wide attentions in recent years. Though such queries have been studied quite extensively in Euclidean spaces, there are few works for objects moving on the road network. In this paper, we first propose an update-efficient data structure to index current positions of moving object in road networks. Then, based on the proposed index structure, we design a new RNN query algorithm, namely the RNN_Turn_MO. In contrast to existing methods, turn restriction of road network are taken into more consideration so that the query result can better meet the need of our real lives. The experimental studies show our methods can support RNN query considering turn prohibition efficiently.
Keywords :
query processing; road traffic; traffic engineering computing; visual databases; RNN query algorithm; RNN_Turn_MO; index structure; intelligent transportation system; location-based service; moving object; object position; reverse nearest neighbors query; reverse nearest neighbors search; road network; turn prohibition; turn restriction; update-efficient data structure; Algorithm design and analysis; Data structures; Intelligent networks; Intelligent transportation systems; Laboratories; Nearest neighbor searches; Query processing; Recurrent neural networks; Remote sensing; Road transportation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
Type :
conf
DOI :
10.1109/CISE.2009.5364547
Filename :
5364547
Link To Document :
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