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A C-DBSCAN algorithm for determining bus-stop locations based on taxi GPS data
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posted on 2014-01-01, 00:00 authored by W Wang, L Tao, C Gao, B Wang, H Yang, Z ZhangDetermining suitable bus-stop locations is critical in improving the quality of bus services. Previous studies on selecting bus stop locations mainly consider environmental factors such as population density and traffic conditions, seldom of them consider the travel patterns of people, which is a key factor for determining bus-stop locations. In order to draw people’s travel patterns, this paper improves the density-based spatial clustering of applications with noise (DBSCAN) algorithm to find hot pick-up and drop-off locations based on taxi GPS data. The discovered density-based hot locations could be regarded as the candidate for bus-stop locations. This paper further utilizes the improved DBSCAN algorithm, namely as C-DBSCAN in this paper, to discover candidate bus-stop locations to Capital International Airport in Beijing based on taxi GPS data in November 2012. Finally, this paper discusses the effects of key parameters in C-DBSCAN algorithm on the clustering results. Keywords Bus-stop locations, Public transport service, Taxi GPS data, Centralize density-based spatial clustering of applications with noise.
History
Title of book
Advanced data mining and applications : 10th International Conference, ADMA 2014, Guilin, China, December 19-21, 2014, proceedingsVolume
8933Series
Lecture Notes in Artificial Intelligence; 8933Chapter number
23Pagination
293 - 304Publisher
Springer VerlagPlace of publication
Berlin, GermanyPublisher DOI
ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319147178Language
engPublication classification
B Book chapter; B1 Book chapterCopyright notice
2014, Springer VerlagExtent
58Editor/Contributor(s)
X Luo, J Yu, Z LiUsage metrics
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