NDLI: A spatial analysis approach for describing spatial pattern of urban traffic state

Content Provider	IEEE Xplore Digital Library
Author	Haixiang Zou Yang Yue Qingquan Li Yonghui Shi
Copyright Year	2010
Description	Author affiliation: School of Remote Sensing and Information Engineering, Wuhan University, Hubei, China (Haixiang Zou) \|\| Research department of Wuhan traffic management bureau, Hubei, China (Yonghui Shi) \|\| State Key Laboratory for Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Hubei, China (Yang Yue; Qingquan Li)
Abstract	To urban transportation management, it is valuable to obtain the whole road network traffic state, while most existing traffic analysis methods pay little attention to this problem. This paper proposes a method to analyze spatial pattern of road network traffic state, which describes traffic characteristic from network level. Above all, we treat traffic data as road link's attribution and establish a spatial model to describe road network traffic data from spatial perspective. Then using real travel speed data extracted from long-term floating car data, we analyze spatial dependency of traffic state based on spatial autocorrelation method, which shows that urban road network traffic state exist association in space, and this method can quantify the influence degree of road link, which is useful to micro-view traffic management; using trend surface analysis method, we analyze spatial heterogeneity of urban traffic state, which qualitatively shows that urban traffic state is unstable in space and is related to land use. Further, divergence tendency analysis shows that urban traffic state is influenced by road network structure, and it can also quantitatively analyze the influence range, which is useful to detailedly discover hot spot in urban traffic, such as traffic congestion. This study shows that it is a feasible approach to use spatial analysis method to study the overall characteristics of urban traffic system, which is of benefit to both dynamic traffic control and long-term traffic planning.
Starting Page	557
Ending Page	562
File Size	662046
Page Count	6
File Format	PDF
ISBN	9781424476572
ISSN	21530017
e-ISBN	9781424476596
DOI	10.1109/ITSC.2010.5625226
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-19
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Roads Correlation Spatial databases Analytical models Space exploration Data models Bandwidth
Content Type	Text
Resource Type	Article

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