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Article

Characterizing Traffic Conditions from the Perspective of Spatial-Temporal Heterogeneity

by 1,*, 2,*, 2 and 3
1
Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
2
Institute of Geomatics, Department of Civil Engineering, Tsinghua University, Haidian District, Beijing 100084, China
3
College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China
*
Authors to whom correspondence should be addressed.
Academic Editors: Bin Jiang, Constantinos Antoniou and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(3), 34; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5030034
Received: 20 January 2016 / Revised: 3 March 2016 / Accepted: 8 March 2016 / Published: 10 March 2016
(This article belongs to the Special Issue Geospatial Big Data and Transport)
Traffic conditions are usually characterized from the perspective of travel time or the average vehicle speed in the field of transportation, reflecting the congestion degree of a road network. This article provides a method from a new perspective to characterize traffic conditions; the perspective is based on the heterogeneity of vehicle speeds. A novel measurement, the ratio of areas (RA) in a rank-size plot, is included in the proposed method to capture the heterogeneity. The proposed method can be performed from the perspective of both spatial heterogeneity and temporal heterogeneity, being able to characterize traffic conditions of not only a road network but also a single road. Compared with methods from the perspective of travel time, the proposed method can characterize traffic conditions at a higher frequency. Compared to methods from the perspective of the average vehicle speed, the proposed method takes account of the heterogeneity of vehicle speeds. The effectiveness of the proposed method has been demonstrated with real-life traffic data of Shenzhen (a coastal urban city in China), and the advantage of the proposed RA has been verified by comparisons to similar measurements such as the ht-index and the CRG index. View Full-Text
Keywords: head/tail breaks; fractal; ht-index; CRG index; rank-size plot head/tail breaks; fractal; ht-index; CRG index; rank-size plot
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MDPI and ACS Style

Gao, P.; Liu, Z.; Tian, K.; Liu, G. Characterizing Traffic Conditions from the Perspective of Spatial-Temporal Heterogeneity. ISPRS Int. J. Geo-Inf. 2016, 5, 34. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5030034

AMA Style

Gao P, Liu Z, Tian K, Liu G. Characterizing Traffic Conditions from the Perspective of Spatial-Temporal Heterogeneity. ISPRS International Journal of Geo-Information. 2016; 5(3):34. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5030034

Chicago/Turabian Style

Gao, Peichao, Zhao Liu, Kun Tian, and Gang Liu. 2016. "Characterizing Traffic Conditions from the Perspective of Spatial-Temporal Heterogeneity" ISPRS International Journal of Geo-Information 5, no. 3: 34. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5030034

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