Urban Traffic Congestion Detection Based on Clustering Analysis of Real-time Traffic Data
| Autor: | Zhihao Song, Muzi Li, Zhu Xu, Xiaoya Lu, Weiya Sun, Ting Li |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
DBSCAN
Traffic congestion reconstruction with Kerner's three-phase theory Geography Traffic congestion business.industry ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS Floating car data Urban road business Cluster analysis Network traffic control Computer network Task (project management) |
| Zdroj: | Journal of Geo-information Science. 14:775 |
| ISSN: | 1560-8999 |
| DOI: | 10.3724/sp.j.1047.2012.00775 |
| Popis: | Traffic congestion in urban road network heavily restricts transportation efficiency.Detecting traffic congestions in the spatio-temporal sense and identifying network bottlenecks become an important task in transportation management.Up to now,many traffic congestion detection methods have been proposed,which have focused on the detection of momentary local congestions.Larger-scale,longer-time and regular congestions can't be detected using these methods.That is because congestions have different temporo-spatial scales,and a characteristic is not considered in those methods.This paper proposes a new kind of urban traffic congestion detection method that deals with spatio-temporal extension of congestion.It is based on spatio-temporal clustering analysis of real-time traffic data.By defining a proper spatio-temporal correlation,the classic DBSCAN algorithm is adapted to tackle spatio-temporal clustering.With it we can detect longer time and regular traffic congestion in the spatio-temporal sense.Experiments have been conducted using real traffic condition data of Chengdu to validate the effectiveness of the method.The experiment shows that the proposed method can detect the congestion areas and identify the spatio-temporal extent of congestions accurately.The detected congestion areas were compared with congestion report from local traffic management authority and found to be consistent with the later. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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