DocumentCode :
2248726
Title :
Discrepancy in real-time traveler info websites traffic condition estimation based on rough set theory
Author :
Liu, Hao ; Zhang, Ke
Author_Institution :
Nat. ITS Res. Center, Res. Inst. of Highway, Beijing, China
fYear :
2009
fDate :
4-7 Oct. 2009
Firstpage :
1
Lastpage :
6
Abstract :
More and more real-time traveler information Websites have been set up to provide real-time traffic condition information. They derive traffic conditions with different algorithms based on different data sources. We have found that there is a discrepancy among those Websites. This certainly confuses users because they provide inconsistent traffic condition information. As known, people draw conclusions of traffic conditions in a vague way. Estimating traffic conditions is not necessary with high resolution, while a rough classification might be enough. This paper presents a rough set model to address the problem of traffic condition estimation. A densely used urban arterial in Beijing was selected to test the performance of this model. Also, the existing models used in practice are used for comparison. The results of the comparisons indicate that this proposed model is capable of classifying traffic conditions with satisfying accuracy.
Keywords :
Web sites; real-time systems; road traffic; rough set theory; data sources; real-time traffic condition information; real-time traveler information Web sites; rough classification; rough set model; rough set theory; traffic condition classification; traffic condition estimation; traffic conditions; urban arterial; Detectors; Global Positioning System; Intelligent transportation systems; Licenses; Real time systems; Road transportation; Set theory; Traffic control; USA Councils; Vehicles; Traffic Condition Estimation; comparison; existing algorithms; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems, 2009. ITSC '09. 12th International IEEE Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-5519-5
Electronic_ISBN :
978-1-4244-5520-1
Type :
conf
DOI :
10.1109/ITSC.2009.5309681
Filename :
5309681
Link To Document :
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