Open AccessAn Elastic Combination Forecasting Method for Urban Road Traffic Status
Author(s) -
Cheng Wang,
Xiyu Pang,
Zhonghua Xi,
Guannan Si
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022027
Subject(s) - traffic flow (computer networking) , fractal , computer science , fractal dimension , flow (mathematics) , nonlinear system , traffic system , scale (ratio) , function (biology) , algorithm , transport engineering , mathematical optimization , mathematics , engineering , geography , mathematical analysis , physics , geometry , computer security , cartography , quantum mechanics , evolutionary biology , biology
In intelligent transportation system, urban road traffic flow status prediction plays an important role. Study shows that the traffic flow status has fractal phenomenon in a certain time scale, so using fractal method to excavate the inherent regularity of traffic flow time series can avoid some difficulties of analyzing the traffic flow influencing factors. This paper proposes a new forecasting algorithm of urban road traffic status based on fractal theory, and in the algorithm, the calculation of fractal dimension is based on the structural function method, and the design of the algorithm takes into account the traffic conditions at different time intervals based on the prediction time. The experimental results indicate that the proposed algorithm is capable of dealing with complex nonlinear urban traffic flow forecasting with satisfying accuracy and effectiveness.