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2009 WRI World Congress on Computer Science and Information Engineering
Research of Chang'an Street Coordinated Fuzzy Control Based on Traffic Flow Forecasting
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
| ASCII Text | x | ||
| Haifeng Qian, Yangzhou Chen, Zhenlong Li, Yuzhen Yang, "Research of Chang'an Street Coordinated Fuzzy Control Based on Traffic Flow Forecasting," Computer Science and Information Engineering, World Congress on, vol. 6, pp. 39-42, 2009 WRI World Congress on Computer Science and Information Engineering, 2009. | |||
| BibTex | x | ||
| @article{ 10.1109/CSIE.2009.685, author = {Haifeng Qian and Yangzhou Chen and Zhenlong Li and Yuzhen Yang}, title = {Research of Chang'an Street Coordinated Fuzzy Control Based on Traffic Flow Forecasting}, journal ={Computer Science and Information Engineering, World Congress on}, volume = {6}, year = {2009}, isbn = {978-0-7695-3507-4}, pages = {39-42}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.685}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Computer Science and Information Engineering, World Congress on TI - Research of Chang'an Street Coordinated Fuzzy Control Based on Traffic Flow Forecasting SN - 978-0-7695-3507-4 SP39 EP42 A1 - Haifeng Qian, A1 - Yangzhou Chen, A1 - Zhenlong Li, A1 - Yuzhen Yang, PY - 2009 VL - 6 JA - Computer Science and Information Engineering, World Congress on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.685
Chang’an Street is one of the most important arterial roads in Beijing, and it is one of ten congestion streets at the same time. How to solve this congestion problem become crucial after the 29th Olympic Game. This paper proposed using fuzzy coordinated control method to control this two-direction street, and three signal control parameters consisting of the cycle length, green split and offset were controlled systematically by three different fuzzy controllers which used queuing length, density and flow as inputs. In order to overcome hysteresis problem in fuzzy method, we applied traffic flow forecasting which can forecast the coming flow in 2min interval to give flow input to the fuzzy controllers. Clustering method was used to organize the history flow data which were collected by the detectors located on the arterial road, and then KNN method forecasted the coming flow in next 2min by using the history data and current detected data. Finally, a simulation test with a real-world data in Paramics software has been done to explain the advantage of the proposed method in comparison with the fixed-time method which is being used in Chang’an Street.
Citation:
Haifeng Qian, Yangzhou Chen, Zhenlong Li, Yuzhen Yang, "Research of Chang'an Street Coordinated Fuzzy Control Based on Traffic Flow Forecasting," csie, vol. 6, pp.39-42, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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