DocumentCode :
2944297
Title :
Research on Traffic Flow Base on Neural Network
Author :
Li, Xiaoying ; Li, Yongzhi ; Liu, JianXin
Author_Institution :
Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
Volume :
3
fYear :
2009
fDate :
11-12 April 2009
Firstpage :
302
Lastpage :
304
Abstract :
The traffic flow according to toll vehicle type classification spends greatly and the data is inaccurate. But the traffic flow according to traffic investigation classification may obtain easily from intelligent toll station. Using neural networks ways transform charge flow into traffic investigation flow, building-up transformation model, programming in MATLAB, Obtaining error ratio of each kind of vehicle type and total error ratio. It can utilize fully the advantage of the toll-gate. Every toll-gate has the charge record to all kinds of vehicles type in the process charging. The research can cut down the cost of the traffic survey,and make full use of the traffic survey data.
Keywords :
automated highways; mathematics computing; neural nets; pattern classification; road traffic; road vehicles; traffic engineering computing; MATLAB; intelligent toll station; neural network; toll vehicle type classification; toll-gate; traffic flow; traffic investigation classification; transformation model; Communications technology; Costs; Fluid flow measurement; Intelligent systems; MATLAB; Neural networks; Radial basis function networks; Telecommunication traffic; Traffic control; Vehicles; MATLAB; error ratio; radial basis function; traffic flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
Type :
conf
DOI :
10.1109/ICMTMA.2009.296
Filename :
5203206
Link To Document :
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