DocumentCode :
1895289
Title :
Platoon Dispersion Prediction Based on Transformation Kernel Estimate
Author :
Gong, Bowen ; Yang, Zhaosheng ; Lin, Ciyun
Author_Institution :
Dept. of Traffic & Transp., Univ. of Jilin, Changchun, China
Volume :
1
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
448
Lastpage :
451
Abstract :
Vehicle arrival rate is the key parameter for signal planning at intersections, which are determined by upstream intersection signal planning and platoon dispersion characteristic. With consideration of randomness and uncertainty of traffic flow arriving at intersections and the requiring for coordinated signal control between adjacent intersections, this paper presents a new method for predicting vehicle arrival rate through estimating platoon dispersion characteristic based on transform kernel estimate under unknown sample distribution function. Based on the simulation platform of VISSIM 4.20 combined with VC ++ and MATLAB mixed programming, the predicting accuracy of the method is proved. Furthermore, the comparison application in signal control system with Webster platoon dispersion calculating formula and the existing signal planning plan encourages the validity and potential of the method.
Keywords :
C++ language; mathematics computing; prediction theory; road traffic; road vehicles; traffic engineering computing; visual languages; Matlab mixed programming; VC++; VISSIM 4.20; Webster platoon dispersion; platoon dispersion prediction; signal control; signal planning; traffic flow uncertainty; transformation kernel estimate; vehicle arrival rate; Accuracy; Control systems; Distribution functions; Kernel; MATLAB; Predictive models; Traffic control; Uncertainty; Vehicles; Virtual colonoscopy; Box-Cox transformation; Vehicle arrival rate; platoon dispersion; transform kernel estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.115
Filename :
5287617
Link To Document :
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