DocumentCode :
2368958
Title :
GA-based parameter optimization for the ALINEA ramp metering control
Author :
Yang, Xu ; Lianyu Chu ; Recker, Will
Author_Institution :
Inst. of Transp. Studies, California Univ., Irvine, CA, USA
fYear :
2002
fDate :
2002
Firstpage :
627
Lastpage :
632
Abstract :
ALINEA, a local feedback ramp-metering strategy, has been shown to be a remarkably simple, highly efficient and easy application. This paper presents a microscopic simulation-based method to optimize the operational parameters of the algorithm, as an alternative to the difficult task of fine-tuning them in real-world testing. Four parameters, including the update cycle of the metering rate, a constant regulator, the location and desired occupancy of the downstream detector station, are considered. A genetic algorithm that searches the optimal combination of parameter values is employed. Simulation results show that the genetic algorithm is able to find a set of parameter values that can optimize the performance of the ALINEA algorithm.
Keywords :
digital simulation; genetic algorithms; road traffic; traffic control; traffic engineering computing; ALINEA; Paramics model; fine-tuning; genetic algorithm; microscopic simulation; parameter optimization; ramp-metering control; road traffic; update cycle; Calibration; Centralized control; Control systems; Feedback; Genetic algorithms; Microscopy; Optimization methods; Regulators; Testing; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems, 2002. Proceedings. The IEEE 5th International Conference on
Print_ISBN :
0-7803-7389-8
Type :
conf
DOI :
10.1109/ITSC.2002.1041291
Filename :
1041291
Link To Document :
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