Title :
Multi-objective Optimization Method of Fixed-Time Signal Control of Isolated Intersections
Author :
Hu Hua ; Gao Yunfeng ; Yang Xiaoguang
Author_Institution :
Coll. of Urban Railway Transp., Shanghai Univ. of Eng. Sci., Shanghai, China
Abstract :
In this paper, we presented a multi-objective optimization model of fixed-time signal control of unsaturated intersections. The performance indices taken into consideration include total volume, average delay, average stop frequency, average queue length of vehicular traffic at signalized isolated intersections. A multi-objective genetic algorithm was given to solve the model based on Non-dominated Sorting Genetic Algorithm II (NSGAII) which can solve multi-objective optimization problems directly. Finally, an example was given to illustrate not only advantages of multi-objective optimization over single-objective or weighted combination optimization methods but also validities of different performance indices and sensitivities of the performance indices to signal control parameters. Compared with single-objective optimization method, multi-objective optimization method can sharply decrease average vehicle delay and queue length at a single intersection, and compared with weighted combination method, the multi-objective optimization method can acquire better comprehensive traffic benefits.
Keywords :
genetic algorithms; road traffic; sorting; traffic control; fixed-time signal control; isolated intersections; multiobjective genetic algorithm; multiobjective optimization method; nondominated sorting genetic algorithm II; unsaturated intersections; vehicular traffic; weighted combination optimization; multi-objective optimization; performance index; sensibility; traffic signal control; validity;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8814-8
Electronic_ISBN :
978-0-7695-4270-6
DOI :
10.1109/ICCIS.2010.316