Genetic algorithm approach to generate rules and membership functions of fuzzy traffic controller

Author

Jongwan Kim ; Byeong Man Kim ; Huh, Nam Chul

Author_Institution

Sch. of Comput. & Inf. Eng., Taegu Univ., Kyungpook, South Korea

Volume

1

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

525

Lastpage

528

Abstract

A fuzzy traffic controller with the membership functions and control rules generated by using genetic algorithm is presented for crossroad management. Conventional fuzzy traffic controllers use membership functions and control rules generated by human operators. However, this approach does not guarantee the optimal solution to design fuzzy control system. In this paper, we use genetic algorithms to automatically determine the near optimal rules and their membership functions of fuzzy traffic controllers. The effectiveness of our method was shown through simulation of multiple intersections

Keywords

control system synthesis; fuzzy control; genetic algorithms; road traffic; suboptimal control; traffic control; GA; crossroad management; fuzzy control system design; fuzzy traffic controller; genetic algorithm; membership function generation; multiple intersection simulation; near optimal rules; optimal control; rule generation; Automatic control; Automatic generation control; Fuzzy control; Genetic algorithms; Humans; Input variables; Lighting control; Timing; Traffic control; Vehicle detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2001. The 10th IEEE International Conference on

Conference_Location

Melbourne, Vic.

Print_ISBN

0-7803-7293-X

Type

conf

DOI

10.1109/FUZZ.2001.1007364

Filename

1007364