Based on evolutionary algorithm and cellular automata combined traffic signal control

Author

Nie, Xin ; Li, Yuanxiang ; Wei, Xiong

Author_Institution

State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China

fYear

2010

fDate

20-21 Oct. 2010

Firstpage

285

Lastpage

288

Abstract

Dynamic signal control is complex but important to develop a city intelligent transportation system, which is the best measure to solve the urban traffic jam problem all over the world. In this paper, the mathematical model of traffic signal control based on the classic BML models was introduced, then combines evolutionary algorithm with cellular automata simulation to calculate travel time and optimize signal setting plan. Iterative simulation and assignment procedure is built: Road is discredited by cellular automata. Traffic flow dynamics is represented by the combined model; Signal setting is optimized by evolutionary algorithm. The results of the simulation show that it is to be very promising and can meet the needs in the research and design of intelligent traffic system.

Keywords

cellular automata; evolutionary computation; iterative methods; road traffic; transportation; Biham, Middleton, and Levine model; assignment procedure; cellular automata simulation; city intelligent transportation system; dynamic signal control; evolutionary algorithm; intelligent traffic system; iterative simulation; mathematical model; road; traffic flow dynamics; traffic signal control; urban traffic jam problem; Adaptation model; Analytical models; Educational institutions; Numerical models; Silicon; BML model; Intelligent Transportation System; cellular automata; evolutionary algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge Acquisition and Modeling (KAM), 2010 3rd International Symposium on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-8004-3

Type

conf

DOI

10.1109/KAM.2010.5646149

Filename

5646149