DocumentCode
2876491
Title
Traffic Signal Control with Swarm Intelligence
Author
Renfrew, David ; Yu, Xiao-Hua
Author_Institution
Dept. of Electr. Eng., California Polytech. State Univ., San Luis Obispo, CA, USA
Volume
3
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
79
Lastpage
83
Abstract
Traffic signal control is an effective way to regulate traffic flow to avoid conflict and reduce congestion. The ACO (Ant Colony Optimization) algorithm is an optimization technique based on swarm intelligence. This research investigates the application of ACO to traffic signal control problem. The decentralized, collective, stochastic, and self-organization properties of this algorithm fit well with the nature of traffic networks. Computer simulation results show that this method outperforms the conventional fully actuated control, especially under the condition of high traffic demand.
Keywords
cooperative systems; optimisation; road traffic; ant colony optimization; swarm intelligence; traffic signal control; Adaptive control; Ant colony optimization; Application software; Communication system traffic control; Computer simulation; Particle swarm optimization; Roads; Stochastic processes; Timing; Traffic control; Traffic signal control; ant colony algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.653
Filename
5366981
Link To Document