Swarm intelligence for traffic light scheduling: Application to real urban areas

被引：98

作者：

Garcia-Nieto, J. ^{[1
]}

Alba, E. ^{[1
]}

Carolina Olivera, A. ^{[2
]}

机构：

[1] Univ Malaga, Dept Lenguajes & Ciencias Comp, ETSI Informat, E-29071 Malaga, Spain

[2] Univ Nacl Sur, Dept Ciencias & Ingn Comp, RA-8000 Bahia Blanca, Buenos Aires, Argentina

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2012年 / 25卷 / 02期

关键词：

Traffic light scheduling; Particle swarm optimization; SUMO microscopic simulator of urban mobility; Cycle program optimization; Realistic traffic instances; PARTICLE SWARM; OPTIMIZATION; METAHEURISTICS; FLOW;

D O I：

10.1016/j.engappai.2011.04.011

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Congestion, pollution, security, parking, noise, and many other problems derived from vehicular traffic are present every day in most cities around the world. The growing number of traffic lights that control the vehicular flow requires a complex scheduling, and hence, automatic systems are indispensable nowadays for optimally tackling this task. In this work, we propose a Swarm Intelligence approach to find successful cycle programs of traffic lights. Using a microscopic traffic simulator, the solutions obtained by our algorithm are evaluated in the context of two large and heterogeneous metropolitan areas located in the cities of Kilaga and Sevilla (in Spain). In comparison with cycle programs predefined by experts (close to real ones), our proposal obtains significant profits in terms of two main indicators: the number of vehicles that reach their destinations on time and the global trip time. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：274 / 283

页数：10

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