An urban traffic controller using the MECA cognitive architecture

被引：5

作者：

Gudwin, Ricardo ^{[1
]}

Paraense, Andre ^{[1
]}

de Paula, Suelen M. ^{[1
]}

Froes, Eduardo ^{[1
]}

Gibaut, Wandemberg ^{[1
]}

Castro, Elisa ^{[1
]}

Figueiredo, Vera ^{[1
]}

Raizer, Klaus ^{[2
]}

机构：

[1] Univ Campinas UNICAMP, Campinas, SP, Brazil

[2] Ericsson Res Brazil, Indaiatuba, SP, Brazil

来源：

BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES | 2018年 / 26卷

基金：

巴西圣保罗研究基金会;

关键词：

Cognitive architecture; Dual-process theory; Dynamic subsumption; CST; REAL-TIME; CONTROL-SYSTEM; SIGNAL CONTROL; MODEL; OPTIMIZATION;

D O I：

10.1016/j.bica.2018.07.015

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a Cognitive Manager for urban traffic control, built using MECA, the Multipurpose Enhanced Cognitive Architecture, a cognitive architecture developed by our research group and implemented in the Java language. The Cognitive Manager controls a set of traffic lights in a junction of roads based on information collected from sensors installed on the many lanes feeding the junction. We tested our Junction Manager in 4 different test topologies using the SUMO traffic simulator, and with different traffic loads. The junction manager seeks to optimize the average waiting times for all the cars crossing the junction, while at the same time being able to provide preference to special cars (police cars or firefighters), called Smart Cars, and equipped with special devices that grant them special treatment during the phase allocation policies provided by the architecture. Simulation results provide evidence for an enhanced behavior while compared to fixed-time policies.

引用

页码：41 / 54

页数：14