A Multi-Agent Traffic Control Model Based on Distributed System

With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe...

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Main Authors: Qian WU, Bing LI, Keli CHEN
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2014-06-01
Series:Sensors & Transducers
Subjects:
Online Access:http://www.sensorsportal.com/HTML/DIGEST/june_2014/Vol_173/P_2149.pdf
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spelling doaj-d40f6e63d51e4049acdcc6235c03696b2020-11-24T22:09:14ZengIFSA Publishing, S.L.Sensors & Transducers2306-85151726-54792014-06-0117366067A Multi-Agent Traffic Control Model Based on Distributed SystemQian WU0Bing LI1Keli CHEN2School of Math &Computer Science, Xihua University, Chengdu, Sichuan, 610039, ChinaSchool of Math &Computer Science, Xihua University, Chengdu, Sichuan, 610039, ChinaSchool of Math &Computer Science, Xihua University, Chengdu, Sichuan, 610039, ChinaWith the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion. http://www.sensorsportal.com/HTML/DIGEST/june_2014/Vol_173/P_2149.pdfTraffic controlDistributed approachMulti- agentVISSIMAdaptive control.
collection DOAJ
language English
format Article
sources DOAJ
author Qian WU
Bing LI
Keli CHEN
spellingShingle Qian WU
Bing LI
Keli CHEN
A Multi-Agent Traffic Control Model Based on Distributed System
Sensors & Transducers
Traffic control
Distributed approach
Multi- agent
VISSIM
Adaptive control.
author_facet Qian WU
Bing LI
Keli CHEN
author_sort Qian WU
title A Multi-Agent Traffic Control Model Based on Distributed System
title_short A Multi-Agent Traffic Control Model Based on Distributed System
title_full A Multi-Agent Traffic Control Model Based on Distributed System
title_fullStr A Multi-Agent Traffic Control Model Based on Distributed System
title_full_unstemmed A Multi-Agent Traffic Control Model Based on Distributed System
title_sort multi-agent traffic control model based on distributed system
publisher IFSA Publishing, S.L.
series Sensors & Transducers
issn 2306-8515
1726-5479
publishDate 2014-06-01
description With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.
topic Traffic control
Distributed approach
Multi- agent
VISSIM
Adaptive control.
url http://www.sensorsportal.com/HTML/DIGEST/june_2014/Vol_173/P_2149.pdf
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AT kelichen amultiagenttrafficcontrolmodelbasedondistributedsystem
AT qianwu multiagenttrafficcontrolmodelbasedondistributedsystem
AT bingli multiagenttrafficcontrolmodelbasedondistributedsystem
AT kelichen multiagenttrafficcontrolmodelbasedondistributedsystem
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