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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IFSA Publishing, S.L.
2014-06-01
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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.
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topic |
Traffic control Distributed approach Multi- agent VISSIM Adaptive control. |
url |
http://www.sensorsportal.com/HTML/DIGEST/june_2014/Vol_173/P_2149.pdf |
work_keys_str_mv |
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1725812861931880448 |