Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing

Data-driven intelligent transportation systems (D<sup>2</sup>ITSs) have drawn significant attention lately. This work investigates a novel multi-agent-based data-driven distributed adaptive cooperative control (MA-DD-DACC) method for multi-direction queuing strength balance with changeab...

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Main Authors:	Haibo Zhang, Xiaoming Liu, Honghai Ji, Zhongsheng Hou, Lingling Fan
Format:	Article
Language:	English
Published:	MDPI AG 2019-04-01
Series:	Energies
Subjects:	D<sup>2</sup>ITS data-driven control multi-agent systems adaptive cooperative control queuing strength balance urban traffic signal timing
Online Access:	https://www.mdpi.com/1996-1073/12/7/1402

id	doaj-23f66b9db31747ffa108621fa93c886e
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spelling	doaj-23f66b9db31747ffa108621fa93c886e2020-11-24T21:44:24ZengMDPI AGEnergies1996-10732019-04-01127140210.3390/en12071402en12071402Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal TimingHaibo Zhang0Xiaoming Liu1Honghai Ji2Zhongsheng Hou3Lingling Fan4School of Electrical & Control Engineering, North China University of Technology, Beijing 100144, ChinaSchool of Electrical & Control Engineering, North China University of Technology, Beijing 100144, ChinaSchool of Electrical & Control Engineering, North China University of Technology, Beijing 100144, ChinaSchool of Automation, Qingdao University, Qingdao 266071, ChinaSchool of Automation, Beijing Information Science & Technology University, Beijing 100192, ChinaData-driven intelligent transportation systems (D<sup>2</sup>ITSs) have drawn significant attention lately. This work investigates a novel multi-agent-based data-driven distributed adaptive cooperative control (MA-DD-DACC) method for multi-direction queuing strength balance with changeable cycle in urban traffic signal timing. Compared with the conventional signal control strategies, the proposed MA-DD-DACC method combined with an online parameter learning law can be applied for traffic signal control in a distributed manner by merely utilizing the collected I/O traffic queueing length data and network topology of multi-direction signal controllers at a single intersection. A Lyapunov-based stability analysis shows that the proposed approach guarantees uniform ultimate boundedness of the distributed consensus coordinated errors of queuing strength. The numerical and experimental comparison simulations are performed on a VISSIM-VB-MATLAB joint simulation platform to verify the effectiveness of the proposed approach.https://www.mdpi.com/1996-1073/12/7/1402D<sup>2</sup>ITSdata-driven controlmulti-agent systemsadaptive cooperative controlqueuing strength balanceurban traffic signal timing
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Haibo Zhang Xiaoming Liu Honghai Ji Zhongsheng Hou Lingling Fan
spellingShingle	Haibo Zhang Xiaoming Liu Honghai Ji Zhongsheng Hou Lingling Fan Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing Energies D<sup>2</sup>ITS data-driven control multi-agent systems adaptive cooperative control queuing strength balance urban traffic signal timing
author_facet	Haibo Zhang Xiaoming Liu Honghai Ji Zhongsheng Hou Lingling Fan
author_sort	Haibo Zhang
title	Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing
title_short	Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing
title_full	Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing
title_fullStr	Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing
title_full_unstemmed	Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing
title_sort	multi-agent-based data-driven distributed adaptive cooperative control in urban traffic signal timing
publisher	MDPI AG
series	Energies
issn	1996-1073
publishDate	2019-04-01
description	Data-driven intelligent transportation systems (D<sup>2</sup>ITSs) have drawn significant attention lately. This work investigates a novel multi-agent-based data-driven distributed adaptive cooperative control (MA-DD-DACC) method for multi-direction queuing strength balance with changeable cycle in urban traffic signal timing. Compared with the conventional signal control strategies, the proposed MA-DD-DACC method combined with an online parameter learning law can be applied for traffic signal control in a distributed manner by merely utilizing the collected I/O traffic queueing length data and network topology of multi-direction signal controllers at a single intersection. A Lyapunov-based stability analysis shows that the proposed approach guarantees uniform ultimate boundedness of the distributed consensus coordinated errors of queuing strength. The numerical and experimental comparison simulations are performed on a VISSIM-VB-MATLAB joint simulation platform to verify the effectiveness of the proposed approach.
topic	D<sup>2</sup>ITS data-driven control multi-agent systems adaptive cooperative control queuing strength balance urban traffic signal timing
url	https://www.mdpi.com/1996-1073/12/7/1402
work_keys_str_mv	AT haibozhang multiagentbaseddatadrivendistributedadaptivecooperativecontrolinurbantrafficsignaltiming AT xiaomingliu multiagentbaseddatadrivendistributedadaptivecooperativecontrolinurbantrafficsignaltiming AT honghaiji multiagentbaseddatadrivendistributedadaptivecooperativecontrolinurbantrafficsignaltiming AT zhongshenghou multiagentbaseddatadrivendistributedadaptivecooperativecontrolinurbantrafficsignaltiming AT linglingfan multiagentbaseddatadrivendistributedadaptivecooperativecontrolinurbantrafficsignaltiming
_version_	1725910579216908288

Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing

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