A Collaborative Agent-Based Traffic Signal System For Highly Dynamic Traffic Conditions

被引：0

作者：

Torabi, Behnam ^{[1
]}

Wenkstern, Rym Z. ^{[1
]}

Saylor, Robert ^{[2
]}

机构：

[1] Univ Texas Dallas, Dept Comp Sci, Richardson, TX 75080 USA

[2] City Richardsons Div Traff & Transportat, Richardson, TX 75080 USA

来源：

2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC) | 2018年

关键词：

NETWORKS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper we present DALI, a distributed, collaborative multi-agent Traffic Signal Timing system (TST) for highly dynamic traffic conditions. In DALI, intersection controllers are augmented with software agents which collaboratively adapt signal timings by considering the feedback of all controller agents that may be affected by a change. The model is based on a real-world TST and is intended to be deployed with minimal changes to the infrastructure. DALI has been validated on a simulated model of the City of Richardson, Texas, comprising 128 signalized intersections. The experimental results show that it outperforms the conventional traffic operation modes as well as an RL-based TST in highly dynamic scenarios.

引用

页码：626 / 633

页数：8

共 26 条

[1] Holonic multi-agent system for traffic signals control [J].

Abdoos, Monireh ;

Mozayani, Nasser ;

Bazzan, Ana L. C. .

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2013, 26 (5-6) :1575-1587

[2] Reinforcement learning for True Adaptive traffic signal control [J].

Abdulhai, B ;

Pringle, R ;

Karakoulas, GJ .

JOURNAL OF TRANSPORTATION ENGINEERING, 2003, 129 (03) :278-285

[3] Intelligent cuckoo search optimized traffic signal controllers for multi-intersection network [J].

Araghi, Sahar ;

Khosravi, Abbas ;

Creighton, Douglas .

EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (09) :4422-4431

[4] A distributed approach for coordination of traffic signal agents [J].

Bazzan, ALC .

AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2005, 10 (02) :131-164

[5] A review on agent-based technology for traffic and transportation [J].

Bazzan, Ana L. C. ;

Klugl, Franziska .

KNOWLEDGE ENGINEERING REVIEW, 2014, 29 (03) :375-403

[6] Learning in groups of traffic signals [J].

Bazzan, Ana L. C. ;

de Oliveira, Denise ;

da Silva, Bruno C. .

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2010, 23 (04) :560-568

[7] Type-2 fuzzy multi-intersection traffic signal control with differential evolution optimization [J].

Bi, Yunrui ;

Srinivasan, Dipti ;

Lu, Xiaobo ;

Sun, Zhe ;

Zeng, Weili .

EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (16) :7338-7349

[8]

Chao KH, 2008, LECT NOTES ARTIF INT, V5177, P17, DOI 10.1007/978-3-540-85563-7_8

[9] CoSIGN: A parallel algorithm for coordinated traffic signal control [J].

Cheng, Shih-Fen ;

Epelman, Marina A. ;

Smith, Robert L. .

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2006, 7 (04) :551-564

[10] A novel approach for dynamic traffic lights management based on Wireless Sensor Networks and multiple fuzzy logic controllers [J].

Collotta, Mario ;

Lo Bello, Lucia ;

Pau, Giovanni .

EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (13) :5403-5415

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