Growing Artificial Transportation Systems: A Rule-Based Iterative Design Process

被引：15

作者：

Li, Jinyuan ^{[1
,2
]}

Tang, Shuming ^{[3
]}

Wang, Xiqin ^{[1
]}

Duan, Wei ^{[4
]}

Wang, Fei-Yue ^{[5
]}

机构：

[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China

[2] Chinese Acad Sci, Inst Automat, Lab Complex Adapt Syst Transportat, Beijing 100190, Peoples R China

[3] Chinese Acad Sci, Shandong Univ Sci & Technol, Beijing 100190, Peoples R China

[4] Chinese Acad Sci, Natl Univ Def Technol, Beijing 100190, Peoples R China

[5] Chinese Acad Sci, Key Lab Complex Syst & Intelligence Sci, Inst Automat, Beijing 100190, Peoples R China

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2011年 / 12卷 / 02期

关键词：

Agents; artificial transportation systems (ATS); computational experiments; emergence-based observation; rules;

D O I：

10.1109/TITS.2011.2110646

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Artificial transportation systems (ATS) are an extension of traffic simulations that deal with transportation issues from the complex systems perspective in a systematic and synthetic way. A rule-based iterative ATS design process is presented in this paper, together with a prototype based on the multiagent platform-Swarm and the methods and results of computational experiments conducted on it. Both emergence-based observation and statistical analysis are used to evaluate those results. This paper demonstrates the ability of ATS to generate traffic phenomena from simple consensus rules and the possibility of designing a growing ATS with readily available multiagent tools.

引用

页码：322 / 332

页数：11

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