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

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5 Author(s)
Jinyuan Li ; Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China ; Shuming Tang ; Xiqin Wang ; Wei Duan
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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.

Published in:

IEEE Transactions on Intelligent Transportation Systems  (Volume:12 ,  Issue: 2 )