Traffic Signal Control with Adaptive Fuzzy Coloured Petri Net Based on Learning Automata

S. Barzegar, M. Davoudpour, M. Meybodi, A. Sadeghian, M. Tirandazian
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引用次数: 15

Abstract

Increasing number of vehicles, as the natural consequence of population growth, has caused a significant bottle-neck in transportation network and consequently major delays at intersections. Hence, in this paper we study a hybrid adaptive model, based on combination of Coloured Petri Nets, Fuzzy Logic and Learning Automata to efficiently control traffic signals. We show that in comparison with the results found in the literature the vehicle delay time is drastically reduced using the proposed method.
基于学习自动机的自适应模糊着色Petri网交通信号控制
作为人口增长的自然结果,车辆数量的增加造成了交通网络的严重瓶颈,从而造成了十字路口的严重延误。因此,本文研究了一种基于彩色Petri网、模糊逻辑和学习自动机相结合的混合自适应模型,以有效地控制交通信号。结果表明,与文献中发现的结果相比,使用所提出的方法大大减少了车辆延迟时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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