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

Barzegar, Siamak; Davoudpour, Maryam; Meybodi, M. R.; Sadeghian, Alireza; Tirandazian, M.

doi:10.1109/nafips.2010.5548184

Cited by 12 publications

(4 citation statements)

References 13 publications

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“…This CPN model combined elements from a series of strategies on cloud systems and resource allocation, which we developed [9][10][11][12][13]. Other fields of PN and CPN applications are mentioned below: parallel processing [14], grid computing applications [15,16], traffic control [17], analysis of safety-critical interactive Systems [18], manufacturing [19], everyday applications [20], supply chain management [21], medicine [22], industry [23], project management [24], fuzzy systems [25], and communication protocols [26,27].…”

Section: Related Workmentioning

confidence: 99%

A Novel Method for General Hierarchical System Modeling via Colored Petri Nets Based on Transition Extractions from Real Datasets

2022

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The Colored Petri net (CPN) has evolved into a complete modeling language, which is based on the object-oriented paradigm. Although this language is quite complete and can be used to accurately model a wide variety of systems, it seems that there is a lack of certain modeling rules, which can be used to generate models based on real datasets. This paper is a first attempt to incorporate sequences of real system events and translate them into sequences of Petri net transitions. Then, well-defined modeling rules control the model generation based on these transitions. The specific entities that take part in each of the real system events, as well as their attributes are also considered. The models produced using real data are structured because, in the majority of real systems, each incurring event usually affects a part of the system. Then, this effect is propagated to the entire system. Therefore, it is much easier to divide the entire model into distinct parts when real data are used and then interconnect these parts to build an entire model. This is a very important aspect when modeling very large systems. To test our approach, we used the real data from a courier company to generate its model. Our simulation results have shown that we managed to obtain quite accurate results through the model produced by the actual data.

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Section: Related Workmentioning

confidence: 99%

A Novel Method for General Hierarchical System Modeling via Colored Petri Nets Based on Transition Extractions from Real Datasets

2022

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“…The Petri Net and Colored Petri Net formalism have been widely used in the literature, in numerous fields [26,27]. Only a few are mentioned here: A few applications to mention here include pipeline-based parallel processing [28], grid computing applications [29,30] or even traffic control [31]. In this paper we use an extension of Petri Nets, the Colored Petri Nets (CPN) to extend our previous work [1], which proposed a resource allocation method, to maximize the resource utilization and distribute the system's resources in a fast and fair way.…”

Section: Our Work No No Yesmentioning

confidence: 99%

On Modeling and Simulation of Resource Allocation Policies in Cloud Computing Using Colored Petri Nets

2020

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The Petri net (PN) formalism is a suitable tool for modeling parallel systems due to its basic characteristics, such as synchronization. The extension of PN, the Colored Petri Nets (CPN) allows the incorporation of more details of the real system into the model (for example, contention for shared resources). The CPNs have been widely used in a variety of fields to produce suitable models. One of their biggest strengths is that their overall philosophy is quite similar to the philosophy of the object-oriented paradigm. In this regard, the CPN models can be used to implement simulators in a rather straightforward way. In this paper, the CPN framework is employed to implement a new resource allocation simulator, which is used to verify the performance of our previous work, where we proposed a fair resource allocation scheme with flow control and maximum utilization of the system’s resources.

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“…In the article [33] the authors proposed a hybrid LSE control system combining fuzzy logic, learning automata, and CPN (coloured Petri nets). The system was based on a learning automata (block diagram, see Figure 26), where input data changed its internal settings and chose selected output action.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Fuzzy Logic in Traffic Engineering: A Review on Signal Control

Koukol

Zajı́čková

Marek

et al. 2015

Mathematical Problems in Engineering

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Since 1965 when the fuzzy logic and fuzzy algebra were introduced by Lotfi Zadeh, the fuzzy theory successfully found its applications in the wide range of subject fields. This is mainly due to its ability to process various data, including vague or uncertain data, and provide results that are suitable for the decision making. This paper aims to provide comprehensive overview of literature on fuzzy control systems used for the management of the road traffic flow at road junctions. Several theoretical approaches from basic fuzzy models from the late 1970s to most recent combinations of real-time data with fuzzy inference system and genetic algorithms are mentioned and discussed throughout the paper. In most cases, fuzzy logic controllers provide considerable improvements in the efficiency of traffic junctions’ management.

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

Cited by 12 publications

References 13 publications

A Novel Method for General Hierarchical System Modeling via Colored Petri Nets Based on Transition Extractions from Real Datasets

A Novel Method for General Hierarchical System Modeling via Colored Petri Nets Based on Transition Extractions from Real Datasets

On Modeling and Simulation of Resource Allocation Policies in Cloud Computing Using Colored Petri Nets

Fuzzy Logic in Traffic Engineering: A Review on Signal Control

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