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Analysis of Intelligent Transportation Systems Using Model-Driven Simulations.

Fernández-Isabel A, Fuentes-Fernández R - Sensors (Basel) (2015)

Bottom Line: The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications.There are also guidelines to help researchers in the application of this infrastructure.A case study on advanced management of traffic lights with cameras illustrates its use.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Ingeniería del Software e Inteligencia Artificial, Facultad de Informática, Universidad Complutense de Madrid, 28040 Madrid, Spain. afernandezisabel@estumail.ucm.es.

ABSTRACT
Intelligent Transportation Systems (ITSs) integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use.

No MeSH data available.


Activity diagram of the development process with the ITSML. Concepts starting with uppercase belong to this ML.
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sensors-15-14116-f007: Activity diagram of the development process with the ITSML. Concepts starting with uppercase belong to this ML.

Mentions: Figure 7 shows the development guideline for the framework. The process has two different stages. The first one (see nodes 1–20) is specific of this work and focused on modeling with the ITSML. The definition of its metamodel (see Section 3.1) provides hints to identify the different concepts. The results of this stage are models that provide an abstract representation of the ITS and its environment. They are independent of specific target simulation platforms. The second stage takes these models as input and runs transformations to get models with the INGENIAS-ML (see activity 21), and then applies an INGENIAS development processes [27,28] to get the simulation code (see activity 22).


Analysis of Intelligent Transportation Systems Using Model-Driven Simulations.

Fernández-Isabel A, Fuentes-Fernández R - Sensors (Basel) (2015)

Activity diagram of the development process with the ITSML. Concepts starting with uppercase belong to this ML.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507665&req=5

sensors-15-14116-f007: Activity diagram of the development process with the ITSML. Concepts starting with uppercase belong to this ML.
Mentions: Figure 7 shows the development guideline for the framework. The process has two different stages. The first one (see nodes 1–20) is specific of this work and focused on modeling with the ITSML. The definition of its metamodel (see Section 3.1) provides hints to identify the different concepts. The results of this stage are models that provide an abstract representation of the ITS and its environment. They are independent of specific target simulation platforms. The second stage takes these models as input and runs transformations to get models with the INGENIAS-ML (see activity 21), and then applies an INGENIAS development processes [27,28] to get the simulation code (see activity 22).

Bottom Line: The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications.There are also guidelines to help researchers in the application of this infrastructure.A case study on advanced management of traffic lights with cameras illustrates its use.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Ingeniería del Software e Inteligencia Artificial, Facultad de Informática, Universidad Complutense de Madrid, 28040 Madrid, Spain. afernandezisabel@estumail.ucm.es.

ABSTRACT
Intelligent Transportation Systems (ITSs) integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use.

No MeSH data available.