Section 8 presents the related works, and finally, Sect. 7, taking as reference the division into districts of Madrid, the capital city of Spain. This model is then applied to a real case study in Sect. ![]() Section 6 presents the whole ITS system, integrating both the CPN model and the EPL patterns. 4 and the air quality and road traffic event patterns in Sect. The city road model using CPNs is presented in Sect. Section 3 provides an overview of the CEP technology and the specific model of Petri Nets we use: CPNs. Section 2 presents the motivation of this work. The structure of the paper is as follows. Thus, the contributions of this study are:Ī combination of CEP and Colored Petri Nets (CPNs) to provide an ITS.ĭefinition of event patterns to detect high-risk situations produced by air pollutants.Ī methodology to test an ITS using the validation and verification features of CPNs.Ī realistic use case as a proof of concept, which also allows us to study the scalability of our proposal. The main aim of our proposal is to combine the use of CEP and Petri Nets to model and test ITS and, specifically, the city traffic flow, taking into account air pollution conditions. Furthermore, Petri Nets are supported by tools, which allow us to simulate and analyze the behavior of a given system in a suitable manner. ![]() Patterns are implemented by using the languages provided by CEP engines, the so-called Event Processing Languages (EPLs), and once the patterns are defined, they can be deployed in the CEP engine in question .Īdditionally, Petri Nets (PNs) are a formalism which provides mathematical rigor and a graphical representation of the model, offering a better comprehension from a visual model and a mathematical underlying model in order to obtain important results about all its possible behaviors. To meet this objective, the conditions describing the situations of interest to be detected must be specified as event patterns. CEP provides users with facilities for analyzing and correlating large volumes of data in the form of events with the aim of detecting relevant or critical situations for a particular domain in real time. The methodology we use to design ITS is Complex Event Processing (CEP) in combination with formal methods to model and test the proposed solutions . Thus, we are tackling a common problem in large cities, where traffic restrictions must be applied due to pollution. In this context, we focus on traffic control in cities, taking into account the levels of environmental pollution according to the air quality levels accepted by the international recommendations. It should be simple, but capable of capturing the information required in order to take decisions about traffic regulations. It must be flexible, using parameters that characterize the traffic flow, and be able to represent different situations and random changes in the traffic flow. In general, a desirable model must meet the following requirements: ![]() propose in, where a survey of applications of IoV and big data in autonomous vehicles is presented.Ī key component for the study and development of ITS is traffic modeling, which provides a framework to better investigate and test the state of the road in real time and accurately predict future traffic. Moreover, an increase is expected in the development of ITS, integrating concepts such as big data, thus generating the new concept of Internet of Vehicles (IoV), as Xu et al. ITS has emerged as an important element for both improving human life and the modern economy, with the main objective of optimizing road traffic by managing the capacity of the roads, improving driver safety, reducing energy consumption and improving the quality of the environment, among many others things. Numerous reports have been published in order to determine the extent of the problem, and in particular this has led to the development of a new area of study, Intelligent Transportation Systems (ITS). The increase in vehicles in road traffic is a characteristic phenomenon of today’s world, which means that related problems such as traffic accidents, pollution (air and noise), long travel times, etc., are increasing in the same way.
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