Hybrid Petri net model of a traffic intersection in an urban network

Control in urban traffic networks constitutes an important and challenging research topic nowadays. In the literature, a lot of work can be found devoted to improving the performance of the traffic flow in such systems, by means of controlling the red-to-green switching times of traffic signals. Different techniques have been proposed and commercially implemented, ranging from heuristic methods to model-based optimization. However, given the complexity of the dynamics and the scale of urban traffic networks, there is still a lot of scope for improvement. In this work, a new hybrid model for the traffic behavior at an intersection is introduced. It captures important aspects of the flow dynamics in urban networks. It is shown how this model can be used in order to obtain control strategies that improve the flow of traffic at intersections, leading to the future possibility of controlling several connected intersections in a distributed way

Combining SysML and Timed Coloured Petri Nets for Designing Smart City Applications

A smart city is an urban centre that integrates a variety of solutions to improve infrastructure performance and achieve sustainable urban development. Urban roads are a crucial infrastructure highly demanded by citizens and organisations interested in their deployment, performance, and safety. Urban traffic signal control is an important and challenging real-world problem that aims to monitor and improve traffic congestion. The deployment of traffic signals for vehicles or pedestrians at an intersection is a complex activity that changes constantly, so it is necessary to establish rules to control the flow of vehicles and pedestrians. Thus, this article describes the joint use of the SmartCitySysML, a profile proposed by the authors, with TCPN (Timed Coloured Petri Nets) to refine and formally model SysML diagrams specifying the internal behaviour, and then verify the developed model to prove behavioural properties of an urban traffic signal control system

Middleware control systems design and analysis using message interpreted Petri Nets (MIPN)

Many distributed frameworks use a message-oriented middleware to interchange information among several independent distributed modules. Those modules make up complex systems implementing basic actions and reporting events about their state. This paper introduces the Message Interpreted Petri Net (MIPN) model to design, analyze, and execute the central control of these middleware systems. The MIPN is a new Petri net extension that adds message-based high-level information communications and hierarchic capabilities. It also contributes to the definition and study of new properties such as terminability for the hierarchy-wide analysis of a system. Special attention is given to the analyzability of the model. Useful relations between the individual properties of each MIPN and the global properties of a hierarchic MIPNs system are extracted through a mathematical analysis of the model. The goal is to analyze each net separately and then build up the properties of the whole system. This results in a great aid for the programmer and optimizes the development process. This paper also shows the actual integration of this new MIPN model in different robot control frameworks to design, analyze, execute, monitor, log, and debug tasks in such heterogeneous systems. Finally, some applications created with this framework in the fields of robotics, autonomous vehicles, and logistics are also presentedMinisterio de Ciencia e Innovación | Ref. EXP00139978CER-2021100

Modeling, Analysis, and Simulation of Two Connected Intersections Using Discrete and Hybrid Petri Nets

Indiana University-Purdue University Indianapolis (IUPUI)In recent decades, Petri nets (PNs) have been used to model traffic networks for different purposes, such as signal phase control, routing, and traffic flow estimation, etc. Because of the complex nature of traffic networks where both discrete and continuous dynamics come into play, the Hybrid Petri net (HPN) model becomes an important tool for the modeling and analysis of traffic networks. In Chapter 1 a brief historical summery about traffic systems control and then related work is mentioned followed by the major contributions in this research. Chapter 2 provides a theoretical background on Petri nets. In Chapter 3, we develop a HPN model for a single signalized intersection first, then we extend this model to study a simple traffic network that consists of two successive intersections. Time delays between different points of network are also considered in order to make the model suitable for analysis and simulation. In addition to HPN models, we also consider discrete Petri nets where their modeling simplicity enables the characterization of the occurrences of all events in the system. This discrete PN is particularly useful to give a higher-level representation of the traffic network and study its event occurrences and correlations. In Chapter 4, we build a discrete PN model to represent a traffic network with two successive intersections. However, we find that the model leads to unbounded places which cannot accurately reflect the dynamics of the traffic in terms of event occurrences. Hence, we introduce the Modified Binary Petri nets (MBPN) to overcome the limitation and resolve the confliction problem when we design our controllers. This MBPN model is a powerful tool and can be useful for the modeling and analysis of many other applications in traffic networks. Chapter 5 gives a summary for each chapter, provides conclusion and discusses future work for both discrete and hybrid Petri nets

A SysML profile for smart city applications

A smart city is an urban center that integrates a variety of solutions to enhance infrastructure performance and achieve sustainable urban development. Urban roads are a critical infrastructure highly demanded by citizens and organizations interested in their deployment, performance, and safety. Urban traffic signal control is a major and challenging problem in the real world, which aims to monitor and enhance traffic congestion. Therefore, the deployment of traffic signals for vehicles or pedestrians at a junction is a complex activity, as it is necessary to establish rules to control the flow of vehicles and pedestrians. Also, traffic flow at intersections changes constantly, depending on weather conditions, day of the week, and period of the year, as well as road works and accidents that further influence complexity and performance. This thesis first describes SmartCitySysML, a proposed profile that adapts SysML with special elements that are specific to smart cities. In addition, an extension of the SmartCitySysML profile to the design of the dimensions of smart cities is proposed. Finally, integration of models is performed, that is, the integration of the SmartCitySysML profile with Petri Net to separately model the basic architectural elements (sensor, controller, and actuator) of an urban traffic control system as sub-models to describe the behavior of each element, and the integration of the SmartCitySysML profile with Timed Coloured Petri Nets (TCPN) for modeling, simulation, and verification of properties of an urban traffic signal control system. CPN tools allow the evaluation of the model behavior through simulation and property verification and perform a simulation-based performance. Model simulation allows observing the behavior of the system under conditions that would be difficult to organize in a truly controlled environment. Consequently, a preliminary evaluation can be performed in the early stages of system development, significantly reducing costs of improvements and increasing quality of the final product.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESUma cidade inteligente é um centro urbano que integra uma variedade de soluções para melhorar o desempenho da infraestrutura e alcançar um desenvolvimento urbano sustentável. As estradas urbanas são uma infraestrutura crucial altamente exigida pelos cidadãos e organizações interessadas em sua implantação, desempenho e segurança. O controle de sinais de trânsito urbano é um problema importante e desafiador no mundo real, que visa monitorar e melhorar o congestionamento de trânsito. Portanto, a implantação de semáforos para veículos ou pedestres em um cruzamento é uma atividade complexa, pois é necessário estabelecer regras para controlar o fluxo de veículos e pedestres. O fluxo de tráfego no cruzamento muda constantemente, dependendo das condições climáticas, dia da semana e período do ano, assim como obras e acidentes rodoviários que influenciam ainda mais a complexidade e o desempenho. Esta dissertação descreve primeiro o SmartCitySysML, um perfil proposto que adapta a SysML com elementos especiais que são específicos para cidades inteligentes. Depois, é elaborada uma extensão do perfil SmartCitySysML para o design das dimensões das cidades inteligentes. Em seguida, é realizada a integração de modelos, ou seja, a integração do perfil SmartCitySysML com Redes de Petri para modelar separadamente os elementos arquiteturais básicos (sensor, controlador e atuador) de um sistema de controle de tráfego urbano como sub-modelos para demonstrar o comportamento de cada elemento, e a integração do perfil SmartCitySysML com Redes de Petri Colorida Temporizada (TCPN) para modelagem, simulação e verificação de propriedades do sistema de controle de sinais de trânsito urbano. As ferramentas CPN permitem avaliar o comportamento do modelo por meio de simulação e verificação de propriedades e realizar um desempenho baseado em simulação. A simulação de modelos permite observar o comportamento do sistema sob condições que seriam difíceis de organizar em um ambiente realmente controlado. Consequentemente, uma avaliação preliminar pode ser realizada nos estágios iniciais de desenvolvimento do sistema, reduzindo significativamente os custos de melhorias e aumentando a qualidade do produto final.São Cristóvão, S

An Intelligent Transportation System to control air pollution and road traffic in cities ntegrating CEP and Colored Petri Nets

Air pollution generated by road traffic in large cities is a great concern in today’s society since pollution has an important impact on human health, even causing premature deaths. To address the problem, this paper presents an Intelligent Transportation System model based on Complex Event Processing technology and Colored Petri Nets (CPNs). It takes into consideration the levels of environmental pollution and road traffic, according to the air quality levels accepted by the international recommendations as well as the handbook emission factors for road transport methodology. This proposal, therefore, tackles a common problem in today’s large cities, where traffic restrictions must be applied due to environmental pollution. CPNs are used in this work as a tool to make decisions about traffic regulations, so as to reduce pollution levels