Intelligent traffic simulation by a multi-agent system

The Foundation for Intelligent Physical Agents (FIPA) is a non-profit organization aimed at producing standards for the interoperation of heterogeneous software agents. The FIPA Semantic Language (SL) is a communication language that uses the redefined 'content' parameter of the FIPA Agent Communication Language (ACL). The FIPA SL is also a most widely used standard language between the FIPA-based agent platforms. JADE, the famous agent platform in agent paradigms, also applies the FIPA SL. The agent platforms should follow the FIPA specifications such as FIPA ACL and FIPA SL. However there are no communication methods between the heterogeneous platforms that employ the different languages at present. For communication between the heterogeneous platforms that employ the different languages we should fix the source codes directly. Thus, we propose the FIPA SL-to-XML converting module. The converting module makes the FIPA SL-based agent platforms communicate with the XML-based web applications and platforms. We have the employed converting module in XML-based the Component -based Autonomic Layered Middleware (CALM). We also propose the starting point of the integration module that can combine the heterogeneous language-based platforms.

Agent technology is rapidly becoming one of the most promising paradigms in advanced software development, largely due to its ability to support both distributed applications and high-level programming. It should be noted, however, that agent technology is not a homogeneous research field, but rather comprises several research activities, which are only loosely connected. On the one hand, there is research focussing on mobile agents, i.e. agents migrating from one host to another. This line of research is, for example, addressed in the OMG MASIF standard (Mobile Agent System Interoperability Facility). Another field of research are intelligent agents, where the focus is not on migration but rather on communication. A standard for this research area comprising an Agent Communication Language has been developed by FIPA (Foundation for Intelligent Physical Agents). Finally, there is research on multi-agent systems in the area of Artificial Intelligence, with a particular focus on logicbased formalisations of agents’ beliefs, intentions and actions.KeywordsMobile AgentAgent TechnologyMobile ObjectCode SigningManagement FunctionalityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This article presents an approach for inter-agent communication and inter-platform agent migration based on IEEE FIPA (Foundation for Intelligent Physical Agents) Agent Communication Language (ACL) messages. The promising features of IEEE FIPA standards that support open, flexible, and interoperable agent communication and migration are discussed in the paper. Messages for agent communication and migration, platform architecture that deliver and manage these messages, and the main procedure of processing a mobile agent message are also introduced. An application example, in which a mobile agent visits multiple hosts and travels via mobile agent messages, simulates a mobile agent for remote data processing. This example shows the feasibility, simplicity, and openness of the presented approach for mobile agent migration. Using FIPA ACL messages for agent migration in FIPA compliant agent systems simplifies agent platform, reduces development effort, and easily achieves inter-platform migration through well-designed communication mechanisms provided in the agent platform.

The Agent Communication Language (ACL) proposed by the Foundation for Intelligent Physical Agents (FIPA) is the most complete attempt to create a universally accepted standard so far. Nevertheless, this standard shows some shortcomings which are probably hindering an even greater impact upon the scientific research dealing with multiagent systems. Although agreeing with the mainstream view that analyzes agent communication in terms of communicative acts, we part from FIPA’s assumptions about the semantics, as we shift the focus from affecting communicating agents’ mental states to modifying the commitments binding them to each other. We show that our commitment-based framework is powerful enough to allow for the main FIPA communicative acts and provides a semantics which overcomes some of the problems that are currently affecting the standard.KeywordsTemporal LogicMultiagent SystemAgent CommunicationMessage ExchangeIllocutionary ForceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Smart Home is a modern home that allows residents to have high-level comfort with effective use of electricity. These objectives can be achieved by applying suitable and promising optimization algorithms and techniques. This paper presents a demand side management strategy which was integrated into the existing Home Energy Management System (HEMS). Home energy management system is a Multi-Agent System (MAS) based decentralized architecture proposed by the authors. This intelligent energy management system was developed on an IEEE FIPA (Foundation for Intelligent Physical Agents) compliant multi-agent platform. This enables agents to communicate, interact and negotiate with energy sources and devices of the smart home to provide the most efficient energy usage and minimize the cost of electricity bills. This also results some peak load shaving of the power distribution system of the smart home. Simulation studies show the potential of proposed multi-agent system technique together with the demand side management strategy to provide the optimum solution for smart home energy management.

Traffic lights at crossroads help regulate the flow of vehicles so they can run smoothly and avoid congestion. One of the causes of traffic congestion is a traffic control light system that is not optimal because it still uses a fixed timer system, so the lights' duration is less efficient in its application. When the green light is on, the streets are deserted. But there is a traffic jam on another road. Therefore the concept of traffic light timing needs to be developed to get efficient timing. This study aims to create a traffic light control system that uses a PIR (Passive Infrared) motion sensor and an ultrasonic sensor based on the Arduino Mega2560 microcontroller based on the congestion level. The method used in this traffic control prototype is an experimental method of reading vehicle objects mounted with PIR sensors and ultrasonic sensors. This system can detect the movement of vehicles approaching a traffic light, measure the distance between the car and the traffic light, and set the timing of the light signal according to the level of congestion detected. This system has been tested using vehicle movement simulations brought closer to the PIR and ultrasonic sensors at different distances. The test results show the system can work properly and produce the light signal according to the detected traffic conditions. For its application to traffic lights in the future, it is feasible to help the traffic unit.

This paper presents a new modified Contract Net Protocol (CNP) for microgrid operation based on multiagent system. The CNP is a widely used protocol for interactions among distributed problem solving. The Contract Net Interaction Protocol of the Foundation for Intelligent Physical Agents (FIPA-CNIP) is a minor modification of the original CNP for multiagent system applications. In this paper, a modified CNP (MCNP) based on the FIPA-CNIP is proposed for more specialized interactions among agents for microgrid operation. A multiagent system is designed and constructed for microgrid operation. A microgrid operation based on the multiagent system is tested to check the functionality of the proposed MCNP.

This paper presents a Multi-Agent System (MAS) to model and enable an active power management in a multiple microgrids system consisting of batteries, photovoltaic and diesel micro sources in islanded or grid-connected operation. The multi-agent system was developed in JADE (Java Agent DEvelopment Framework), a Foundation for Intelligent Physical Agents (FIPA) and a compliant open source multi-agent platform. All the six case studies presented in this paper were modeled using JADE. The cases were chosen considering the real life possible scenarios, such as: discharging the battery (boost mode), energy export from the microgrid, charging the battery (buck mode), energy import from diesel generator, energy import from the grid and the system halt. However, considering that the results for the first two cases can demonstrate the performance and features of the proposed MAS, this paper focuses on the results of these cases. The results demonstrate the effectiveness of the proposed control algorithms, necessary for coordinated control and power management, and show the possibility of autonomous built-in operation of a microgrid with a multi-agent system using JADE.

The rise of the Internet and the growth of distributed computing have led to a major paradigm shift in software engineering and computer science. Until recently, the notion of computation has been variously construed as numerical calculation, as information processing, or as intelligent symbol analysis, but increasingly, it is now viewed as distributed cognition and interaction between intelligent entities [60]. This new view has major implications for the conceptualization, design, engineering and control of software systems, most profoundly expressed in the concept of systems of intelligent software agents, or multi-agent systems [99]. Agents are software entities with control over their own execution; the design of such agents, and of multi-agent systems of them, presents major research and software engineering challenges to computer scientists. One key challenge is the design of means of communication between intelligent agents. Considerable research effort has been expended on the design of artificial languages for agent communications, such as DARPA’s Knowledge Query and Manipulation Language (KQML) [33] and the Foundation for Intelligent Physical Agents’ (now IEEE FIPA) Agent Communications Language (FIPA ACL) [35]. These languages, and languages like them, have been designed to be widely applicable. As well as being a strength, this feature can also be a weakness: agents participating in conversations have too many choices of what to utter at each turn, and thus agent dialogues may endure a state-space explosion. Allowing sufficient flexibility of expression while avoiding state-space explosion had led agent communications researchers to the study of formal dialogue games; these are rule-governed interactions between two or more players (or agents), where

An automatic traffic light recognition system is proposed in this paper so that car drivers have sufficient information to make a correct decision. This in turn facilitates the construction of an ITS (Intelligent Transportation System). The proposed method can be applied to movable cameras, is adaptable to environmental variations and is proper for real‐time implementation. It consists of two phases: traffic light detection and classification. The two phases are based on color, region and border information. At the detection stage, the RGB color space is first converted into the HSI color space so as to find those regions with specific colors of traffic lights. The morphology technology is employed to remove holes and noise. Region labeling is then involved to detect candidate regions of traffic lights. At the classification stage, border detection is employed to obtain region borders which together with region colors are matching features. In this study, circle and arrow traffic lights can both be coped with. Moreover, our method is adaptable to environmental variations in numbers of lights, types of lights and time slots. Various experiments have been conducted to demonstrate the effectiveness and practicability of the proposed method.

The current traffic light system uses a lot of fixed time signals. Fixed time signals cause traffic jams in one or several lanes due to traffic congestion. On the other hand, emergency vehicles cannot get their rights to the maximum due to the density of these vehicles. This study aims to build an intelligent traffic light with a vehicle density sensor device and a smartphone application to increase the accuracy of light timing and parse traffic density. Furthermore, in an emergency, they can still overcome and accelerate the speed of passing vehicles by manually intervening with the traffic light through a smartphone application connected wirelessly to the traffic light. The intelligent traffic light is made with Arduino Bluetooth Control (ABC), Bluetooth HC-05, Arduino Mega 2560, and infrared (IR) sensor E18-D80NK. The results show that the green light setting is based on the input from the IR sensor both near sensor (NS) and far sensor (FS) work well. When NS detects a vehicle with a green light, it increases Y seconds from the default X seconds. If FS detects a vehicle with a green light, it increases by Z seconds. Settings with the ABC application can randomly turn on the green light in four lanes according to the will of the smartphone operator.

Although the number of automobiles on the road currently is more than it was a few years ago, the infrastructure of roads and traffic systems has not kept up with this expansion, which makes handling traffic challenging. This mismatch causes hence a lot of traffic congestion, crowding, and pollution. All throughout the globe, handling increasing traffic is a major challenge. Operations depend on traffic management in great part. It has to do with planning, running, and purchasing the necessary transportation services—cars, trucks, railroads, boats—that carry commodities and vehicles. Intelligent Traffic Systems (ITS) might be a fantastic approach to address these types of issues by means of modern technology. Given this, traffic control philosophy has to change to accommodate smart cities—which use computer vision techniques to run an adaptive traffic management system depending on CCTV image stream analytics. The adaptive traffic management system detects and counts vehicles accurately. In smart cities, where traffic lights must be automated based on vehicle density, this technique is particularly helpful. This study investigated intelligent traffic control, gathering and monitoring traffic data through using CCTV images. It embodies possible risks in the implementation state, benefits, challenges, as well as the future prospect of ITS.

Aims Accuracy of the Traffic Light scoring system in predicting operative difficulty and the length of the procedure in early cholecystectomy service delivery. Patients and Method We triaged patients using the Traffic Light Booking system for prioritising surgical intervention with scoring based on the severity of acute gallstone presentation. We started early gallbladder service in February 2022 using the weighted scores of patients’ demographics, BMI, comorbidities, investigation results, diagnosis and associated gallstone complications and the preoperative interventions (ERCP or cholecystostomy). The scores were stratified into traffic light system colours of green (0-3), amber (4-6) and red (>7) to predict the operative difficulty and allocated operative time for effective theatre session use. Early cholecystectomy was performed within 6 weeks of the onset of symptoms and the operative difficulty grading. Results 346 patient were operated with a median age of 51(20-96) years and Male to female ratio of 1: 2.5. The diagnoses were biliary colic (89), acute cholecystitis (172), gallstone pancreatitis (62), acute cholecystitis and pancreatitis (9) and obstructive jaundice (13). Preoperative traffic light grading was green (189), amber (130) and red (27). The median operative time 32(25-210) minutes and the mean hospital stay was 0.43(0-12) days. A direct correlation exists between the preoperative scoring and the operative difficulty (p-value = 0.0001). A direct correlation between the preoperative traffic light scoring and the length of the procedure (p-value = 0.0001) was observed. Conclusion Our Traffic Light Booking system accurately predicted the operative difficulty and the duration of the procedure.

We present a novel approach in designing and de- ploying traffic light systems by identifying key intersections of the road network. Based on techniques borrowed from Complex Network Analysis, our algorithm can be applied successively at different levels of granularity allowing a hierarchical clustering of the intersections and prioritization of the traffic lights. We illustrate our approach with a case study conducted over the city of Timisoara. from complex networks apply and influence traffic behavior. We believe that proven metrics for describing the structure of a complex network can be used successfully for finding the key intersections in any urban network. These intersections are subject to intense traffic flow and require careful regulation in order to maintain this flow. By consequence, optimal policies and strategies for deploying traffic lights are essential in an Intelligent Transportation System; this makes up for the core of this paper. The rest of the paper is organized as follows: Section 2 provides an overview of the most relevant research initiatives in the area of our study, while Section 3 consists of a short introduction in the field of Complex Network Analysis, pre- senting the key concepts and metrics used in our research. Section 4 describes the core of our investigations in the form of a novel strategy and its corresponding algorithm for identifying the key intersections of the city in order to place traffic lights. In Section 5 we present the application of this methodology over the city of Timisoara, while Section 6 presents our concluding remarks and provides some ideas for future work. II. STATE OF THE ART With the advent of modern tools and methodologies for com- puter aided urban planning and the rapid spread of (Geograph- ical Information Systems) GIS tools in the public services and administration, significant research has been carried towards finding alternative approaches in analyzing the structure of cities. The approach based on graph theory was a clear choice

In recent years popularity of private cars is getting urban traffic more and more crowded. As result traffic is becoming one of important problems in big cities in all over the world. Some of the traffic concerns are congestions and accidents which have caused a huge waste of time, property damage and environmental pollution. This research paper presents a novel intelligent traffic administration system, based on Internet of Things, which is featured by low cost, high scalability, high compatibility, easy to upgrade, to replace traditional traffic management system and the proposed system can improve road traffic tremendously. The Internet of Things is based on the Internet, network wireless sensing and detection technologies to realize the intelligent recognition on the tagged traffic object, tracking, monitoring, managing and processed automatically. The paper proposes an architecture that integrates internet of things with agent technology into a single platform where the agent technology handles effective communication and interfaces among a large number of heterogeneous highly distributed, and decentralized devices within the IoT. The architecture introduces the use of an active radio-frequency identification (RFID), wireless sensor technologies, object ad-hoc networking, and Internet-based information systems in which tagged traffic objects can be automatically represented, tracked, and queried over a network. This research presents an overview of a framework distributed traffic simulation model within NetLogo, an agent-based environment, for IoT traffic monitoring system using mobile agent technology.