Resource integration is the only way to achieve the sharing of traffic information and infrastructure. Through integration, resource sharing can be achieved to the maximum extent, intermediate links can be reduced as much as possible, and efficiency can be improved.
The integration here mainly refers to the integration of physical resources, data resources and application systems. (As shown in Figure 1)
The Internet of Things technology provides a new reference model for the integration of traffic information resources. The Internet of Things technology is a combination of Internet technology, sensor technology, radio frequency tags, artificial intelligence, wireless data communication, etc., which is used to construct a distributed computing environment in which objects (commodities) can "communicate" with each other, realize the automatic identification of objects (commodities) and the interconnection and sharing of information. The concept of the Internet of Things will change people's long-standing concept and status quo that it is difficult to coordinate the construction of physical infrastructure and IT infrastructure, and that different types of IT infrastructure resources are difficult to integrate and share.
Based on the advantages of the Internet of Things in this regard, this paper explores a model for sharing traffic information and infrastructure resources based on the Internet of Things concepts and technologies in the agent mode.
1 Proxy Model
Agent technology originated from the research of distributed artificial intelligence in the 20th century. Agent technology emphasizes the distribution, autonomy and intelligence of software and is usually used to build large-scale distributed software systems. Software agents are high-level abstractions of modeled complex software systems, showing highly dynamic behaviors. Software agents are complex computer programs that take autonomous actions, collaborate with applications and interact with the environment to achieve given goals. The architecture model of the agent system is shown in Figure 2. The connector in the middle is the message bus of the system, and multiple agents and clients are connected to it; the controller coordinates the activities of the agents.
1.1 Entity Analysis
The scope of entities that make up the Internet of Things goes far beyond the scope of the current Internet. One important point is that the Internet of Things includes instruments and meters for various industry applications. Existing digital smart devices can theoretically be upgraded and transformed into devices in the Internet of Things. Various sensors, signal controllers, and vehicle terminals in the traffic management system, together with the central system, can become resources in the future grid system.
Table 1 shows the five types of entities in the traffic management system and their corresponding applications
The view is shown in Figure 3.
1.2 Proxy Object Model
In order to describe the operating environment of the T-Grid system in a standardized manner, we proposed the T-Grid model.
T-Grid is a universal information resource sharing platform that integrates Internet and distributed system technologies, and fully complies with the concept of Internet of Things technology. Its main goal is to establish a compatible environment so that various distributed traffic information resources can be scheduled and used with a unified interface. Under the T-Grid framework, all accessed devices (resources) have basic data processing capabilities.
The grid computing adopted by Hu Songlin et al. and Li Wei et al. is the agent architecture model. Through the analysis of the functions of each entity node in the field of traffic management system in 1.1, the following objects and corresponding relationships are further summarized (see Table 2). The mobile node (node E), field node (C) and control node (B) are described as subclasses of T-Agent.
We can see from the above description the objects that make up T-Grid:
Messaging Objects
1.2.1 Message Passing Object (MEX)
That is, the message bus determined by the connector class. The message bus is the basis of proxy grid computing. The basis of the message bus is XML-based message exchange. Through a unified message communication method and a unified message exchange format, various applications or systems are connected to the message bus to exchange data or other information with each other. The message bus structure based on message exchange effectively connects different business systems (or application systems) to the message bus, which is the basis for the business process management system to integrate different businesses. An extensible message exchange standard based on XML[6][7] can be used to define the T-Grid message specification. Figure 5 is a schematic diagram of the message bus of the T-Grid platform.
In T-Grid, from a standardization perspective, we use the instruction and data encoding standards established by the NTCIP protocol to manage these basic I/O objects.
1.2.2 Data I/O Object (T-MUX)
T-Grid divides the hardware characteristics into five basic I/O objects: display class, operation class, storage class, input class and control class. Each basic class can be completely independently controlled by its corresponding instruction set. In this way, everything from a super-large instrument to a simple sensor can become a shared target. Each front-end T-Node processes the data through the corresponding data processing algorithm. First, it filters the noise of the data and second, it performs necessary data association preprocessing on the original data. The processing of independent data source traffic data is completed here. After the data of many detectors are uploaded to the center, the central system platform will perform relevant information fusion work on this basis.
1.2.3 Data Control Object (T-Agent)
The implementation of applications in T-Grid is the result of the interaction between T-MUX and T-Agent through basic communication objects. T-Agent is a responsive, autonomous, internally driven entity. Although it is in a changing environment, it can perceive and respond to it; and T-MUX is the direct action object of T-Agent. T-Agents are connected and can be accessed directly. T-MUX is also a responsive, autonomous, internally driven entity, but T-MUX does not perceive and understand the environment by itself. It responds only after being accessed. Moreover, T-MUXs are independent and cannot directly access each other.
1.2.4 Grid Application Control (C-Agent)
We regard Node B in the traffic management system as the controller in the agent system and also the application control in T-Grid. The T-Grid model is different from the original traffic system in terms of resource integration. It should achieve two aspects of integration: T-Agent uses the NTCIP protocol to call the functions of T-MUX and collect data. On the other hand, T-Agent should be able to integrate with the new and old system-level (NodeA and NodeB) resources through the message bus. The agent generally exists in the form of a software program running on a high-performance computing device. Agent is the most critical part of T-Grid. It effectively manages and schedules various T-MUX and systems in a distributed state, and provides efficient, safe and reliable services for applications.
2. System operation mechanism
Under the concept of the Internet of Things, shared resources and collaborative network services are the essential characteristics of the grid. The goal of the functional composition and distribution of the traffic management system is to reasonably distribute the functions of the entire system in data collection, information processing and information release among five different types of nodes, and work together to complete the functions of the traffic management system. The system is divided into three levels: 1) Central information processing platform. The main function of the central intelligent agent is to realize the information integration of the entire system. It manages, coordinates and controls the entire system through the central database and method library. 2) Intelligent agent node platform. The intelligent agent node includes a data collection unit, an execution module, a processing module, an independent database, a specific method library and a coordination communication unit. 3) Existing basic traffic information collection units and traffic control units.
In the T-Grid operation mechanism model (see Figure 6), T-MUX represents the underlying object service, and Agent represents the control mechanism of the data flow. When using a function, the user does not directly face the provider of the function, but indirectly accesses it through an agent mechanism, which allows a user to call multiple service providers of the same type to work at the same time. Its advantage is that the efficiency of the system no longer depends only on the performance of a single service interface. The system has the ability to process in parallel, and its fault tolerance is significantly enhanced. When a service interface fails, the Agent can transfer the call to another interface of the same type without causing the application to crash. At the same time, both T-MUX and Agent in T-Grid have "plug and play" capabilities. T-Grid changes the original scope of resources. T-MUX is a basic I/O object, and Agent calls and processes the functions of T-MUX through basic communication objects.
For a traffic information management and control system, it can be regarded as a partial combination of several T-MUXs and an Agent; and an embedded traffic data acquisition device can be regarded as a single T-MUX object. In the T-Grid system, there is no direct data exchange between T-MUX and T-MUX, but indirect interaction through Agent. The Agent and T-MUX use basic communication protocols to exchange data. For Agent and T-MUX in the same position, in order to improve system efficiency, the system provides local autonomy, that is, T-MUX and Agent do not use communication protocols, but are directly and efficiently connected internally. At this time, the entire system is an Agent to the outside. If local autonomy is not used, this device can be regarded as a combination of several T-MUX objects and Agents, and the outside can independently access each T-MUX object and Agent. However, whether local autonomy is allowed between several Agents requires different control strategies based on actual conditions. For example, in an urban traffic control system, if a single intersection information control point is regarded as an agent, then whether the intersection signal controllers should adopt autonomy depends on the actual situation, otherwise control chaos will occur.
3 Conclusion
Traffic information sharing is one of the key areas of research in the field of intelligent transportation. Dynamic, heterogeneous and distributed are the main characteristics of traffic information systems. The integration of systems determines whether these systems can function effectively. This paper studies the technical architecture of traffic information resource integration under the Internet of Things technology.
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