A Review of the Applications of Agent Technology
In Traffic and Transportation Systems
The agent computing paradigm is rapidly emerging as one of the powerful technologies for the development of largescale distributed systems to deal with the uncertainty in a dynamic environment. The domain of traffic and transportation systems is well suited for an agent-based approach because transportation systems are usually geographically distributed in dynamic changing environments. Our literature survey shows that the techniques and methods resulting from the field of agent and multiagent systems have been applied to many aspects of traffic and transportation systems, including modeling and simulation, dynamic routing and congestion management, and intelligent traffic control. This paper examines an agent-based approach and its applications in different modes of transportation, including roadway, railway, and air transportation. This paper also addresses some critical issues in developing agent-based traffic control and management systems, such as interoperability, flexibility, and extendibility. Finally, several future research directions toward the successful deployment of agent technology in traffic and transportation systems are discussed.
This paper we implemented agent applications in traffic and transportation systems. Software agents and their applications in traffic and transportation systems have been studied for over one decade. A number of agent-based applications have already been reported in the literature. These applications propose and investigate different agent-based approaches in various traffic and transportation related areas. The research results clearly demonstrate the potential of using agent technology to improve the performance of traffic and transportation systems. Most agent based applications,
The mobile agent technology has been increasingly studied, and its strengths, such as reduced network load, overcoming network latency, supporting disconnected operation, working in heterogeneous environments, and the ability to deploy new software components dynamically,
Project Implementation Module:
1. Large-scale distributed Network Module:
Agent multiple-hop mobility to build a distributed monitoring system which reconfigures itself as the status of the monitored system changes. Reconfigurability is an essential requirement if the status of the monitored system is dynamic and transient. We have seen that with distributed objects and single hop mobility we can only realize a relatively static monitoring system that may or may not be optimized on the basics of the initial status of the monitored system. As the latter evolves, the distributed monitoring logic may have to be relocated in order to maintain optimality- i.e. When MAs are used as adaptive area monitors their optimal locations depend on the status of the network which may vary considerably in highly dynamic environments.
Fig: large-scale distributed Network
2. Freeway Traffic Management Module:
Freeway agent and an arterial agent, for analysis of congestion and for generation of suitable responses. The freeway agent supports incident management operations for a freeway sub network, and the arterial agent supports operation for the adjacent arterial network. Both agents continuously receive real-time traffic data, incident detection data, and control status of the control devices on the network (signals, ramp meters, and changeable message signs). By performing an analysis of the input data and interacting with a human operator at their local traffic operation center (TOC), each agent generates suitable local control plans, which are aimed at reducing the impact of congestion at a local level. The system provides a dialog facility through a distributed user interface to allow operators at different TOCs to agree on the selection of a global solution.
3.JavaAgent Development Framework (JADE) implementation Module:
Propose MAS to help traffic operators determine the best traffic strategies for dealing with no urban roadway meteorological incidents. The agents in these two systems are implemented using the sending and receiving messages through logical filters of emission, reception, and interception. In , present their approach of dynamic modeling of a disturbance process through a multi agent-based incident model. Through this model, knowledge relative to the network structure and knowledge relative to the network dynamics are gathered to help human regulators in their monitoring tasks.
Mobile agent to move to a system that contains an object with which the agent wants to interact and then to take advantage of being in the same host or network as the object. The mobile agent technology has been increasingly studied, and its strengths, such as reduced network load, overcoming network latency, supporting disconnected operation, working in heterogeneous environments, and the ability to deploy new software components dynamically,
4. Intelligent transportation system (ITS), Multi agent system (MAS) Module:
Agent-based applications in traffic and transportation systems focus on developing MASs that consists of multiple distributed stationary agents. Mobile agent technology has not been widely applied in this area. To demonstrate the great value of mobile agents to intelligent transportation systems (ITSs), integrate mobile agent technology with MASs to enhance the flexibility and adaptability of large-scale traffic control and management systems. Different from stationary agents, mobile agents are able to migrate from one host in a network to other hosts and resume execution in remote hosts. Mobile agents can be created dynamically at runtime and dispatched to destination systems to perform tasks with most updated code and algorithms. Mobility offers great opportunity to address challenges in traffic control and management
MASs usually refers to systems that support stationary agents, and mobile agent systems support mobile agents. An agent system provides mechanisms for agent management, agent communication, and agent directory maintenance. A mobile agent system provides additional mechanisms to support the migration and execution of mobile agents. In an agent system, agencies are the major building blocks and are installed in each node of a networked system,
5. Intelligent control of traffic and transportation Module:
Developed an agent based networked traffic-management system. The agent-based control decomposes a sophisticated control algorithm into simple task-oriented agents that are distributed over a network. The ability of dynamically deploying and replacing control agents as needed allows the network to operate in a “control on demand” mode to adapt to various control scenarios. The system architecture employs a three-level hierarchical architecture. The highest level performs reasoning and planning of task sequences for control agents; the middle level dispatches and coordinates control agents; and the lowest level hosts and runs control agents. The control agents are represented by mobile agents that could migrate from remote traffic control centers to field traffic devices or from one field device to another.
PROCESSOR : PENTIUM IV 2.6 GHz
RAM : 512 MB DD RAM
MONITOR : 15” COLOR
HARD DISK : 20 GB
FLOPPY DRIVE : 1.44 MB
CDDRIVE : LG 52X
KEYBOARD : STANDARD 102 KEYS
MOUSE : 3 BUTTONS
Front End : Java, Swing , RMI
Tools Used : Eclipse 3.3
Operating System: WindowsXP/7