IJRIT International Journal of Research in Information Technology, Volume 2, Issue 3, March 2014, Pg: 485- 490

International Journal of Research in Information Technology (IJRIT) www.ijrit.com

ISSN 2001-5569

Cloud Computing For Agent-Based Urban Transportation System Prof. D.R.Ingle1,Mayuri Jagtap2, Tumngam Ette3, Pooja Jaiswal4 1


H.O.D, Computer Engineering Department, Mumbai University Kharghar, Maharashtra, India

Student, Computer Engineering Department, Mumbai University Thane, Maharashtra, India [email protected]


Student, Computer Engineering Department, Mumbai University Kharghar, Maharashtra, India


Student, Computer Engineering Department, Mumbai University Kharghar, Maharashtra, India

Abstract Cloud computing is a technique where the cloud stores all the necessary data which help us to handle the huge amount of storage resources and mass transportation of data effectively and efficiently. Intelligent transportation clouds also provide various services such as autonomy, mobility, decision support and the traffic management strategies. Traffic and transportation systems are the main domain which is well suited for an agent-based approach. Our Agent can be used in many aspects of traffic and transportation systems, including modeling, dynamic routing and congestion management, and intelligent traffic control. The project is developed as an Android application that can help to deal with the urban-traffic management system using intelligent traffic clouds.

Keywords:. Cloud Computing, Intelligent traffic clouds, Adaptive Platforms for Transportation Systems, Intelligent traffic cloud.

1. Introduction AGENT-BASED computing is one of the powerful technologies that can be used in traffic management system. The most appealing characteristics of agent-based traffic management system are autonomy, collaboration and mobility. To deal with dynamic traffic environments, we have make use of cloud computing that can help such system to handle the large amounts of storage resources and mass transport data effectively. Agent-based transportation systems allows collaborations of different agents to perform traffic control and management based on real-time traffic conditions. Intelligent transportation clouds provide services for making decision support and standard development environment for traffic management strategies. This paper reviews the history of the development of traffic control and

Prof. D.R.Ingle,



IJRIT International Journal of Research in Information Technology, Volume 2, Issue 3, March 2014, Pg: 485- 490

management. Urban- traffic management system is based on Agent-Based Distributed and Adaptive Platform for Transportation System (Adapts). Urban-traffic management system uses mobile agent technology. We also a prototype for urban-traffic management system using intelligent traffic clouds.

2. History Of Traffic Control And Management System

Fig-1: History of traffic management system As Figure 1 shows, five distinct phases that reflect the five stages in the deployment of the traffic control and management system. In the first phase, computers were mainly huge and costly, so mainframes were shared by many terminals. In the 1960s, a whole traffic management system shared the resources of one computer in a centralized model. In the second phase, large-scale integrated (LSI) circuits and the miniaturization of computer technology were introduced at this point, a microcomputer was powerful enough to handle and simultaneously, the same technology led to the development of the traffic signal controller (TSC). Each TSC was capable enough to handle independent computing and storage capacity . In phase three, local area networks (LANs) helped to enable resource sharing to handle the increasingly complex requirements. Urban-traffic management systems took advantage of LAN technology and developed a hierarchical model. Network communication also helped the layers to handle their own duties while cooperating with one another. In the phase four, came the Internet era, where users have been able to retrieve data from remote sites and process them locally, but this lead to the loss of precious network bandwidth. To handle this problem Agent-based computing and mobile agents were proposed. Here mobile agents only require a runtime environment for computation, it reduces communication time and costs so to improve performance. In the fifth phase, the cloud computing came into focus that is based on the Internet, cloud computing provides services such as on demand computing capacity to individuals and businesses in the form of heterogeneous and autonomous services. The advantage of cloud computing is that users do not need to understand the details of the infrastructure in the “clouds;” the only thing they need to know what resources they need and how to obtain appropriate services. 2.1 Agent-Based Distributed And Adaptive Platforms For Transportation Systems In this section we are going to discuss about the Agent-Based Distributed and Adaptive Platforms for Transportation Systems, in the short it is known as “Adapts”. The Adapts was developed in the year of 1992. Later on the technology which was called as multi agent traffic management system was developed,

Prof. D.R.Ingle,



IJRIT International Journal of Research in Information Technology, Volume 2, Issue 3, March 2014, Pg: 485- 490

but these two systems was used for negotiation and collaboration which did not full fill the requirement of urban traffic transportation system. So later in the year of 2004, the mobile agent technology was developed started attracting attention of transportation field towards itself. The characteristics of mobile agents are autonomous, mobile and adaptive. The mobile agent job is to save large amount of storage and capacity in physical control devices which helps reduce their update and replacement rates. The mobile agent will perform better than any other static agent system. In 2005 the new technology called as Adapts was developed which was proposed as an hierarchical urban traffic-management system. The Adapts contain three layers namely co-ordination , execution and organization. Adapts is also a part of Parallel Transportation Management Systems (PTMS), which can take advantage of mobile traffic strategy agents to manage a road map. In Adapts the layer called as organization layer which is the core of the system, that can perform four functions which are agent-oriented task decomposition, agent scheduling, encapsulating traffic strategy, and agent management. The organization layer consists of a management agent (MA),which consist of three databases(control strategy, typical traffic scenes, and traffic strategy agent), and also an artificial transportation system. 2.2 Intelligent Traffic Cloud In this section of intelligent traffic cloud ,we are going to describe about the importance of cloud computing which will tell about the use of cloud computing in managing the urban traffic system .Cloud can be describe as specialized distributed computing paradigm, it can also be defined as massively scalable, encapsulated as an abstract entity that delivers different levels of services to customers which are outside the cloud .The services of cloud can be dynamically configured. The cloud can also rapidly decrease in hardware cost and increase in computing power and storage capacity. Urban-traffic management systems is based on cloud computing which has two roles: service provider and customer. All the service providers such as the test bed of typical traffic scenes, ATS, traffic strategy database, and traffic strategy agent database are all veiled in the systems’ core. The clouds’ customers such as the urban-traffic management systems and traffic participants exist outside the cloud.

Fig-2: Urban-traffic management system based on cloud computing The above figure is based on urban traffic management systems which is based on cloud computing. The job of intelligent traffic clouds could provide traffic strategy agents and agent-distribution maps to the traffic management systems, traffic-strategy performance to the traffic-strategy developer, and the state of urban traffic transportation and the effect of traffic decisions to the traffic managers .The cloud also plays role like different customers’ requests for services such as storage service for traffic data and strategies, mobile traffic-strategy agents. The intelligent cloud development also played a vital role to manage the urban traffic system .Hence we can say that cloud computing play a very important role in managing the urban transportation system.

Prof. D.R.Ingle,



IJRIT International Journal of Research in Information Technology, Volume 2, Issue 3, March 2014, Pg: 485- 490

2.3. Architecture The entire scenario can be conveniently express in form of four different layers: 1.Application layer 2.Platform layer 3.Unified source layer 4.Fabric layer.

Fig-3: Intelligent traffic clouds structure Figure shows the relationship between all the four layers of the architecture. Application layer: Application layer is the top most layer in the architecture of the system, application layer contains various management task and application that run in the clouds, It also supports applications such as agent generation, agent management, testing, agent optimization, agent oriented task decomposition, and traffic decision support. The clouds provide all the services to customers through a standard interface which proves very beneficial to the customer. Platform Layer: The second layer in the architecture is the platform layer, it is made up of ATS. This layer also consists of various different types of Services which are as follows: Population synthesizer, weather simulator, Path planner, 3D game engine and so on which provide service to the upper traffic Application and agent development. Unified source Layer: This is the third layer in the system architecture ,this layer also provide various other types of services ,its job is to govern the raw hardware level resource in the fabric layer which helps to provide infrastructure as service. It also make use of virtualization technologies such as virtual machines to hide the physical characteristics of resources from users to ensure the safety of data and equipment. The other job of unified source layer is to provide access interface for the upper and reasonable distributed computing resources. The information created by this access interface solve many different other types of urban traffic problem. Fabric Layer: This is the last layer of the system architecture; it also provides many different types of services, which proves to be very important in solving urban traffic problem. It also contains many other services which are as follows: it has raw hardware level resource such as computing, storage and network resources which plays a very important role in urban traffic management system. The cloud make use of this distributed resource which cater all the peak demand of urban traffic management system which support the running of agent and ATS test beds which efficiently store traffic strategy agents and their performance.

Prof. D.R.Ingle,



IJRIT International Journal of Research in Information Technology, Volume 2, Issue 3, March 2014, Pg: 485- 490

3. Existing System According to feasibility study and including online survey, there is no any online application or android application which gives idea about traffic in cities 3.1. Proposed System Our project works requires following hardware and software. Hardware: Processor: Pentium 4, Ram: 4 GB or more, Hard disk: 16 GB or more Android device Software: WAMP Server version 2.2 Windows operating system Eclipse Android sdk Proposed system includes 3 users on primary basis. • Admin •

Traffic agent


Fig- 4: Context Level Data Flow Diagram Traffic agent will upload traffic status of city through their android application on cloud. Travelers can view the traffic status if they planning to travel from their source to destination. Admin can view the status of framework, and able to perform CRUD operations on framework. Advantages of proposed system: •

Cell phones are very convenient to carry.

Assistance about traffic at any time and at any place.

User friendly environment.

Centralized database.

Prof. D.R.Ingle,



IJRIT International Journal of Research in Information Technology, Volume 2, Issue 3, March 2014, Pg: 485- 490

Less cost

Time saving technology

4. Conclusions In this paper, we are are using the software agent and their application in traffic and transportation system. 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. In our project, the proposed system will help to improve the performance of centralized database facility. In our project of Urban traffic management systems based on cloud computing, the intelligent traffic clouds could provide traffic strategy agents and agentdistribution maps to the traffic management systems and enable traffic-strategy performance, and to improve the effect of traffic decisions. It could also deal with different user requests for various services such as storage service for traffic data, traffic map, it also proves to be time saving and cost effective.

5. Acknowledgments This paper is the result of the dedication and encouragement of many individuals. Our sincere and heartfelt appreciation goes to all of them. We wish to express our profound thanks to all those who helped us in making the whole work very easy. We are especially grateful to our project guide Prof. D.R.INGLE,H.O.D.,COMPUTER DEPARTMENT for helpful guidance ,suggestion and inspiration given by him. We would like to thanks our PROJECT CO-ORDINATOR Prof. B.W.BALKHANDE, who guided and helped us for making us to complete our project on time

6. References [1] F.-Y. Wang, “Agent-Based Control for Networked Traffic Management Systems,” IEEE Systems, vol. 20, no. 5, 2005, pp. 92–96.


[2] I. Foster et al., “Cloud Computing and Grid Computing 360-Degree Compared,” Proc. Grid Computing Environments Workshop, IEEE Press, 2008, pp. 1–10. [3] . B. Chen, H. H. Cheng, and J. Palen, “Agent-based real-time computing and its applications in traffic detection and management systems,” in Proc. ASME 24th Comput. Inf. Eng. Conf., Salt Lake City, UT, 2004, pp. 543–552. [4] B. Chen and H. H. Cheng, “A Review of the Applications of Agent Technology in Traffic and Transportation Systems,” IEEE Trans. Intelligent Transportation Systems, vol. 11, no. 2, 2010, pp. 485– 497.

Prof. D.R.Ingle,



Cloud Computing For Agent-Based Urban Transportation System - IJRIT

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