Towards Building Intelligent Transportation Information Service ...

Towards Building Intelligent Transportation Information Service System on Grid* Ying Li1,2, Minglu Li1, Jiao Cao1, Xinhong Wu3, Linpeng Huang1, Ruonan Rao1, Xinhua Lin1, Changjun Jiang4, and Min-You Wu1 1

Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China 2 Computer Science and Technology School, Soochow University, Suzhou, China 3 Shanghai Urban Transportation Information Center 4 Tongji University, Shanghai, China {liying, li-ml, cao-jian}@cs.sjtu.edu.cn Abstract. Poor interpretability of current transportation systems has become an obstacle to further develop the intelligent transportation systems (ITS). Our design and implementation of intelligent transportation information service systems (ITIS) focuses on integrating heterogeneous data, transportation systems, and resources by using the grid technique. The ITIS project will refine and summarize the business model in Shanghai transportation information service system, design and set up open standards for intelligent transportation information service and simulation, develop grid supporting platform for transportation information service, integrate and fuse massive dynamic transportation data and legacy transportation systems, construct high performance computing (HPC) platform and dynamic parallel transportation simulation platform. ITIS will provide various high-level transportation information services for both citizens and government, which include optimal dynamic bus riding planning service, dynamic on-board navigation service, bus arrival-time prediction service, network optimization and simulation system, large-scale traffic-flow simulation system. Using these services will help to reduce the traffic congestion and other traffic problems, enhancing the transportation intelligence.

1 Introduction Shanghai is a municipality of eastern China at the mouth of the Yangtze River. Today, it has become the largest economic center and an important port city in China, with a land area covering 6340 km2 and a population of 16 million people. It is the host city of the 2010 Shanghai World Expo. With the rapid development of economic and the increasing number of automobiles, the problem of urban traffic congestion has become more and more serious. To solve such problems, Shanghai government puts its focus not only on road infrastructure construction, but also on transportation intelligence *

This paper is supported by ShanghaiGrid grand project of Science and Technology Commission of Shanghai Municipality (No.03DZ15027, 05DZ15005).

H.T. Shen et al. (Eds.): APWeb Workshops 2006, LNCS 3842, pp. 632 – 642, 2006. © Springer-Verlag Berlin Heidelberg 2006

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development for higher performance and better service. Recent years, the government has made tremendous effort toward solving traffic problems such as traffic congestion, air pollution, traffic guidance and et al, therefore, some transportation information management systems have been put into use or are under developing, i.e., taxi dispatch system, public transportation management system, traffic signal-control system, incident-detection system. These systems play important roles in solving the traffic problems in Shanghai, acting as subsystems of ITS. In using these systems, one problem has emerged gradually. The design of these sytems does not consider the interoperation among each other. These systems belong to different government agencies, use different technologies and the traffic data cannot be shared among them. In order to provide satisfactory service to users, transportation systems have to work together intimately. For example, to analyze and forecast traffic status, we need massive amounts of information from different systems, which includes weather conditions, digital maps, historic data, GPS systems, traffic-light information. But unfortunately, due to the management, security and technique issues, these data can not be access in real-time. And the heart of ITS lies in gathering and using system information in real time to improve real-time control [1]. Another problem is how to store, fuse, and utilize the transportation information data (TID) in these systems. TID is fundamental to ITS, as a big city, the amount of TID of Shanghai in each system are huge. Even more, different systems use different ways to store their data. It is difficult to provide a good way to interoperate among these systems. Shanghai government has already noticed the weakness of the non-interoperation of these systems. In order to provide better services to citizen, further reduce the traffic congestion, provide real-time traffic information to decision makers, it launches the ITIS project, which aims to build a platform to integrate various transportation systems as a whole. ITIS will be based on previous successful closed ShanghaiGrid [2] [3] research project, which has already developed a set of software and tools called ShanghaiGrid Operating System (SGOS) to construct information service grid (ISG). It provides sophisticated tools to implement the ITIS.

2 ShanghaiGrid and SGOS ShanghaiGrid aims to construct a metropolitan-area Information Service Grid (ISG) and establish an open standard for widespread upper-layer applications from both communities and the government. It is one of five top grand Grid projects in China. It is based on the current four major computational aggregates and networks in Shanghai, including Shanghai Supercomputing Center (SSC), and various campus supercomputer centers in Shanghai Jiao Tong University (SJTU), Tongji University (TJU) and Shanghai University (SHU). It is planned to enable the heterogeneous and distributed resources to collaborate in an information fountain and computational environment for Grid services, seamlessly and transparently. ShanghaiGrid has connected several major Grid nodes to form a 0.6 Tflops aggregate computing power and a 4 TB aggregate storage power, sophisticated information environment [3]. Shanghai government wants to use the Grid technology to construct a basic infrastructure for e-science, e-business, e-education, e-government and e-life, as the

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basic facilities of the city, similar to transportation and communication systems, water and power lines. So ShanghaiGrid as an infrastructure will fully use the existing techniques and resources to provide rich functionality of information services. Currently, several applications have been developed and put into use in the ShanghaiGrid, such as computational fluid dynamics, medicine image processing, drug discovery Grid, et al. The core of ShanghaiGrid is the SGOS, which provides middlewares, services and tools to satisfy the needs of building the ISG. Moreover, the SGOS hides the complexity of the Grid techniques for developers building Grid applications. The main components of SGOS are brief introduced as following: • ShanghaiGrid information service (SGIS) [4]. SGIS provides a standard way to register, publish, update and unregister information such as computation resources, web services, grid services and user-defined information. Different from the MDS [5] that used in GT [6], it puts focus on how to organize self-defined information such as workflow. • ECA (Event-Condition-Action)-rule-based workflow management system (EWMS) [7]. It is important for ISG to build a collaborative workflow infrastructure that allows users to describe the interactions between services and compose new workflow out of existing services to build complex applications consisting of thousands of tasks and services. However, the existing approaches do not provide enough functionality to support flexible service composition, workflow modeling and enactment. Our EWMS combines graphical process representation and ECA rules in controlling Grid workflow process, using integration adapter to facilitate the composition of all possible services, supporting hierarchical graph definition that allows workflow coursing and refinement. In this way, EWMS extends the scope of resource sharing and offers a well-layered view for complicated workflow. • Grid transaction service (GridTS) [8]. GridTS is used to ensure system consistency in Grid services while handling different types of transactions represents. The GridTS has three main components: The service discovery component is used to search for appropriate Grid services to execute specified sub-transactions, and uses a two-level registry mechanism to adopt the transient Grid services. The transaction component coordinates the atomic and coherent transactions. The latter is defined to satisfy the requirements of long-lived Grid transactions by automatically generating and executing compensation transactions. The real-time transaction component is responsible for managing transactions with a strict time restriction. The ratio of successful real-time transactions can be improved significantly by executing functional, alternative services in parallel. These components enable the GridTS to intelligently handle various transactions in the service Grid environment. • Grid monitor service (M-Grid). M-Grid is a resource monitoring and analysis system in grid. M-Grid provides an infrastructure for conducting online monitoring and performance analysis of a variety of grid resources distributed environments. • Data integration service. The Open Grid Services Architecture Data Access and Integration (OGSA-DAI) [9] provides a common interface that can be used to


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access remote databases and XML files. Currently, we use it to integration data from various systems. • Protocols adaptive file transfer (PAFTP). PAFTP is core middleware for data transport, which supports various protocols such as GridFTP, bbFTP, HTTP, FTP. User can transport files either from client software named SHGridFTP, or from browser. • Application delivery toolkit (ADT) [10]. ISG uses the Java Network Launching Protocol (JNLP) [11] client to support the ubiquitous computing. ADT is used here to develop a JNLP-enabled application (a jar file) and store it with a delivery service for mobile device to download and execute. Other services or middlewares include: Accounting Service [12], Security service, Grid portal [13], et al.

3 Architecture of ITIS 3.1 Overview The ITIS project will refine and summarize the business model in Shanghai transportation information service field, design and set up standards, assessments for Intelligent transportation information service and simulation, develop a set of protocols and standards to connect resources such as storage, computing, network to form an ITIS grid environment based on ShanghaiGrid, integrate and fuse massive dynamic transportation data and legacy transportation management systems, construct HPC platform and dynamic parallel transportation simulation platform, and provide high-level transportation information services for both citizen and government. The main reasons that ITIS needs Grid technology are based on following facts: • Integration of computational resources and various transportation systems. There exits dozens of transportation systems in Shanghai. These systems are independent, autonomic and none-interoperated. Grid can share computation, storage and other resources among these systems, cooperate among different transportation systems and provide huge computational power. Grid services provide an approach to build distributed systems that deliver application functionality as services to end-user applications or to build other services. The existing transportation systems can be wrapped with web Services or grid services, thus individual exiting systems become the building blocks, which could be easily used to develop ITIS. • Massive transportation data fusion. Transportation data are distributed, dynamic and of great volume, and could be collected by various kinds of sensors, GPS systems, video cameras, etc, from different systems. Shanghai is the biggest city in China, the production of daily transportation data is huge, which could accumulate to several PB a year. Table 1 shows the amount of GPS data in Shanghai, it reaches 17GB per day. So the massive transportation data must be fused and handled by high preference computers and networks, Grid is an ideal way.

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Y. Li et al. Table 1. The amount of GPS data in Shanghai Year 2004

2005

2006 (estimated)

Automobie type Public bus Taxi special vehicle total Public bus Taxi special vehicle total Public bus Taxi special vehicle total

count 3000 5000 1000 9000 7000 20000 3400 30400 8000 30000 4000 42000

Daily(GB) 1.690 2.816 0.563 5.069 3.943 11.265 1.915 17.123 4.506 16.898 2.253 23.657

Yearly(TB) 0.602 1.004 0.201 1.807 1.405 4.015 0.638 6.103 1.606 6.023 0.803 8.432

Fig. 1. Architecture of ITIS

• Large-scale and complex traffic-flow simulation. Simulation of traffic-flow is a key approach to study, evaluate, and better understand traffic condition in certain area. It is playing an increasingly important role as a problem solving tool for transportation system analysis. Traditionally, PC server can only simulate several intersections simultaneously, while Shanghai has about 14000 intersections and 21000 road sections, it needs huge computational power to do such simulation.


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Grid can provide the computational power by dynamically allocate the computation resources from several supercomputer centers, such as Shanghai supercomputer center, or PC clusters. On another hand, simulation of real traffic-flow demands on integration of various transportation systems to provide traffic data, which include road-sensors, traffic light systems, GPS systems et al. 3.2 Architecture As shown in Fig.1, ITIS consists of five parts. The bottom is resource layer, which contains various resources, i.e. road sensors, databases, storages. These resources are distributed and have various types. We treat the legacy transportation systems as a type of resources that can offer certain services. Infrastructure layer is on the top of the resource layer which is used to construct the grid nodes. On the top of infrastructure layer is system software layer, which provides high level services such as workflow, transaction support. Application supporting layer integrates computational resources, data resources and business logical as a whole. Upper-layer applications can use these resources transparently and easily. Application layer is the top layer of ITIS Grid. It provides various transportation information services and simulations to satisfy the needs of citizens and decision makers.

4 Sub-projects of ITIS ITIS comprises five sub-projects, including 1) Development of open protocols and standards for transportation information service applications. 2) Research on Grid supporting platform 3) Transportation resources integration. 4) Dynamic parallel transportation simulation. 5) Implementation of intelligent traffic information services. The detail information about these projects is discussed as follows. 4.1 Protocols and Standards In ITS, there exist several standards to describe traffic data, such as ISO-GDF [14], SDAL [15] and various standards developed by different governments. This became an obstacle for integrating different transportation management systems. Meanwhile, open standards and protocols must be applied to construct Grid nodes, grid services, web services and simulations to ensure the interoperation among them. These protocols and standards include: • Protocols for connecting grid nodes. • Standards for grid security. • Standards for grid metadata. Metadata service plays important roles in grid. It is heavily used by services, protocols, workflow, security, data access and data

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integration. Different systems have their own metadata. The standards give a semantic definition of the grid resources. The research topics include: how to encode the different information in a uniformed way? How to define the metadata? How to query, update, and map the metadata? Protocols for data exchanging. Protocols for service invoking. Standards for building the parallel transportation simulation platform. Standards for transportation information services.

4.2 Grid Supporting Platform The design of ITIS grid supporting system is based on the idea that grid kernel should be minimized and the functionality should be provided as plug-in services. The architecture of the platform is shown in Fig.2.

Fig. 2. Architecture of the ITIS grid supporting platform

Fig. 3. Transportation resource integration

The main researches are: • Design the micro grid kernel based on SOA • Refine the existing middlewares in SGOS and design new middlewares such as high-speed data transfer service, massive data fusion service to meet the requirements of ITIS. • Make it compatible with Web Service, OGSI and WSRF. 4.3 Transportation Resource Integration Transportation resource integration includes computational resources integration and data integration. Fig.3 shows the main research topics. The purpose of computational resources integration is to connect several supercomputers and clusters to form high performance distributed computing environment mainly for transportation simulation and real-time data processing.


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The massive dynamic multi-source transportation data integration mainly uses the Data Grid technique. For every data source, there are one or more corresponding data adapters providing data services to other grid application. By using Data flow, ITIS can handle data in an automatic way. Another aspect of data resource integration is data fusion. For example, the GPS data are collected by taxi, public bus, and special vehicle. These GPS data should be merged for further process. This kind of data fusion is heavily needed in ITIS. Data fusion needs high speed data transport, i.e. parallel data transfer, third-part data transfer, fault-detected and automatic transfer resuming. Legacy transportation management systems integration is high level business logical integration. The legacy systems export their business logical as web or Grid services by using grid supporting platform, i.e., taxi location service, parking information service, as shown in Fig.4.

Fig. 4. Legacy transportation management systems export their business logical as services

4.4 Transportation Simulation Transportation simulation as a basic problem simulating and solving tool is widely used in ITS. Due to the computational power limitation, traditional simulation tools can only simulate small-scale to middle-scale traffic condition, and usually not real-time simulation. Based on ITIS, we want to construct a transportation simulation platform for large-scale real-time dynamic traffic flow. There exist some similarities between traffic flow and fluid dynamics. In traffic dynamics, vehicle is treated as fluid flow. But in fact, traffic flow is much more complex than fluid dynamics. In Shanghai, tens of thousands of automobiles, bicycles, pedestrians each have their own trait and mobility form a complex mixed traffic flow. In order to provide accurate, real-time traffic prediction, high performance computing power is needed to satisfy the requirement of complexity problem solving. Generally speaking, a simulation process has four steps: modeling, meshing, domain decomposition and solution. The study focuses on following aspects:

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• Architecture of parallel simulation system. It defines the standards, protocols and implementation details of simulation system in Grid. • Domain decomposition for transportation simulation. Domain decomposition divides input mesh into several small meshes that are used in solution process. The strategy of decomposition will affect the efficiency of solution greatly. • Workflow based simulation scheduling. It is used to schedule the parallel solution according to the complexity of problems and the computational resources of Grid. • Agent based traffic flow simulation. Classical mathematical simulation methods are hard to simulation the interaction among different transportation entities while the interaction is important aspect of realistic environment. In real world, an entity has several properties such as reaction, autonomy, decision, etc al. We can regard entity as an agent with these properties, thus the essential of simulation will turn into the study of the behavior among a collection of autonomous agents, with each agent has its goals, decisions, rules, et al. The nature property of the distribution of the agent is suitable for parallel process. • Visualization of simulation results. Through various visualization tools, traffic information and condition can be clearly presented to decision makers. 4.5 Transportation Information Services The design and implementation of transportation information services can be divided into two catalogs: services for decision maker and services for public. Based on transportation simulation, ITIS provides several simulations as decision support systems: • • • •

Network optimization and simulation system Transportation emergency response and simulation system Large-scale traffic-flow simulation system Transportation disaster and evacuation simulation system

Different from real-time analysis of traffic data, OLAP and Data mining service will help decision makers to further study the historic data and find knowledge or useful patterns among these data, which include: • • • • •

Grid-enabled OLAP service Cluster Analysis service Association rules service Decision tree service Outlier analysis service

Traditional approach of traffic information forecast used in Shanghai is semiautomatic adjust the traffic congestion level and show it in the display at the entrance of some important roads, or forecast it through radio. Some web sites provide traffic congestion information, but this information is neither real-time nor serviceable. Based on transportation data and systems integration, one key feature of ITIS is that it can provide real-time dynamic traffic information services, which include:


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• Real-time traffic information on demand based on WebGIS. WebGIS has provided a new efficient means for traffic information publishing through browsers. With the graphic interface, traffic congestion and other information would be easily acquired by citizen. • Optimal dynamic bus riding planning service. This service calculate least-time riding schedule by giving the start and end point according to the predict modeling based on the real-time traffic data. • Dynamic on-board navigation service and dynamic navigation service for handheld device. These services provide an approach to access the traffic information by mobile devices. • Bus-arrival-time prediction service. E-display is equipped at several bus stops in Shanghai to show citizen when the next bus will arrive by using this service. It uses the real-time data from GPS, traffic light system and road sensors to predict arrival time of public bus. • Least-time travel prediction service. This service gives user a least-time travel schema according to the real-time traffic condition. Through these traffic information services, citizen could use various ways to gain the traffic condition and make their own travel plan avoiding traffic congestion. Fig.5 shows user get traffic information through PDA, fig.6 shows that user get bus-arrivaltime information from E-display at bus stop.

Fig. 5. User get traffic information through PDA

Fig. 6. E-display used to forecast the bus arrival time

5 Conclusion Transportation intelligence is one of practical approach to lessen the traffic problems by using limited money and effort compared with building road infrastructure. With the development of ITS, the non-interoperation of each systems and non-exchangeability of transportation data became an obstacle to further reduce the traffic congestion and solve other traffic problems. ITIS wants integration various transportation systems and data to provide real-time, dynamic transportation information services to avoid these problems by using Grid. Citizens and decision makers will gain better services from ITIS.

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This paper introduces the architecture of the ITIS and its main components. It uses SGOS to integrate transportation data, existing transportation systems and supercomputers to form a sophisticated Grid environment for hosting information services. Under this environment, traffic simulation systems could simulate large-scaled real-time dynamic traffic flow to analyze and forecast traffic condition. The Real-time traffic information on demand service and other information services could help citizens to be aware of the traffic condition and avoid traffic congestion. The research and development of ITIS will construct a production Grid and bring better transportation information services to the public.

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