Modeling Temporally Variable Transportation Networks

Modeling Temporally Variable Transportation Networks -...

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Modeling Temporally Variable Transportation Networks * Zhiming Ding and Ralf Hartmut Güting Praktische Informatik IV Fernuniversität Hagen, D-58084 Hagen, Germany {zhiming.ding, rhg}@fernuni-hagen.de Abstract. In this paper, a State-Based Dynamic Transportation Network (SBDTN) model is presented, which can be used to describe the spatio- temporal aspect of temporally variable transportation networks. The basic idea of this model is to associate a temporal attribute to every node or edge of the graph system so that state changes (such as traffic jams and blockages caused by temporary constructions) and topology changes (such as insertion and dele- tion of nodes or edges) can be expressed. Since the changes of the graph system are discrete, the temporal attribute can be expressed as a series of temporal units and each temporal unit describes one single state of the node or edge during a certain period of time. The data model is given as a collection of data types and operations which can be plugged as attribute types into a DBMS to obtain a complete data model and query language. Keywords. Spatio-temporal, Database, Moving Object, Algebra. 1 Introduction The management of moving objects has been intensely investigated in recent years. However, the interaction between moving objects and the underlying transportation networks has been largely ignored. To explore this relationship by involving transpor- tation networks into the modeling of moving objects is one of the main aims of the research project “databases for moving objects”, which we participate in. Obviously, the first step along the research line is to model transportation networks themselves. The work described in this paper arose from the observation that in many moving objects database (MOD) applications, not only the moving objects are “dynamic”, but the underlying transportation networks are “dynamic” as well - new routes can be added into the network and existing routes can be blocked or become obsolete. There- fore, we need a mechanism to model the “dynamic” aspect of the transportation net- works. For simplicity, we will call temporally variable transportation networks “dy- namic transportation networks”, or simply “dynamic graphs” throughout this paper. * This research was supported by the Deutsche Forschungsgemeinschaft (DFG) research pro- ject “Databases for Moving Objects”.
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In the literature, a lot of strategies have been proposed to model the spatio-temporal aspect of geographical data. Rasinmäki in [9] has proposed a valid-period based method in which every object is associated with a pair of time stamps, one for the time of creation and one for cessation. Hamre in [6] has presented a snapshot-based model, in which the state of the world is given at regular or irregular intervals as different snapshots. Besides, Peuquet et al . in [8] have proposed an Event-oriented Spatio- Temporal Data Model (ESTDM). However, most of these methodologies are focused
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Modeling Temporally Variable Transportation Networks -...

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