Towards a Semantically Enriched Local Dynamic Map

摘要

With the increasing availability of Cooperative Intelligent Transport Systems, the Local Dynamic Map (LDM) is becoming akey technology for integrating static, temporary, and dynamic information in a geographical context. However, existing ideasdo not leverage the full potential of the LDM approach, as an LDM contains streaming data and varying implicit informationwhich are not captured by current models. We aim to provide a semantically enriched LDM that applies Semantic Webtechnologies, in particular ontologies, in combination with spatial stream databases. This allows us to define an enhancedworld model, to derive model properties, to infer new information, and to offer expressive query capabilities over streams.We introduce our envisioned architecture which includes an LDM ontology, an integration and annotation framework, anda stream query answering component. We also sketch three application scenarios that illustrate the usability and benefits ofour approach, thus we provide an in-depth validation of the scenarios in an experimental prototype.