In-vehicle information management is vital in intelligent traffic systems. In this paper we motivate an architecture for ontology-based context-aware reasoning for in-vehicle information management. An ontology is essential for system standardization and communication, and ontology-based reasoning allows
context-awareness, inference and advanced reasoning capabilities. However, the amount of computational power it requires often conflicts with the computational limitations of on-board units, as well as the high demand for timeliness and safety. Our approach uses ontology-based reasoning and a finite state machine (FSM). By combining ontology and FSM, we illustrate how a heavy-weight reasoning-solution could be applied in a light-weight computational environment.
|Conference||3rd international conference on agents and artificial intelligence (ICAART 2011)|
|Period||28/01/11 → 30/01/11|
|Other||28-30 January 2011|