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.
|Title of host publication||Proceedings of the3rd International Conference on Agents and Artificial Intelligence|
|Publication status||Published - 2011|
Stoter, A., Dalmolen, S., Drenth, E., Cornelisse, E., & Mulder, W. (2011). Real-time context aware reasoning in on-board intelligent traffic systems: An Architecture for Ontology-based Reasoning using Finite State Machines. In Proceedings of the3rd International Conference on Agents and Artificial Intelligence (pp. 637-642). SCITEPRESS. https://doi.org/10.5220/0003185506370642