Abstract
Intelligent Speed Adaptation (ISA) is one of the key technologies for Advanced Driver Assistance Systems (ADAS), which aims to reduce car accidents by supporting drivers to comply with the speed limit. Context awareness is indispensable for autonomous cars to perceive driving environment, where the information should be represented in a machine-understandable format. Ontologies can represent knowledge in a format that machines can understand and perform human-like reasoning. In this paper, we present an ontology-based ISA system that can detect overspeed situations by accessing to the ontology-based Knowledge Base (KB). We conducted experiments on a car simulator as well as on real-world data collected with an intelligent car. Sensor data are converted into RDF stream data and we construct SPARQL queries and a C-SPARQL query to access to the Knowledge Base. Experimental results show that the ISA system can promptly detect overspeed situations by accessing to the ontology-based Knowledge Base.
Keywords
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Zhao, L., Ichise, R., Mita, S., Sasaki, Y. (2015). An Ontology-Based Intelligent Speed Adaptation System for Autonomous Cars. In: Supnithi, T., Yamaguchi, T., Pan, J., Wuwongse, V., Buranarach, M. (eds) Semantic Technology. JIST 2014. Lecture Notes in Computer Science(), vol 8943. Springer, Cham. https://doi.org/10.1007/978-3-319-15615-6_30
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DOI: https://doi.org/10.1007/978-3-319-15615-6_30
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