A model for ontology-based scene description for context-aware driver assistance systems

Authors:
Simone Fuchs;Stefan Rass;Bernhard Lamprecht;Kyandoghere Kyamakya
Affiliations:
University of Klagenfurt;University of Klagenfurt;University of Klagenfurt;University of Klagenfurt
Venue:
Proceedings of the 1st international conference on Ambient media and systems
Year:
2008

Citing 10
Cited 2

Generic intelligent drive support

Generic intelligent drive support
Real-time eye, gaze, and face pose tracking for monitoring driver vigilance

Real-Time Imaging
A Software Engineering Framework for Context-Aware Pervasive Computing

PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
A proposal for an owl rules language

Proceedings of the 13th international conference on World Wide Web
An ontology for context-aware pervasive computing environments

The Knowledge Engineering Review
ContextUML: A UML-Based Modeling Language for Model-Driven Development of Context-Aware Web Services Development

ICMB '05 Proceedings of the International Conference on Mobile Business
Holistic Sensing and Active Displays for Intelligent Driver Support Systems

Computer
CMP: A UML Context Modeling Profile for Mobile Distributed Systems

HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
Ontology-Based Pervasive Spatial Knowledge for Car Driver Assistance

PERCOMW '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops
ScudWare: A Semantic and Adaptive Middleware Platform for Smart Vehicle Space

IEEE Transactions on Intelligent Transportation Systems

A Game-Theoretic Approach to Co-operative Context-Aware Driving with Partially Random Behavior

EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Semantic-based approach for route determination and ontologyupdating

Engineering Applications of Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Driving assistance systems (DAS) offer support in potentially dangerous situations, especially for unexperienced drivers. Co-operative systems improve their performance by sharing information with each other. One key-enabler for describing and exchanging context between intelligent vehicles, which use it for reasoning about their environment, is a common context-model. In this paper, we briefly discuss the influence of the driving context on decision-making and present an OWL-based context-model for abstract scene representation of driving scenarios. We further outline the integration of scene-descriptions with a logic-based reasoning system, based on a set of transformation rules.