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Knowledge Representation for On-Road Driving

Published

Author(s)

Christopher J. Scrapper Jr, Stephen B. Balakirsky

Abstract

This paper will present a knowledge layer used by a hierarchical on-road driving planner that represents a road network as a discrete set of attributed road states. This knowledge layer facilitates the construction of a planning graph by providing simulation and prediction services to the planning system. These services allow the determination of possible spatial transitions along a road network that a vehicle may take from its current location given its current state.
Conference Dates
March 22-24, 2004
Conference Location
Palo Alto, CA, USA
Conference Title
AAAI Sprint Symposium Series on Knowledge Representation and Ontology for Autonomous Systems

Keywords

driving, Knowledge Engineering, knowledge representation, Mobility, on-road, planning, RCS, Robotics & Intelligent Systems, world model

Citation

Scrapper Jr, C. and Balakirsky, S. (2004), Knowledge Representation for On-Road Driving, AAAI Sprint Symposium Series on Knowledge Representation and Ontology for Autonomous Systems, Palo Alto, CA, USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822482 (Accessed July 24, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created March 23, 2004, Updated October 12, 2021