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Linking Sensed Images to an Ontology of Obstacles to Aid in Autonomous Driving

Published

Author(s)

Craig I. Schlenoff

Abstract

In this paper, we discuss the importance of recognizing and representing both stationary and moving obstacles for the purpose of autonomous driving as well as linking these representation to an ontology of obstacles to aid in deducing additional information about them. With the ability to access additional information about a sensed obstacle, an autonomous vehicle can better forecast where that obstacle can and can not be at a future time, and therefore be able to better plan its path to avoid collision with that obstacle. This paper describes work just recently-begun at the National Institute of Standards and Technology in developing and incorporating an ontology of driving obstacles into the control of an autonomous vehicle to aid in path planning and obstacle avoidance.
Proceedings Title
Proceedings of the AAAI-2002 Workshop on Ontologies and the Semantic Web
Conference Dates
July 28-August 1, 2002
Conference Location
Edmonton, CA
Conference Title
Ontologies and the Semantic Web

Keywords

autonomous driving, moving object, obstacle avoidance, ontologies, symbolic representation

Citation

Schlenoff, C. (2002), Linking Sensed Images to an Ontology of Obstacles to Aid in Autonomous Driving, Proceedings of the AAAI-2002 Workshop on Ontologies and the Semantic Web, Edmonton, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=821735 (Accessed June 12, 2024)

Issues

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

Created August 1, 2002, Updated February 17, 2017