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

Published

August 1, 2002

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

Pub Type

Conferences

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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 October 11, 2025)