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Knowledge representation and planning for on-road driving

Published

Author(s)

Stephen B. Balakirsky, Christopher J. Scrapper Jr

Abstract

This paper presents a cost-based adaptive planning agent and knowledge layers that is operating at one level of a deliberative hierarchical planning system for autonomous road driving. At this level, the planning agent is responsible for developing fundamental driving maneuvers that allow a vehicle to travel safely amongst moving and stationary objects. This is facilitated through the application of knowledge to the graph creation process and the use of dynamic cost function within the incrementally created planning graph. This cost function varies to comply with particular road, regional, or event driven situations, and when coupled with the incremental graph expansion allows for the agent to implement hard and soft system constraints. Further discussion will be provided that details on of the expert systems that is implemented to provide the planning system with this knowledge in real-time.
Citation
Journal of Robotics and Autonomous Systems
Volume
49

Keywords

autonomous road driving, knowledge representation, Mobility, Planning, planning, RCS, Robotics & Intelligent Systems

Citation

Balakirsky, S. and Scrapper Jr, C. (2004), Knowledge representation and planning for on-road driving, Journal of Robotics and Autonomous Systems, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822607 (Accessed December 11, 2024)

Issues

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

Created July 15, 2004, Updated October 12, 2021