Determination of vehicle behavior based on distributed sensor network data

David Friedlander, Shashi Phoha, Richard Brooks

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Vehicle tracking can be done automatically based on data from a distributed sensor network. The determination of vehicle behavior must currently be done by humans. Behaviors of interest include searching, attacking and retreating. The purpose of this paper is to show an approach for the automatic interpretation of vehicle behaviors based on data from distributed sensor networks. The continuous dynamics of the sensor network are converted into symbolic dynamics by dividing its phase space into hypercubes and associating a symbol with each region. When the phase-space trajectory enters a region, its corresponding symbol is emitted into a symbol stream. Substrings from the stream are interpreted as a formal language defining the behavior of the vehicle. The formal language from the sensor network is compared to the languages associated with known behaviors of interest. Techniques for performing quantitative comparisons between formal languages are presented. The abstraction process is shown to be powerful enough to distinguish two simple behaviors of a robot based on data from a pressure sensitive floor.

Original languageEnglish (US)
Pages (from-to)155-163
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5205
DOIs
StatePublished - 2003
EventAdvanced Signal Processing Algorithms, Architectures, and Implementations - San Diego, USA, United States
Duration: Aug 6 2003Aug 8 2003

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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