System and method for classifying vehicles
AssigneeLockheed Martin Orincon Corporation
InventorsDonald K. Owen, Dale M. Klamer
Life of this patent
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Abstract
A system and method have been provided for classifying electronic signatures, obtained through the detection of a vehicle with a single loop inductive sensor, into one of a plurality of vehicle classification groups. A neural networking process is able to learn the plurality of vehicle classifications. In response to an electronic signature stimulus, the neural networking process is able to recall the classification group corresponding to the signature.
Claims31
A method for identifying a vehicle, the method comprising:
- generating electronic signatures in response to receiving data from a single sense point;
- analyzing the signatures with a neural network trained to distinguish different vehicle classifications having nonlinear decision boundaries;
- and
- classifying vehicles in response to analyzing the signatures.
A method for identifying a vehicle, the method comprising:
- supplying an electrical signal to a single loop inductive sensor located at a single sense point;
- generating a field with the electrical signal supplied to the single loop inductive sensor;
- in response to changes in the field caused by vehicles proximate the single sense point, measuring changes in the electrical signal;
- generating electronic signatures in response the measured changes in the field;
- analyzing the electronic signatures with a neural network trained to distinguish different vehicle classifications having nonlinear decision boundaries;
- and
- selecting, from a plurality of vehicle classification groups, a vehicle classification group in response to each analyzed signature.
A method for identifying a vehicle, the method comprising:
- learning a process to form boundaries between a plurality of vehicle classification groups;
- generating electronic signatures in response to receiving data from a single sense point;
- analyzing the signatures;
- and
- classifying vehicles in response to analyzing the signatures;
- wherein analyzing the signatures includes recalling the boundary formation process.
A system for classifying traffic on a highway, the system comprising:
- one or more sensors positioned at predetermined locations along a highway to generate a signal when a vehicle passes near a particular sensor;
- and
- a neural network configured to assign a classification to the vehicle in response to the signal generated by the particular sensor, the neural network being trained to distinguish different vehicle classifications having nonlinear decision boundaries.
A system for classifying traffic on a highway, the system comprising:
- a single sensor positioned at a predetermined location along a highway, having a port to supply an electronic signature generated in response to a proximal vehicle;
- and
- a neural network based classifier having an input connected to the sensor port, and an output to supply a vehicle classification from a plurality of classification groups, in response to receiving the electronic signature, the neural network based classifier being trained to distinguish different vehicle classifications having nonlinear decision boundaries.
A system for classifying traffic on a highway, the system comprising:
- a single sensor positioned at a predetermined location along a highway, having a port to supply an electronic signature generated in response to a proximal vehicle;
- and
- a classifier having an input connected to an output of the single sensor, and an output to supply a vehicle classification from a plurality of vehicle classification groups, in response to receiving the electronic signature;
- wherein the classifier learns a process to form boundaries between the plurality of vehicle classification groups, and analyzes electronic signatures by recalling the boundary formation process.
Dependencies are inferred from the claim text.