Fritz W. Cathey's research while affiliated with University of Washington Seattle and other places

The wide variety of remote sensors used in Intelligent Transportation Systems (ITS) applications (loops, probe vehicles, radar, cameras, etc.) has created a need for general methods by which data can be shared among agencies and users who own disparate computer systems. In this paper, we present a methodology that demonstrates that it is possible to create, encode, and decode a self-describing data stream using: 1) existing data description language standards; 2) parsers to enforce language compliance; 3) a simple content language that flows out of the data description language; and 4) architecture neutral encoders and decoders based on ASN.1.

We present a novel approach to estimate traffic speed using a sequence of images from an uncalibrated camera. We assert that exact calibration is not necessary to estimate speed. Instead, we use: 1) geometric relationships inherently available in the image, 2) some common-sense assumptions that reduce the problem to a one-dimensional geometry, 3) frame differencing to isolate moving edges and track vehicles between frames, and 4) parameters from the distribution of vehicle lengths to estimate speed