Samenvatting
Positioning Systems that measure the location of vehicles are a key enabling technology for Intelligent Transport Systems. An important issue will be the compression of position data. This paper presents the definition of the fundamental limits on the compression of position data, for both stochastic and chaotic sources. It then displays some numerical examples to show how these limits can be calculated and compares these with an existing compression scheme. Finally it is shown this work has wider implications for Intelligent Transport Systems, including traffic control algorithms. (A)