Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1140070 | Mathematics and Computers in Simulation | 2009 | 9 Pages |
Abstract
Detection and recognition of the level of congestion at an intersection is a very important problem and a valuable source of information in traffic management. Although it is just one of all the aspects that make up a traffic management system, it seems to be a crucial point for gathering information. In this paper, we present a technique based on a k-means clustering algorithm for classification, which has been already successfully used in a number of pattern recognition problems, namely: as an algorithm for face recognition problems and in a number of medical diagnosis problems and it compares very well with the state of the art techniques.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Angélica Lozano, Giuseppe Manfredi, Luciano Nieddu,