Abstract
How can traffic authorities deal with vehicle growth in cities with limited infrastructures? This paper presents a solution to optimize infrastructure sensors already installed in cities, focusing on the case of a laser scanner, tacking the problem in two ways: on one hand by developing sensorsable to provide more accurate and valuable traffic parameters and on the other by endowing it with “intelligence”. The detection system used is a laser scanner, which provides information in real-time about: detection (presence), flow rate, counting and vehicle classification. The classification has been made following statistical methods in five groups (5+1).