Three-dimensional laser ranging image reconstruction using three-line laser sensors and fuzzy methods

This paper describes the analysis and identification of road surfaces three dimensional distress characteristics by means of a three-line laser sensor. A laser-based vehicle-mounted imaging system simultaneously evaluates several conditions of road surface distress, such as ruts, cracks, and surface roughness. The three-dimensional feature extraction is done by a combination of two measuring techniques: triangulation and defocusing. A generated pattern of transverse profiles spaced by 11 cm, is used to sample the road surface. Physical differences between profiles (beam shaping, back-scattering angles, etc.) require special signal processing and analysis techniques in order to reconstruct a three dimensional image. A new fuzzy system is applied to the analysis and identification of surface cracks. The fuzzy reasoning takes into account the vagueness and the subjectivity of the classification process provided by human experts in the formulation of the identification criteria. This approach is based on a limited number of linguistic fuzzy rules given in natural language, which are extracted from the experimental description of road surface characteristics. Based on a limited number of dispersed events, the fuzzy system is able to predict the evolution of the cracking on the road surface. Theoretical aspects and experimental results are presented.