Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 265-272, 2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
07 Nov 2014
Development of a Multi-Sensor System for Road Condition Mapping
A. Miraliakbari1, M. Hahn1, and H.-G. Maas2 1Department of Geomatics, Computer Science and Mathematics, University of Applied Sciences Stuttgart, Schellingstraße 24, 70174 Stuttgart, Germany
2Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Helmholtzstr. 10, 01069, Dresden, Germany
Keywords: Spectrometer, Camera, Laser scanner, GPS/INS, Sensor Integration, Road Condition, Mapping Abstract. We present a concept for a vehicle based road condition mapping system using infrared spectrometers, high resolution RGB cameras and a laser scanner. Infrared spectrometry is employed to monitor the deterioration of the surface material and pavement condition, in particular by aging. High resolution RGB imaging enables automatic asphalt crack detection and provides base images for spectrometry spots. Laser scanning aims at the detection of geometrical road irregularities and pavement failures such as potholes and ruts. These three major recordings contribute to the analysis of the pavements condition. All mapping sensors are synchronised with a navigation sensor to collect geo-referenced data. The concept of road condition mapping relies on a separate analysis of the different sensor data which are related to road sections. Processing results like the percentage of the road section area related to cracks, pot holes, ruts etc. are merged to achieve an assessment for the road section. The processes for assessing deterioration from the spectrometer data, the detection of ruts from the laser data and cracks from the images are discussed in detail and outlined with some experiments.
Conference paper (PDF, 982 KB)

Citation: Miraliakbari, A., Hahn, M., and Maas, H.-G.: Development of a Multi-Sensor System for Road Condition Mapping, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 265-272, doi:10.5194/isprsarchives-XL-1-265-2014, 2014.

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