• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.68-79
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• 2008

Ground vehicle borne system which is named RoSSAV(Road Safety Survey and Analysis Vehicle) developed in KICT(Korea Institute of Construction Technology) can collect road geometric data. This system therefore is able to evaluate the road safety and analyze road deficient sections using data collected along the roads. The purpose of this study is to extract road geometric data for 3D road modeling in dangerous road section and The system should be able to quickly provide more accurate data. Various sensors(circular laser scanner, GPS, INS, CCD camera and DMI) are installed in moving object and collect road environment data. Finally, We extract 3d road geometry(center, boundary), road facility and slope using integrated multi-sensor data.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.61-68
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• 2004

In this paper, we suggest an automatic technique to obtain 3-D road information in complex urban areas using road pavement markings. This method is composed of following three main steps. The first step is extracting the pavement markings from aerial images, the second one is matching the same pavement markings in two aerial images, and the last one is obtaining the 3-D coordinates of those using EOP(exterior orientation parameters) of aerial images. Here, we focus on the first and second step because the last step can be performed by using the well hewn collinearity condition equation. We used geometric properties and spatial relationships of the pavement markings to extract the lane line markings on the images and extracted arrow lane markings additionally using template matching. And then, we obtained 3-D coordinates of the road using relational matching for the pavement markings. In order to evaluate the accuracy of extraction, we did a visual inspection and compared the result of this technique with those measured by digital photogrammetric system.