Precise mobile laser scanning for urban mapping utilizing 3D aerial surveillance data

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Precise 3D map as the primary provider of static information such as road geometry and building structures plays an important role for the autonomous vehicles. Access to the map can reduce challenging environment perception problem to a more simple localization problem. Although many vehicle self-positioning techniques are relying on a priori known map, generation of the accurate 3D map is not an easy task in urban areas with tall buildings. The accuracy of the Mobile Mapping System (MMS), which is the main vehicle-based mapping technology for the autonomous driving, significantly degrades in the urban area due to the blockage and reflection of the satellite signals. In this paper, we propose a complete framework for the precision mobile mapping of deep urban areas. The proposed framework overcomes the problem of MMS in the urban areas by registering MMS point cloud to a high-precision aerial surveillance data. For this purpose, 3D road markings from the combination of high-resolution aerial image and Aerial Laser Scanning (ALS) are considered as a reference for the registration. For the 3D registration, a method based on a dynamic-size sliding window over each MMS survey is proposed to preserve the registration accuracy. Experimental results in one of the urban canyons in central Tokyo show that the proposed method can significantly reduce the error and even outperform conventional landmark updating method which is labor-intensive and costly.