Vehicle Localization System in Urban Scenario with Three-Dimensional City Map

Abstract

Accurate self-localization is a critical problem in the autonomous driving system. In this paper, we proposed a localization system which integrates stereo camera and three-dimensional city model containing building and road mark information. The stereo camera generates visual odometry, reconstructs building scene and detects road mark. We aligned building scene with Normal Distribution Transform (NDT) map to get the absolute localization. Road mark detection result helps to rectify the inner lane positioning with road map. The experiment conducted in Hitotsubashi, Tokyo indicates that the lateral and heading error of visual odometry can be corrected and sub-meter accuracy localization is achieved.