摘要
A method for road boundary detection and tracking using laser ladar with respect to a vehicle＇ s local coordinates is proposed. It can be applied to different types of road conditions, such as roads with or without curbs, having relatively rough road surface and with obstacles on road surface. In the method, some line segments are extracted after a series of preprocessing on range data. The extracted line segments are combined and further selected. They are then united to match the road models and generate the road boundary points which are tracked by Kalman filter. Then the obtained road boundary points are transformed to build a precise vector map by least squares fitting algorithm. These fitted line segments represent road boundary vectors. The vector map is precise enough to provide ample road information such as the orientation of road, the road width and the passable road region. Finally, extensive experiments conducted in urban and semi-urban environment demonstrate the robustness, effectiveness and viability of the proposed method.
A method for road boundary detection and tracking using laser ladar with respect to a vehicle＇ s local coordinates is proposed. It can be applied to different types of road conditions, such as roads with or without curbs, having relatively rough road surface and with obstacles on road surface. In the method, some line segments are extracted after a series of preprocessing on range data. The extracted line segments are combined and further selected. They are then united to match the road models and generate the road boundary points which are tracked by Kalman filter. Then the obtained road boundary points are transformed to build a precise vector map by least squares fitting algorithm. These fitted line segments represent road boundary vectors. The vector map is precise enough to provide ample road information such as the orientation of road, the road width and the passable road region. Finally, extensive experiments conducted in urban and semi-urban environment demonstrate the robustness, effectiveness and viability of the proposed method.
基金
Supported by the National Natural Science Foundation of China (61174178)
