Resolution-adaptive elevation mapping based road surface preview method for intelligent vehicles

Roads serve as the primary interface between vehicles and the driving environment, significantly affecting driving quality. Accurate and efficient road surface preview is crucial for intelligent vehicles to optimize body control and ride comfort. This paper proposes a novel road surface preview method based on resolution-adaptive elevation mapping (RAEM) to construct a real-time digital elevation map (DEM). The methodology integrates point cloud segmentation and resolution-adaptive optimization modules. The new measurements are used to update the DEM through an attribute-aware update mechanism, which is guided by the segmentation results. Subsequently, a quadtree-based optimization method is applied to refine the map, enabling precise descriptions of terrain variations across varying scales. Finally, elevation profiles along the wheel trajectory are estimated to provide forward-looking preview information for intelligent vehicle control. Simulations and real vehicle experiments are conducted to validate the effectiveness of the proposed RAEM.