This paper presents a method of road detection and mapping using accumulated 3D data from 2D scans. The idea of 3D rolling window is introduced, and its probabilistic characteristics are studied. A cascaded road detection process is developed with region-growing and classification methods. A probabilistic framework is utilized for road mapping purposes with the detection results. The performance of detection and mapping algorithm is evaluated through experiments.