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In this paper we present a new model for joint extraction of vehicles and coherent vehicle groups in airborne LIDAR point clouds collected from crowded urban areas. Firstly, the 3D point set is segmented into terrain, vehicle, roof, vegetation and clutter classes. Then the points with the corresponding class labels and intensity values are projected to the ground plane, where the optimal vehicle and traffic segment configuration is described by a Two-Level Marked Point Process (L2MPP) model of 2D rectangles. Finally, a stochastic algorithm is utilized to find the optimal configuration.