Modern road systems have become complex networks with multiple layers, making three-dimensional (3D) road modeling an important task in the geoinformatic realm. Although traditional topographic maps contain explicit planimetric networks, they often lack sufficient elevation information to describe the vertical alignments ill multi-layer road systems. In this investigation, we combine data from large-scale topographic maps and airborne light detection and ranging (LIDAR) data to reconstruct 3D road models. The proposed scheme includes two steps: planimetric networking and surface modeling. In the first part, road centerlines are determined then linked up and their topologies organized using the polylines extracted from large-scale topographic maps. In the second part, a filter is utilized for the extraction of road surface points from airborne LIDAR data. The three dimensional alignment of the profiles and cross-sections is then computed. Furthermore, to improve the realism of the road models, surfaces are constrained by continuities of slope and slope difference. There are three types of data included in the test data set: single-layer, multi-layer, and interchanges between road systems. In addition to the elevation accuracy, surface continuity, slopes, and slope differences of the modeled roads are also analyzed.