摘要 由於道路類型的多樣化與複雜性，傳統二維道路輪廓圖已無法充分展現立體道路與立體交流道。因此，三維道路模型重建為空間資訊領域重要的研究方向之一，藉由整合光達資料豐富的三維資訊，與道路輪廓線精確的道路範圍，重建三維道路模型。研究內容包含兩部份：二維路網建立與三維道路模型重建。 二維路網建立部份，將道路輪廓線經由分割、連結與配對處理產生道路中心線，再由中心線產生路網位相關係。三維道路模型重建部份，由光達資料經處理後產生初始模型，再以區域路網高程平差修正道路豎曲線得到精確模型。 測試區域為新竹科學園區，光達點雲密度為每平方公尺1.73點，道路輪廓圖比例尺為千分之一。二維路網建立的正確性均高於95%，剩餘以人工編修產生完整路網。道路模塑的相對精度於一般道路區域約為0.10公尺，若為坡度道路則約為0.20公尺。 ABSTRACT Due to the diversity and complexity of the road types, traditional 2-D road maps are insufficient to represent 3-D road models when multi-layer road systems are considered. The reconstruction of 3-D road models, thus, becomes an important task in the geoinformatic area. The LIDAR data contains the height information of the road surface. The road maps record the accurate boundaries. Thus, we fuse LIDAR data and road maps to reconstruct the 3-D road models. The proposed scheme comprises two major parts: establishment of 2-D road networks and 3-D road modeling. In the first part, the roadsides in the maps are split, merged, and paired for the determination of road centerlines and the formation of networks. In the second one, the heights of the road centerlines are derived from LIDAR data to represent the road surface. Then the profiles of the 3-D roads are modified by the least squares adjustment. Finally, the patches are organized in road models in terms of ribbons. The test data covers Hsin-Chu city in the north Taiwan. The point density of LIDAR data is 1.73 points/m2. The scale of the road maps is 1:1,000. The experimental results show that the successful rate of the automatic reconstruction for 2-D road networks is above 95%. After the enhancement of the planimetric road networks by manual editing, the reconstructed 3-D road models reach a modeling accuracy of 0.10m to 0.20m.
