近景攝影測量應用於鋪面檢測之初探

現今的鋪面檢測技術雖然多元，但各自有不同之缺點，如以人力方式檢測鋪面狀況，則檢測速度過於緩慢，且常需配合封道，不僅造成車輛回堵，對檢測人員之安全更是一大隱憂。若使用鋪面檢測車等相關設備，雖然可進行快速檢測，但檢測車之造價高昂，面對臺灣錯綜複雜的路網無法有效地調查。本研究以消費型數位相機，並使用近景攝影測量技術對鋪面進行拍攝，透過影像處理軟體重建鋪面三維模型，再搭配ArcGIS軟體可分析出道路縱斷面高程變化、辨識鋪面坑洞位置、計算坑洞體積、辨識鋪面車轍位置、計算車轍深度，以及建立鋪面糙度指標。研究結果顯示近景攝影取得之影像解析度與數值高程模型解析度可分別達到0.1(mm/pix)及0.5(mm/pix)，此解析度對於應用於分析道路高程、鋪面坑洞，甚至鋪面紋理與細小起伏皆有一定程度滿足性。另外配合使用非監督式影像群集分類法於鋪面進行分析，可成功判斷鋪面坑洞及車轍位置，並可進一步得到坑洞體積與車轍深度。本研究所建立的鋪面糙度指數小於0.25視為鋪面狀況良好；0.25至1.0視為鋪面粗糙且有損壞；1.0以上則鋪面嚴重損壞，行車困難。經本研究成果得知近景攝影測量確實有應用於鋪面檢測之潛力，若未來將此方法搭載於車輛載具上，必定能增加檢測之效率並獲取鋪面維護重要之資訊。

關鍵字

道路鋪面檢測；近景攝影測量；鋪面糙度指標

並列摘要

Pavement inspection technology nowadays is diversified. But each method has its own flaws. For example, manpower detection applied to road pavement is too slow, and often needs road closure. Not only results vehicle cause a blockage, it is a major concern for the safety of the inspectors. On the other hand, although using pavement inspection vehicles or other related equipments can quickly inspect pavement condition, the cost is expensive. Considering complex road network in Taiwan, it is hard to complete the investigation effectively by using pavement inspection vehicle. In this study, a consumer digital camera and close-range photogrammetry technology were used to construct 3D model of pavement.The elevation of road profile, the pothole volume, the rutting depth, and the road surface roughness index can be obtained through image processing software and ArcGIS analysis. The research results show that the resolution of the image and the resolution of numerical elevation model can be realized up to 0.1(mm/pix) and 0.5 (mm/pix), respectively. These resolutions can be applied to the analysis of road potholes and even textures and small fluctuations of pavement. In addition, unsupervised image clustering classification can be successfully determined the locations of potholes and ruts, volume of potholes and rutting depth.In this study, the pavement roughness index is defined at 20 cm sampling. Pavement is consider to be a good state as roughness index value is less than 0.25. Pavement is damaged as roughness index value is between 0.25 to 1.0. Pavement is seriously damaged as roughness index value is above 1.0 and it is difficult to drive. Based on the results of this study, it is known that the close-range photogrammetry does have potential for pavement inspection. When this method is combined with vehicles in the future, it will definitely improve pavement inspection efficiency and obtain the important information for road maintenance.