我國現行檢測路面平整度的方式為以人工方式操作三公尺直規或高低平坦儀進行測量，測量效率僅每小時0.8公里，相當耗時、費力且效率低落，不符合台灣地狹人稠、道路分佈密集的需求。車載光達近年來引進台灣，比較起傳統人工測量有著獲取道路資訊快速、道路點雲密度極高與無人為操作誤差等優點，效率可達每小時40公里，可取代傳統人工測量之不便。依據Optech Lynx車載光達系統規格書表示其車載光達本身即有8公厘之系統誤差。此誤差在進行道路平整度調查時是超過容許值的，需以資料後處理方式降低系統誤差至6公厘以下。本研究使用航帶平差，將車載光達測量車的兩個掃描頭點雲分別進行道路萃取、資料前處理與航帶平差，並檢視不同車速、轉彎與路段性質對其航帶平差造成的影響。結果顯示在車速低於60km/hr，轉彎角度低於40度的情形的一般道路可以將原始車載光達點雲以資料後處理方式降低一半的系統誤差，獲得可供道路平整度分析之路面高程值。

The current way of analyzing pavement roughness is manually operating the 3m-straight edge or the Hi-Lo detector. The efficiency of such measurement is only 0.8 kilometer per hour. It wastes lots of time and very laborious, does not meet the requirement of Taiwan’s situation: densely populated and intensive distribution of road. Mobile LiDAR has been introduced to Taiwan recently, comparing to traditional manual measurement, it has more advantages like accessing road information quickly, high accuracy data and without human operating error. The efficiency could reach 40 kilometers per hour that could replace traditional manual measurement completely. Based on the Optech Lynx mobile LiDAR system specifications, mobile LiDAR system has 8 mm system error. This error is unacceptable for the investigation of road roughness, need to be reduced to 6mm by data post-processing. In this study, we use two laser scanner’s point cloud data of mobile LiDAR system to process road extraction, data preprocessing and strip adjustment. Then testing the effection from different speed, turning angle and nature of pavement. The results shows when measuring vehicle’s speed is less than 60km/hr, turning angle is less than 40 degrees and driving on a generally flat road, strip adjustment will reduce systematic errors by half, could export the pavement data with enough precision for analyzing pavement roughness at Taiwan.

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