Autoscope系統與現行方法用於車流資料調查處理分析之比較研究－－以台北市建國高架快速道路為例

Comparing Autoscope Image Processing System with Present Method on Traffic Data Collection and Analysis - A Case Study on Chien-Kuo Expressway in Taipei

為改善現行人工調查方式耗費人、時之缺失，並加速推動臺灣地區公路容量手冊修訂進度，於車流特性基本資料之蒐集作業上，確有朝向自動化方面發展之必要。為此，交通部運輸研究所特將所引進之Autoscope系統所得之資料，與現行作業方式所得資料加以比較分析，期能進一步了解應用Autoscope系統之穩定性與精確度等特性資料。本研究在台北市建國南北高架快速道路基本路段(不受上、下臣道或線形彎曲之影響)蒐集各項車流特性資料，做為比較分析之基礎。研究結果顯示，以Autoscope系統對各項車流特性進行判讀時，精確度約在74%~95%間，其中以車流量之判讀結果精確度最高，其次為空間平均速率，佔有率則較差。

Manual trajfic data collection is an expensive and time-consuming task. There is an urgent need to automate data collection to support model development and planning and management decisions. Autoscope Image Processing System has the potential to satify this need. The objective of this study is to access the performance of Autoscope in estimating average travel speed, jlow rate and occupancy. It is found that accurate estimates generated by Autoscoperangefrom 74% to to 95%. Autoscope is fairly good at estimating jlow rate whereas not as good at estimating occupancy.