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題 名 | 鑑別高速公路潛在易肇事路段影像準則及模式之建立=Development of a Freeway Accident Prone Area Image Evaluation Criteria and Model |
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作 者 | 黃國平; 莊榮哲; | 書刊名 | 成功大學學報 |
卷 期 | 32(科技.醫學篇) 民86.11 |
頁 次 | 頁169-197 |
分類號 | 557.34 |
關鍵詞 | 易肇事路段; 影像評估; 分析層級法; 影像實錄; Accident prone area; Image evaluation; Analytical hierachical process; Videologging; |
語 文 | 中文(Chinese) |
中文摘要 | 建立評估易肇事路段的準則,為本研究藉路段影像實錄建立評估易肇事路段模式 的基礎;本研究首先建立易肇事分析層級評估準則及評估程序,其次經由重現路段影像,比 對影像中符合易肇事評點項目。最後再由模式計算路段上的潛在易肇事指標,據以判斷一路 段是否為潛在易肇事路段。 國內外對於鑑別易肇事路段,已有多項研究;這些研究在尋找易肇事路段時,多是以歷 年肇事資料為基礎鑑別易肇事路段,因此得依賴完整的肇事資料始能進行研究。而對於肇事 資料零散或新開闢的道路,因為缺乏肇事歷史資料,所以難以找出影響肇事之因素,亦無法 在道路通車前或事故發生前予以改善,使得這些易肇事路段的潛在危險因素持續存在,導致 事故發生。 本研究應用影像實錄(Video logging)為工具,以路段上工程幾何及交通管理特徵為基 礎,進行評估路段易肇事程度及尋找潛在易肇事路段。研究成果除了突破傳統尋找易肇事路 段的万法外,並以實際肇事資料證明以影像實錄為基礎之肇事預測模式能有效尋找高速公路 易肇事路段。 基於校估模式必須取得道路流量、線形及交通管理資料,本研究乃針對路型封閉,幾何 及管理資料較完整的高速公路進行課題研究。研究範圍以高速公路327公里(仁德交流道) 迄373,2公里(高速公路高雄尾端)的路段為基礎,以民國82年至84年南下方向肇事及相 關資料建立路段特徵與肇事關係之評估準則,並配合事故肇因的專家權重AHP問卷構建影像 寘錄對路段肇事評點之預測模式。最後以影像評估模式對研究範圍北上路段進行肇事趨勢預 測,再以同期肇事資料(民國82年至84年)驗證預測結果。 |
英文摘要 | In the subject of safety analysis, historical accident data are normally used as the dependent variable to correlate with highway geometric elements, vehicle characteristics, driver features, time, etc. The lack of reliable or sufficient data often makes accident cause analysis impossible. For traffic or highway engineers, accident analysis is often used to identify accident prone areas in order to design countermeasures to reduce accident casualties or to plea for proper funds to improve safety efficiency. The purpose of this study is to establish both an evaluation criteria and a model to identify freeway accident prone areas. To achieve such a goal, the analytical hierarchical process (AHP) is used to obtain the evaluation criteria of accident causing factors. The priority vectors for those factors are then used to compute an image hazardous index for each section of freeway. The image hazardous index together with other system variables such as toll plaza, interchange, etc. are then put into the evaluation model to arrive at an overall sectional accident prone index. Thereafter, accident prone areas are identified through use of the accident prone index. The development of such a procedure and evaluation model is designed to supplement the current deficiency of statistical models whenever historical accident data are unavailable. To identify the occurrence frequency for each accident causing factor, a video logging system is developed and is used both to record and re-display the continuous freeway image. Those accident causing factors such as grade, length of grade, bridge abatement, gore, glare, etc. are then identified and scrutinized for further analysis. In order to calibrate and field test the developed system, the southern section of Taiwan's Sun Yat-Sen freeway is selected for analysis. The section has a length of 131.94 kilometers and has an accident history of 91 A-l records per year. |
本系統中英文摘要資訊取自各篇刊載內容。