標題: 以機車事故發生過程構建風險矩陣之研究
Constructing Motorcycle Crash Risk Matrix for Safety Improvement Based on Crash Sequences
作者: 陳聖尹
Chen, Sheng-Yin
吳昆峯
Wu, Kun−Feng
運輸與物流管理學系
關鍵字: 交通事故改善;事故資料;事故流程序列;traffic accidents improvement;crash data;crash sequence
公開日期: 2015
摘要: 以國內每年道路事故統計資料發現國內的機車事故持續增加,產生不少社會問題和社會成本。縱使國內相關道路安全改善單位利用了國內事故資料進行分析,並提出相關解決辦法,而由於國內資料的缺陷,在事故流程和碰撞型態的資訊過少,導致改善效果有限。因此本研究藉由美國GES (General Estimates System)的事故流程資料,用以探究事故的發生原因和過程,將事故流程變成序列類型資料進行分析,揀選、合併適合的資料產出事故流程序列,並利用事故的嚴重度和發生次數繪成事故風險評估表,找出應優先改善的事故類型。最後,本研究找到優先改善的四個主要事故類型,藉由過去文獻和GES現有事故資料分析出可能的事故發生原因,提出可行的改善方案,並建議國內如何改善現有事故資料,用以改善國內事故資料的缺陷。
In Taiwan, motorcycles’ crashes keep rising, and cause lots of social cost. Although the government has devoted resource in roadway safety improvement, the chosen countermeasures may not effectively reduce the severity and the number of crashes. Because of lack of the crash data, the agency of roadway improvement lacks messages about the process of crashes. The countermeasure they’ve chosen may not have the direct effectiveness to improve the crashes, which they want to solve. Therefore, we use American GES data (General Estimates System) to find a way to analyze crash sequence data, which have the information of crash’s process. This study would use crash sequence to make the groups, and use risk assessment table to discuss the severity and the number of those groups in the same time to find out which kinds of crash sequence is the severe one that need to improve first. By using crash sequence data, it shows more detail about the crashes, so it would be helped to find out the more effective countermeasures. This study would also discuss what data is lacked in Taiwan, if we want to build crash sequence data.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT070253602
http://hdl.handle.net/11536/127571
Appears in Collections:Thesis