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題名:交通事故空間分析方法之研究-以南投縣為例
作者:王裕民
作者(外文):WANG, YU-MING
校院名稱:中華大學
系所名稱:科技管理博士學位學程
指導教授:蘇昭銘
學位類別:博士
出版日期:2017
主題關鍵詞:空間分析重複性分析核密度分析嚴重性指標spatial analysisrepeatability analysiskernel density analysisseverity index
原始連結:連回原系統網址new window
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空間分析為交通事故最常使用的分析方法之一,在交通事故研究分析上,其最主要目的在於評定易發生交通事故的地點及區域,讓交通管理單位可以採取預防措施和實施交通安全等規定,以減少交通事故人員的傷亡及財物損失;因此,如何透過空間方法精確的分析,建立交通事故肇事分析平臺,讓用路人可以充分掌握相關資訊及安全駕駛於道路上,為目前交通安全政策推動上重要的課題。本研究以南投縣旅遊交通事故為分析主軸,以重複性分析、核密度分析及嚴重性指標等三種不同空間分析方法,進行肇事地點的分析比較,據以建構核密度嚴重性指標分析模式,評定10個路口、路段地點及指標分數,並與傳統嚴重性指標進行比較。研究顯示:核密度嚴重性指標分析模式評分的結果,較傳統嚴重性指標為高,在交通事故分析上,確實能有效排序出易肇事地點路口及路段;本研究透過不同的空間分析方法進行探討,以建構適宜的核密度嚴重性指標分析模式,及評列出易肇事地點及肇事特性,研究分析結果將可提供給道路交通管理機關,在未來建構肇事平台之參考。
Spatial analysis is the most commonly used method of analyzing traffic accidents. The primary objective of traffic accident studies and analyses is to identify locations and areas prone to accidents. This information allows traffic management authorities to implement preventive measures and traffic safety regulations that can reduce casualties or property damage caused by traffic accidents. How to perform accurate spatial analyses to establish a traffic accident analysis platform that provides road users with full access to relevant information which would encourage them to drive more safely on the road is therefore a crucial issue in traffic safety policies. The subjects of analysis in this study were tourism-related traffic accidents in Nantou County. Traffic accident locations were analyzed using three methods: repeatability analysis, kernel density analysis, and severity index; results from these analyses were compared. A novel analysis method, the kernel density-based severity index, was developed in this study and used to evaluate and score ten intersections or road sections based on various indicators. These results were compared to those obtained from a traditional severity index. Findings from the present study showed that the kernel density-based severity index produced higher scores than the traditional severity index. In addition, when this method was applied to traffic accident analysis, it produced an effective ranking of intersections and road sections that were prone to accidents. In the present study, different methods of spatial analysis were explored to construct an appropriate analysis method, namely, the kernel density-based severity index. This analysis method could be used to identify and rank traffic accident locations and characteristics. These study and analysis results can be provided to road or traffic management authorities and serve as a reference in the future construction of a traffic accident platform.
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