Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County
博士 === 中華大學 === 科技管理博士學位學程 === 105 === 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 imp...
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ndltd-TW-105CHPI16850142019-05-15T23:32:19Z http://ndltd.ncl.edu.tw/handle/82a2ra Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County 交通事故空間分析方法之研究-以南投縣為例 WANG, YU-MING 王裕民 博士 中華大學 科技管理博士學位學程 105 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. SU, JAU-MING 蘇昭銘 2017 學位論文 ; thesis 98 zh-TW |
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博士 === 中華大學 === 科技管理博士學位學程 === 105 === 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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author2 |
SU, JAU-MING |
author_facet |
SU, JAU-MING WANG, YU-MING 王裕民 |
author |
WANG, YU-MING 王裕民 |
spellingShingle |
WANG, YU-MING 王裕民 Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County |
author_sort |
WANG, YU-MING |
title |
Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County |
title_short |
Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County |
title_full |
Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County |
title_fullStr |
Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County |
title_full_unstemmed |
Methods of Spatial Analysis for Traffic Accidents: The Case of Nantou County |
title_sort |
methods of spatial analysis for traffic accidents: the case of nantou county |
publishDate |
2017 |
url |
http://ndltd.ncl.edu.tw/handle/82a2ra |
work_keys_str_mv |
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