{"title":"Creating a composite road safety performance index by a hierarchical fuzzy TOPSIS approach","authors":"Qiong Bao, D. Ruan, Yongjun Shen, Elke Hermans","doi":"10.1109/ISKE.2010.5680828","DOIUrl":null,"url":null,"abstract":"With the increasing public awareness of the complexity of road safety phenomenon, much more detailed aspects of crash and injury causation rather than only crash data (e.g., the number of road fatalities) are extensively investigated in the current road safety research. Safety performance indicators (SPIs), which are causally related to the number of crashes or to the injury consequences of a crash, are thus rapidly developed and increasingly used. Furthermore, to measure the multi-dimensional concept of road safety which cannot be captured by a single indicator, the exploration of a composite road safety performance index is attractive and desirable. This study proposes a hierarchical fuzzy TOPSIS method to combine the multilayer SPIs into one overall index by incorporating experts' opinions. Using the number of road fatalities per million inhabitants as a relevant point of reference, the proposed method has proven valuable as an alternative way in creating a composite road safety performance index for a set of European countries. Meanwhile, it effectively handles experts' linguistic expressions instead of crisp values and takes the layered hierarchy of the indicators into account which is seldom considered in the current index research.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"10 1","pages":"458-463"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE.2010.5680828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
With the increasing public awareness of the complexity of road safety phenomenon, much more detailed aspects of crash and injury causation rather than only crash data (e.g., the number of road fatalities) are extensively investigated in the current road safety research. Safety performance indicators (SPIs), which are causally related to the number of crashes or to the injury consequences of a crash, are thus rapidly developed and increasingly used. Furthermore, to measure the multi-dimensional concept of road safety which cannot be captured by a single indicator, the exploration of a composite road safety performance index is attractive and desirable. This study proposes a hierarchical fuzzy TOPSIS method to combine the multilayer SPIs into one overall index by incorporating experts' opinions. Using the number of road fatalities per million inhabitants as a relevant point of reference, the proposed method has proven valuable as an alternative way in creating a composite road safety performance index for a set of European countries. Meanwhile, it effectively handles experts' linguistic expressions instead of crisp values and takes the layered hierarchy of the indicators into account which is seldom considered in the current index research.