ایجاد شاخص های عملکرد ایمنی جاده با استفاده از روش دلفی فازی و روش دلفی گری

The main goal of this paper is to construct three sets of road safety performance indicators, which are regional road safety performance indicators, urban road safety performance indicators and highway safety performance indicators, respectively. Fuzzy Delphi Method and Grey Delphi Method are applied to quantify experts’ attitudes to regional road safety, urban road safety and highway safety. Comparing the results of two methods, the different results of two methods are analyzed, and then the final safety performance indicators are obtained by taking the intersection of results of two methods. Finally, three sets of performance indicators are constructed, which can be described and evaluated the safety level of region, urban road and highway, respectively. The research findings show that the method used in this paper is feasible and practical and can be provided as a reference for the administrative authority of road safety.

Road safety management is an important means for forecasting and preventing traffic accidents, and its core is the evaluation, forecast and decision-making technique of road safety. Especially, road safety evaluation is the foundation of safety management. In general, the process of evaluation is made up of evaluation object, evaluation indicator, weighting and evaluation model. In practice, the process of weighting and evaluation model is always paid much attention, but the selection of evaluation indicator is ignored. In fact, it is very important to choose scientific and rational evaluation indicators, which is the first step to conduct evaluation and the key problem concerning the success or failure of the whole process of evaluation. Therefore, how to establish a set of scientific and rational road safety performance indicators is the key problem for road safety management. Many researchers have dedicated to the research of the macro road safety model over 50 years, and these research results were remarkable, such as Smeed’s law (Smeed, 1949), Rumar descriptive model (Rumar, 1987), Koornstra’s function (Koornstra, 1996), Navin Model (Navin, Bergan, & Zhang, 1996) and Trinca model (Trinca, 1988). These models were used to compare countries’ road safety level by means of risk indicators, such as fatalities per vehicles, fatalities per population, fatalities per vehicle kilometers or the number of passenger miles. But some indirect influence factors, such as Socio-economic factor level and social medical condition, have not been considered. Some researchers established a comprehensive performance indicators taking into account the impact of direct and indirect influence factors from the view of systems engineering. Al-haji (2003) proposed a road safety development index (RSDI) allowing comparison among nations and adopted a framework used to develop a human development index (HDI), which included nine basic dimensions with 14 indicators and averaged them to produce the RSDI. Fu and Fang (2006) proposed highway network safety performance indicators, which included five basic dimensions with 13 relative indicators. Wu, Liu, and Xiao (2006) proposed freeway safety performance indicators, which included three basic dimensions with 11 indicators. Ma, Sun, and Han (2008) proposed urban road safety performance indicators, which included three basic dimensions with 11 indicators. Above all, these safety performance indicators have overcome the deficiency of indicators which were considered from the aspect of accidents, and have made great progress. But the present researches do not specify the detailed process of constructing road performance indicators and why those indicators are selected. Delphi Method was widely applied to select performance indicators in many fields, but it requires multiple investigations to achieve the consistency of expert opinions and experts are required and forced to modify their opinions so as to meet the mean value of all the expert opinions. However, Fuzzy Delphi Method requires only a small number of samples and the derived results are objective and reasonable. Not only it saves time and cost required for collecting expert opinions but also experts’ opinions will also be sufficiently expressed without being distorted (Hsu and Yang, 2000, Ishikawa et al., 1993, Kuo and Chen, 2008 and Murry et al., 1985). Furthermore, grey system theory also can deal with uncertain, hazy and incomplete data (Liu, Dang, & Fang, 2004). Grey whitening weight function can be described evaluation objects belonging to the degree of a certain grey class, and it has been widely used (Li et al., 2008, Shao et al., 2003 and Xie and Pan, 2007). Therefore, two kinds of methods are used to filter road safety performance indicators, which are Fuzzy Delphi Method and Grey Delphi Method, respectively. The main goal of this paper is to construct three sets of road safety performance indicators, which are regional road safety performance indicators, urban road safety performance indicators and highway safety performance indicators, respectively. Through Fuzzy Delphi Method and Grey Delphi Method, the importance of indicators can be derived. The comparative analysis on the results of two methods was carried out, and then three sets of road safety performance indicators could be constructed. The research results can be provided as a reference for the administrative authority of road safety.

This paper explored the application of Fuzzy Delphi Method and Grey Delphi Method to quantify experts’ attitudes to regional road safety, urban road safety and highway safety. Possible factors impacted regional road safety, urban road safety and highway safety are considered. Then, safety performance indicators are selected using Fuzzy Delphi Method and Grey Delphi Method, respectively. Comparing the results of two methods, the different results of two methods are analyzed, and then the final safety performance indicators are obtained by taking the intersection of results of two methods. Finally, three sets of performance indicators are constructed, which can be described and evaluated the safety level of region, urban road and highway, respectively. It can be discovered that some indicators were deleted. The main reason is that investigated experts had different focuses on the safety evaluation. This paper proposed three sets of primary performance indicators based on literature reviews in advance, which cover influencing factors on safety as much as possible. Besides, due to insufficient human resource and other objective factors, some biases of the survey results could still exist. However, these biases impacted on the results are too insignificant to mention and can be ignored. Therefore, the results in this paper are feasible and practical and can be provided as a reference for the administrative authority of road safety.