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对国内宏观道路交通安全模糊综合评价方法进行改进,重点是改进了模糊层次分析法中由两两比较判断矩阵确定权重的方法,即提出了基于三角模糊数的权重计算方法。基于交通事故绝对指标及人、车、路等关联因素指标,确定出了9个评价指标,构建了宏观交通安全评价体系。引入三角模糊数来描述各指标权重。与传统模糊层次分析法中用1~9个整数及其倒数确定权重的方法相比,三角模糊数表达的是一个区间的概念,给定可能性区间的上限、下限及取值可能性最大的中限值,从而得到整个区间范围内不同参数的可能性,更好的保留了模糊评价过程中的有效信息,评价结果更为合理。给出了基于隶属函数的评判矩阵确定方法和最终的模糊综合评价方法。并以国内31个省、自治区、直辖市近10年的统计数据为例,进行方法应用并对宏观交通安全状况进行分析。分析评价结果可知,基于三角模糊数权重算法的交通安全评价方法更为准确合理,从2005年至2014年的10年间,安全状况为差的地区比例从87%降低至6.5%,整体的交通安全状况有了极大提高。
The method of fuzzy comprehensive evaluation of macro road traffic safety in China is improved. The emphasis is to improve the method of determining the weight by comparison judgment matrix in fuzzy AHP, that is, the weight calculation method based on triangular fuzzy number is proposed. Based on the absolute indicators of traffic accidents and the related factors such as people, vehicles and roads, 9 evaluation indexes were determined and a macro-traffic safety evaluation system was constructed. The triangular fuzzy number is introduced to describe the weight of each index. Compared with the traditional fuzzy analytic hierarchy process using 1 to 9 integers and their reciprocal weights, the triangular fuzzy number expresses the concept of an interval. Given the upper limit, lower limit and maximum value of the possible interval The possibility of different parameters in the whole range can be obtained and the valid information in the process of fuzzy evaluation can be better preserved so that the evaluation result is more reasonable. The determination method of matrix based on membership function and the final fuzzy comprehensive evaluation method are given. Taking the statistics of the past 31 years in 31 provinces, autonomous regions and municipalities directly under the Central Government as an example, the method is applied and the macro-traffic safety situation is analyzed. According to the analysis and evaluation results, the traffic safety assessment method based on the triangular fuzzy number weighting algorithm is more accurate and reasonable. From 10 years from 2005 to 2014, the proportion of areas with poor safety conditions decreased from 87% to 6.5%. The overall traffic safety The situation has greatly improved.