%0 Journal Article %T 结合自然语言处理与改进层次分析法的乘用车驾驶舒适性评价<br>Driving comfort evaluation of passenger vehicles with natural language processing and improved AHP %A 卢兆麟 %A 李升波 %A Schroeder Felix %A 周吉晨 %A 成波 %J 清华大学学报(自然科学版) %D 2016 %R 10.16511/j.cnki.qhdxxb.2016.22.004 %X 为了有效和准确地评价乘用车驾驶舒适性, 构建了 “人-机-环境” 系统下的汽车驾驶舒适性本体模型, 并对驾驶舒适性的形成机制进行了阐述。通过用户访谈实验并基于改进的 “词频-逆向文件频率” (TF-IDF)方法对主题词进行提取, 获得影响驾驶舒适性的主要因素并进行分类, 在此基础上建立递阶层次结构; 针对传统层次分析法(AHP)的不足, 以三标度取代九标度以保证精确性, 通过Delphi实验, 构造两两比较判别矩阵后再进行处理, 以计算各评价指标的权重, 并对该指标体系进行一致性检验。以C级乘用车为例, 验证了该评价方法的有效性。该方法为乘用车的驾驶舒适性评价提供了一种可行的技术支持。<br>Abstract:The driving comfort of drivers in passenger vehicles was evaluated using an ontology model for driving comfort in a human-machine-environment system. The model was then used to evaluate driving comfort with the main driving comfort description extracted and classified via user interviews based on the improved term frequency-inverse document frequency (TF-IDF) method. The words were then ranked in a hierarchical structure. The scale of nine in the traditional analytical hierarchy process (AHP) was replaced by a scale of three to improve the accuracy. The comparative judgment matrix was defined with the weight of each index calculated through a Delphi survey. The index consistency system was also tested. The reliability of this method was validated using C-class passenger vehicles. Thus, this gives an effective approach for evaluating vehicle driving comfort. %K 乘用车 %K 驾驶舒适性 %K 评价指标 %K 层次分析法 %K 自然语言处理 %K < %K br> %K passenger vehicle %K driving comfort %K evaluation index %K analytic hierarchy process %K natural language processing %U http://jst.tsinghuajournals.com/CN/Y2016/V56/I2/137