CAJ | 학술논문

为精确建立车辆跟驰模糊推理系统,提出采用模糊聚类分析的方法为输入、输出变量划分模糊集,并求出对应的高斯隶属度函数;引入Takagi-Sugeno推理方法进行车辆跟驰模糊推理与去模糊化处理;利用NGSIM数据对模糊推理系统和Gipps跟驰模型进行参数标定并评价.结果表明:改进的建立车辆跟驰模糊推理系统的方法能真实反映数据本身的特征和驾驶员的心理生理特性,并且所建立的模糊推理系统与Gipps模型相比,其误差指标的仿真精度均有较大提升.
위정학건립차량근치모호추리계통,제출채용모호취류분석적방법위수입、수출변량화분모호집,병구출대응적고사대속도함수;인입Takagi-Sugeno추리방법진행차량근치모호추리여거모호화처리;이용NGSIM수거대모호추리계통화Gipps근치모형진행삼수표정병평개.결과표명:개진적건립차량근치모호추리계통적방법능진실반영수거본신적특정화가사원적심리생리특성,병차소건립적모호추리계통여Gipps모형상비,기오차지표적방진정도균유교대제승.
In order to establish the car-following fuzzy inference system ( FIS) accurately, the fuzzy clustering analysis method is adopted to divide input and output variables into various fuzzy sets, and the corresponding Gaussian membership function is determined.Then, the Takagi-Sugeno inference method is introduced to conduct-the car-following fuzzy inference and the defuzzification.Finally, the fuzzy inference system and the Gippscar-fol-lowing model are calibrated and evaluated by using NGSIM data.The results show that the improved method to establish the car-following fuzzy inference systemcan truly reflect the characteristics of the data itself and the driver's psychological and physiological features, and that the established fuzzy inference system achieves a much higher simulation accuracy of error indexes in comparison with the Gipps model.