基于IFS交通状态决策信息一致性融合

Consistent Fusion of Traffic State Decision Information Based on IFS

针对多源交通信息具有模糊性和时变性的特点,引入直觉模糊集理论(IFS),建立多源交通信息一致性融合算法,融合传感器检测信息与人工信息对交通状态进行实时判别.为了解决IFS中非隶属度函数难以确定的问题,借鉴隶属度函数的构造方法,通过建立双隶属度函数构造直觉模糊数.并以直觉模糊数中的隶属度、非隶属度建立支持度函数,量化决策信息的一致性程度,决策信息的支持度越高集成权重越大,并且权值随决策信息的变化而动态更新.最后给出交通状态决策信息融合算法的具体步骤,并通过算例证明算法是有效的.

Considering the multi-source traffic information with fuzziness and time-varying characteristics,this paper introduces the intuitionistic fuzzy set theory（IFS） to establish consistency fusion algorithm of multi-source traffic information.It integrates sensor detection information and artificial information to recognize on real-time traffic status.To solve the problem,it is difficult to determine in the non-membership function of the IFS.The construction method of the membership function is introduced,and the dual membership function is used to construct the intuitionistic fuzzy numbers.The support degree function is established using the membership degree and the non-membership degree,to quantify the degree of consistency in decision-making information.The higher the support degree of decision-making information is,the greater is the weight degree of integration.The weight is dynamically updated with the changes in the decision-making information.Finally,the steps is given for the traffic state decision-making information fusion algorithm,and an example is used to illustrate the effectiveness of the algorithm.