摘要
交通拥堵日益严重,能根据路况信息实时在线决策出最佳交通路径对拥堵保畅就显得尤为重要。文章采用模糊隶属函数的数据处理方法解决了基于变结构离散动态贝叶斯网络的最佳交通路径决策模型只能处理离散数据的缺陷。采用模糊集构建隶属度函数,将采集到路况的连续性数据进行离散化,将离散化的数据用于最佳交通路径的规划。仿真实验验证了该模糊化数据处理方法的有效性。
Traffic congestion is becoming more and more serious. It is particularly important to be able to determine the optimal traffic path online in real time based on road condition information to ensure congestion. In this paper, the data processing method of fuzzy membership function is used to solve the defect that the optimal traffic path decision model based on variable structure discrete dynamic Bayesian network can only deal with discrete data. The fuzzy set is used to construct the membership function, and the continuous data of the collected road conditions is discretized, and the discretized data is used for the planning of the optimal traffic path. Simulation experiments verify the effectiveness of this fuzzy data processing method.
作者
刘晨兴
陈海洋
樊甜甜
赵程程
董显明
Liu Chen Xing;Chen Hai Yang;Fan Tian Tian;Zhao Cheng Cheng;Dong Xian Ming(College of Electronic Information,Xi＇an Polytechnic University,Xian 710048,China)
出处
《信息通信》
2018年第9期20-23,共4页
Information & Communications
关键词
模糊化
数据处理
隶属函数
路径规划模型
仿真验证
fuzzification
data processing
membership function
path planning model
simulation verification
