基于最大互信息系数的高饱和度交叉口延误模型修正

Delay Model Correction of High Saturation Intersection Based on Maximal Information Coefficient

提出了一种基于最大互信息系数的高饱和度交叉口延误修正模型。使用无人机调查道路通行能力手册(highway capacity manual,HCM)延误模型中所有变量的实测数据,运用R语言和Java语言的通信接口rjava调用最大互信息系数(maximal information coefficient,MIC)算法编码对HCM延误模型中的变量及组合进行最大互信息相关度分析,通过统计软件R对交通流量、通行能力、绿信比等与延误值进行互信息相关度比对检验,选取非线性关系对现有模型进行重新修正,根据赤池信息准则筛选出最佳解释数据、包含最少自由参数的备选项作为优化模型。最后以修正模型计算高(过)饱和度交叉口案例的延误值,与原HCM延误模型和交通仿真模拟值进行结果比对,得出本文提出的新模型具有更高的精确度。

A modified model for calculating delay at high saturation intersections based on maximal information coefficient was proposed.Firstly,unmanned aerial vehicles(UAVs)were used to investigate measured data for all variables in the highway capacity manual(HCM)delay model,and the maximum mutual information correlation analysis of variables and combinations in HCM model was carried out by using rjava to call maximal information coefficient(MIC)algorithm coding,accordingly,the correlation of mutual information between traffic flow,saturation,green signal ratio and delay value was compared and tested through the statistical software R,thus to choose a nonlinear relation to modify the existing model.Then,the modified model with the best interpretation data containing and the least free parameters was selected as the optimal choice according to Akaike information criterion.Finally,by using the modified model to calculate the delay value of high(excessive)saturated intersection cases,comparing with results from HCM and traffic simulation,it is concluded that the new model proposed has higher accuracy.