城市道路网络动态优化选择方法研究

基于解决动态路径诱导算法中的实时性、动态性和人的选择行为,提出了基于实时交通状态因素的动态道路优先等级指数的确定方法,建立了连线交通相似度的模型,研究了道路网络的动态分层规则和方法,实现了路网的动态优化选择,并通过简单的算例进行了验证分析。该方法具有很强的可操作性和应用价值。

Identification of Similar Air Traffic Scenes with Active Metric Learning

The rapid growth of air traffic has continuously increased the workload of controllers,which has become an important factor restricting sector capacity.If similar traffic scenes can be identified,the historical decision-making experience may be used to help controllers decide control strategies quickly.Considering that there are many traffic scenes and it is hard to label them all,in this paper,we propose an active SVM metric learning(ASVM2L)algorithm to measure and identify the similar traffic scenes.First of all,we obtain some traffic scene samples correctly labeled by experienced air traffic controllers.We design an active sampling strategy based on voting difference to choose the most valuable unlabeled samples and label them.Then the metric matrix of all the labeled samples is learned and used to complete the classification of traffic scenes.We verify the effectiveness of ASVM2L on standard data sets,and then use it to measure and classify the traffic scenes on the historical air traffic data set of the Central South Sector of China.The experimental results show that,compared with other existing methods,the proposed method can use the information of traffic scene samples more thoroughly and achieve better classification performance under limited labeled samples.

基于NCut算法的道路网子区划分研究

在对区域路网进行宏观研究时,由于交通流的复杂性和随机性,容易造成路网密度分布不均。因此,本文基于MFD理论,在利用MFD理论进行边界控制之前,提出基于归一化割(Normalized Cut,NCut)的路网子区划分算法将"异质"的路网划分为多个具有"同质性"的子区。首先,基于交通运行相似度构建了路网带权图,分析了NCut算法流程。其次按照一定的原则,采用NCut算法对以组间相似度为标准对路网进行近似归一划割。接着,为了克服NCut算法每次无法判断划分子区数量的问题,本文引入了各子区间匀质度的均值NSk(A,B)为评价指标来确定划分的子区数。最后,实验分析表明,根据该模型对望京区域路网进行划分,发现划分为4个子区时NS值最优。