Robust PCA-Based Abnormal Traffic Flow Pattern Isolation and Loop Detector Fault Detection

One key function of intelligent transportation systems is to automatically detect abnormal traffic phenomena and to help further investigations of the cause of the abnormality. This paper describes a robust principal components analysis （RPCA）-based abnormal traffic flow pattern isolation and loop detector fault detection method. The results show that RPCA is a useful tool to distinguish regular traffic flow from abnormal traffic flow patterns caused by accidents and loop detector faults. This approach gives an effective traffic flow data pre-processing method to reduce the human effort in finding potential loop detector faults. The method can also be used to further investigate the causes of the abnormality.     

正规互质因子扰动模型集的闭环辨识与检验

鲁棒控制的系统辨识问题是控制领域一个十分活跃的研究方向。该文综述了具有正规互质因子扰动模型集的辨识与检验的结果。在闭环实验数据已知时 ,给出了正规互质因子频域响应极大似然估计的解析表达式 ,介绍了这一估计的统计特性和最优参数选择。讨论了基于受约束曲线拟合的正规互质因子参数辨识问题 ,给出了其解析解。最后介绍了模型集与控制器和闭环实验数据相匹配的一个充分必要条件。这一条件可表示为一个线性约束和一个复数向量的欧几里德范数。根据这一条件 ,讨论了随机框架下的模型集检验问题 ,给出了采样非伪概率的计算方法     

Modeling of Spacing Distribution of Queuing Vehicles at Signalized Junctions Using Random-Matrix Theory

The modeling of headway/spacing between two consecutive vehicles in a queue has many applications in traffic flow theory and transport practice.Most known approaches have only studied vehicles on freeways.This paper presents a model for the spacing distribution of queuing vehicles at a signalized junction based on random-matrix theory.The spacing distribution of a Gaussian symplectic ensemble(GSE)fits well with recently measured spacing distribution data.These results are also compared with measured spac...     

基于二分图的城市公交网络拓扑性质研究

以北京市公交系统为例,用二分图模型对其进行描述,分别构建出公交站点网络和公交线路网络,对二分图、公交站点网络和公交线路网络进行了度的分布、集聚系数以及平均路径长度等拓扑参数的计算,并与规则网络和随机网络进行了比较,发现北京市公交系统具有"小世界"网络的性质.最后深入地研究了公交线路网络与公交站点网络拓扑参数形成的机理.