摘要
提出一种基于ART2神经网络的高速公路交通事件自动检测的新算法。该算法利用高速公路交通流模型和ART2神经网络分别作观测器和分类器,观测器估计的数据和实际交通数据进行比较,得到残差序列;利用ART2神经网络对残差序列进行分类,以区分不同交通状态下的交通信息,达到检测交通事件的目的。本算法不但可以识别已知的交通事件类型,还可以识别未知的或从未出现过的交通事件类型,是一个可以边工作、边学习的检测系统。
A novel algorithm of expressway automatic incident detection based on the ART2 neural networks is proposed. This algorithm uses respectively the expressway traffic flow model and ART2 neural networks as observer and classifier. The residual signals will be gotten from the comparison between the actual and the estimated values of observer, the ART2 neural networks is used to classify characteristics contained in the residuals. So, whether the traffic incident has happened can be detected . It can not only recognize known traffic incident type but also can recognize unknown traffic incident type. This algorithm is a system which can be learned at the same time of working.
出处
《公路》
北大核心
2005年第8期114-118,共5页
Highway
基金
国家自然科学基金资助项目(60374056)
