排序方式: 共有4条查询结果,搜索用时 15 毫秒
1
1.
This paper presents a full-scale solution to the detection of the traffic data using laser device. Range images, gathered
by a particular laser camera, are used in the multi-threshold segmentation. The multi-threshold segmentation is based on the
height of the moving objects. In order to get the precise height of the moving objects, mapping of the original terrain is
performed on the first step. On each layer, the clustering algorithm called iteration-self organizing data analysis techniques
algorithm (ISODATA) is conducted afterwards. Kalman filtering technique is applied to recognize and track the moving objects.
Extensive experiments show that these algorithms are effective in object recognition and tracking, as well as robust in the
applications. 相似文献
2.
In order to make full use of heterogeneous multi-sensor data to serve urban intelligent transportation systems, a real-time urban traffic state fusion model was proposed, named federated evidence fusion model. The model improves conventional D-S evidence theory in temporal domain, such that it can satisfy the requirement of real-time processing and utilize traffic detection information more efficaciously. The model frame and computational procedures are given. In addition, a generalized reliability weight matrix of evidence is also presented to increase the accuracy of estimation. After that, a simulation test is presented to explain the advantage of the proposed method in comparison with conventional D-S evidence theory. Besides, the validity of the model is proven by the use of the data of loop detectors and GPS probe vehicles collected from an urban link in Shanghai. Results of the experiment show that the proposed approach can well embody and track traffic state at character level in real-time conditions. 相似文献
3.
针对短时交通流变化的复杂性与非线性特点,分析了分类回归树模型的建立,包括模型的生长、分裂与剪枝,研究了模型在高速路交通流短时预测中的应用,并对美国波特兰州高速路网的真实交通流量数据进行分析建模.采用RMSE与MAPE误差分析法,将试验结果与传统的交通流预测方法ARIMA模型与Kalman滤波预测模型进行比较.对比结果表明:分类回归树预测模型的RMSE比ARIMA模型与Kalman滤波预测模型分别降低了42.1%、13.1%. 相似文献
4.
1