基于云平台的交通视频检测数据优化研究

交通视频检测技术在智能交通领域应用广泛,成为当前交通信息采集的主要手段.但在恶劣天气条件下,视频车辆检测器采集的交通数据误差较大,难以准确反映路面实际状况.为解决此问题,本文提出基于不同气象能见度等级构建k 型BP网络,对气象能见度低于10 km时的原始交通数据作预处理优化.分析了云计算在交通信息处理方面的优势,基于云计算平台实现了该模型的构建与推广.最后以成都绕城高速七里沟大桥定点观测得到的数据做样本进行实例分析,对比了该模型方法与传统处理方法的数据处理效果,得出了本文方法较传统方法先进的结论.     

城市区域交通检测器优化布局模型

智能交通系统（ITS）是公认的缓解城市拥堵的有效手段之一,交通检测器为ITS提供交通基础数据支持。在城市路网中合理布设交通检测器是保证交通数据准确、有效的前提。以交通检测器效用最大和布设检测器费用最少为目标,构建交通检测器优化布局模型,并通过算例加以说明,为此类研究提供了一个新的思路。     

Study on chromatographic fingerprint of sarcandra glabra （Thunb.） by microwave-assisted extraction coupled to HPLC/DAD

Microwave-assisted extraction (MAE) was used for extraction of effective components of sarcandra glabra (Thunb.), and then chromatographic fingerprint of sarcandra glabra (Thunb.) was studied by high performance liquid chromatography/diode array detector (HPLC/DAD). The conditions of MAE were optimized by an orthogonal experiment, and then the authentication and validation of the chromatographic fingerprint were conducted. Nine peaks were identified as common peaks in the fingerprint chromatograms, and isofraxidin was considered as a reference compound and quantified. Relative standard deviations of retention time and peak area of each component were less than 3% and 8%, respectively. Similarity and difference analysis were conducted by use of PCA and relation coefficient. Twenty batches of sarcandra glabra (Thunb.) samples from two different producing areas could be classified into two different groups in the PCA model. The results showed that MAE-HPLC/DAD method was simple, efficient and stable for the study of complex chromatographic fingerprint of sarcandra glabra (Thunb.), which could provide more reliable and precise information for quality evaluation.     

线圈检测器采集信息的预处理方法和多维数据模型的构造

通过环形线圈检测器采集的数据,不仅具有时间序列的特性,而且与其所处的空间位置有很大的关系。文中论述了线圈检测器数据产生的原理,并提出了相应的预处理算法。针对交通数据管理现状和数据挖掘需要,借鉴了空间多维数据模型以建立交通流数据仓库。     

基于InTouch系统的毒害气体监控系统的分析与设计

在使用毒性或危险性气体的制造行业中,如何实现对这些特殊气体的有效监控显得特别重要.本文通过对半导体制造企业的气体监控系统的需求分析,设计了气体监控系统中的网络结构、监控软件功能以及报警系统.实践效果良好.     

考虑时空相关性的固定检测缺失数据重构算法

应用相关性理论, 研究了交通流数据中缺失值与其他数据的相关性, 对与缺失值不同相关性的数据给予不同的权重值, 提出了基于交通流时空相关权重的重构算法, 并以北京市二环快速路为研究对象, 运用VISSIM仿真软件建立仿真模型, 利用仿真数据对新算法和现有算法进行了对比分析。研究结果表明: 在连续缺失1~10个数据时, 模型1的重构值与仿真值平均相对误差最大仅为1.8766%, 一般情况下, 平均相对误差均在1.0000%以下, 可见, 模型1算法优于现有的重构算法。     

Soft Radial Basis Cellular Neural Network (SRB-CNN) based robust low-cost truck detection using a single presence detection sensor

This paper does present a comprehensive concept for a robust and reliable truck detection involving solely one single presence sensor (e.g. an inductive loop, but also any other presence sensor) at a signalized traffic junction. Hereby, two operations modes are distinguished: (a) during green traffic light phases, and (b) a much challenging case, during red traffic light phases. First, it is shown how difficult the underlying classification task is, this mainly due to strongly overlapped classes, which cannot be easily separated by simple hyper-planes. Then, a novel soft radial basis cellular neural/nonlinear network (SRB-CNN) based concept is developed, validated and extensively benchmarked with a selection of the best representatives of the current related state-of-the-art classification concepts (namely the following: support vector machines with radial basis function, artificial neural network, naive Bayes, and decision trees). For benchmarking purposes, all selected competing classifiers do use the same features and the superiority of the novel CNN based classifier is thereby underscored, as it strongly outperforms the other ones. This novel SRB-CNN based concept does satisfactorily fulfill the hard industrial requirements regarding robustness, low-cost, high processing speed, low memory consumption, and the capability to be deployed in low cost embedded systems.     

Innovative detector layout for automated traffic turning volume counting

Because of many advantages, loop detectors are the most common practice for obtaining data to control intersections. However, they have some drawbacks, including the fact that multiple detectors are usually required to monitor a location. The current practice in many cities is to install four consecutive loop detectors per lane, or two at the stop bar and one as an advanced detector. In some cities, there are also departure detectors. All these configurations have some practical problems and do not produce accurate counts especially in shared lanes. In this paper, a new placement configuration for departure detectors is proposed and named the mid‐intersection detector (MID). In this configuration, departure detectors are moved back to the middle of the intersection in such a way that they can be activated by more than one movement at different times. In some cases, departure detectors lack equations for calculating turning movements, a problem solved by MIDs because each movement passes more detectors along its path (without increasing the number of loops), and therefore they can produce more accurate and reliable data for obtaining turning movement counts. Copyright © 2017 John Wiley & Sons, Ltd.     

车辆点火高压检测器的设计与试制

利用电磁感应原理，设计和试制车辆点火高压检测器。该检测器能将汽油机正常运转时点火系高电压的变化转化为感生电动势，驱动发光二极管发亮，从而确定汽油机点火系是否工作正常。具有简单易携带的优点。     

高速公路网络最小检测器布设新方法

对节点和路段进行定义，探索节点数目与路段数目之间的数量关系。根据流量守恒原则，建立了一个包含 n +1个方程、3n -m 个变量的齐次线性方程组。通过对方程组的系数矩阵进行初等行变换，直到找到一个最大无关向量组。将无关组向量对应的变量命名为基变量，其余变量命名为非基变量，所得到的基变量总可用非基变量表示。因变量与路段一一对应，只要在非基变量所对应的路段布设检测器，就可确定整个网络中所有路段的流量。对最小检测器布设数目的存在性和唯一性进行了证明，给出了任意网络检测器布设率的通用公式。应用该方法，设计了贵阳市区部分高速公路网络的最小检测器布设方案。