Data fusion algorithm for macroscopic fundamental diagram estimation

A promising framework that describes traffic conditions in urban networks is the macroscopic fundamental diagram (MFD), relating average flow and average density in a relatively homogeneous urban network. It has been shown that the MFD can be used, for example, for traffic access control. However, an implementation requires an accurate estimation of the MFD with the available data sources.Most scientific literature has considered the estimation of MFDs based on either loop detector data (LDD) or floating car data (FCD). In this paper, however, we propose a methodology for estimating the MFD based on both data sources simultaneously. To that end, we have defined a fusion algorithm that separates the urban network into two sub-networks, one with loop detectors and one without. The LDD and the FCD are then fused taking into account the accuracy and network coverage of each data type. Simulations of an abstract grid network and the network of the city of Zurich show that the fusion algorithm always reduces the estimation error significantly with respect to an estimation where only one data source is used. This holds true, even when we account for the fact that the probe penetration rate of FCD needs to be estimated with loop detectors, hence it might also include some errors depending on the number of loop detectors, especially when probe vehicles are not homogeneously distributed within the network.     

A data fusion approach for real-time traffic state estimation in urban signalized links

Real-time estimation of the traffic state in urban signalized links is valuable information for modern traffic control and management. In recent years, with the development of in-vehicle and communication technologies, connected vehicle data has been increasingly used in literature and practice. In this work, a novel data fusion approach is proposed for the high-resolution (second-by-second) estimation of queue length, vehicle accumulation, and outflow in urban signalized links. Required data includes input flow from a fixed detector at the upstream end of the link as well as location and speed of the connected vehicles. A probability-based approach is derived to compensate the error associated with low penetration rates while estimating the queue tail location, which renders the proposed methodology more robust to varying penetration rates of connected vehicles. A well-defined nonlinear function based on traffic flow theory is developed to attain the number of vehicles inside the queue based on queue tail location and average speed of connected vehicles. The overall scheme is thoroughly tested and demonstrated in a realistic microscopic simulation environment for three types of links with different penetration rates of connected vehicles. In order to test the efficiency of the proposed methodology in case that data are available at higher sampling times, the estimation procedure is also demonstrated for different time resolutions. The results demonstrate the efficiency and accuracy of the approach for high-resolution estimation, even in the presence of measurement noise.     

仿真潜艇航向对规避航空磁探仪搜索的影响

利用蒙特卡罗法仿真潜艇航向对规避航空磁探仪搜索的影响,为实际潜艇规避过程提供理论指导。首先分析航空磁探仪所测磁异常信号的表达式,然后将潜艇作为一个具有三轴磁矩的磁偶极子,并考虑其航向及地磁倾角等因素,根据理论分析得出以潜艇为中心的直角坐标系下的磁场表达式,在此基础上建立航空磁探仪搜潜的数学模型。最后利用蒙特卡罗法对潜艇不同航向时被航空磁探仪搜索到的概率进行仿真。仿真结果表明潜艇在规避磁探仪搜索时应尽量东西向航行。     

海上油气平台可燃气体探测器的布置、选型、安装和维护

在海上平台油气生产中，有效地利用可燃气体探测器来检测海上生产设备的泄漏状况，并及时采取相应的保护措施，是保证油气生产和人身安全的重要一环。但目前对海上油气平台可燃气体探测器工程设计的系统研究却鲜见于国内外的工程文献中，针对这一现状，在研究国内外现有规范和标准以及工程设计经验的基础上，通过分析可能产生泄漏的工艺设备、可燃气体性质和外部环境等因素来确定可燃气体探测器的物理位置，同时完成可燃气体探测器的选型，并根据现场的工作环境合理安装可燃气体探测器，最后总结探测器使用维护中需要注意的问题。对可燃气体探测器的布置、选型、安装和维护的系统总结和分析研究为海上平台火气系统的设计提供了技术支持，从而进一步保障海上油气平台的生产安全。     

道岔外锁闭装置在线探伤仪的研制

道岔外锁闭装置是重要的信号基础设备,直接关系到铁路运输的安全。介绍了一种外锁闭装置在线探伤仪,采用超声波探伤原理,能够实现外锁闭装置在线探伤,可智能选择预置探点并判定结果,是电务维护人员对在用外锁闭装置进行在线无损检测的专用工具。     

隧道火灾探测器的应用与测试技术

概述了国内外目前常见的几种隧道火灾探测器的工作原理和应用现状,归纳了他们在实际应用中的普遍优势、常见问题和存在缺陷。在介绍感温火灾探测器产品检测方法的基础上,结合传统工程检测方法和工程现场情况,对高速公路隧道火灾探测器的检验方法和思路进行了一定的创新和开拓,介绍了可应用于隧道火灾探测器工程现场检测的新方法,探讨了简单易行的检测方案,确保检测内容能够真实反映系统运行情况。现场实际应用表明,这些方法具有实用和推广价值,希望能对隧道火灾探测器的初期选型、后期维护以及工程检测过程有所帮助。     

基于图像识别与追踪技术的高速公路交通事件有效检测范围

针对视频交通事件检测器的有效检测范围目前在行业内产生的广泛争议,结合摄像机安装高度、安装角度、摄像机性能指标,通过理论计算和试验验证,得到视频交通事件检测系统对相关交通事件的合理检测范围,从而为高速公路全程视频监控系统外场监控摄像机的布设间距、布设方式提供数据支持,实现高速公路全程无盲区智能化监控识别。计算结果表明,对于小汽车停驶等交通事件,其有效检测距离大于1 000 m的传统说法是不准确的,目前的技术水平很难达到,其合理检测距离应该在500 m左右,试验数据验证了这一说法,但视频交通事件检测系统的有效检测距离后续会随着摄像机性能的不断增强而有所提高,从而满足高速公路监控系统不断提高的监控需求。     

过零极性相关算法在管道测漏中的应用

由于传统相关测漏仪采用直接相关法,对硬件要求高,价格较贵,提出将过零极性相关算法应用于相关测漏,并设计出硬件结构,进行了实验仿真,验证了其可行性。     

基于手机信息的居民出行调查

居民出行数据是交通规划中最重要的基础资料之一,但在传统居民出行调查中该数据的获取耗时长、成本高、自动化程度低,完全不能满足现行中国蓬勃的城市建设、规划的需要。该文提出了“person as sensor”的概念,也就是把居民日常使用的通讯工具——手机作为检测器,利用手机在居民使用过程中产生的大量位置和时间信息进行居民用户调查。该方法对现有的无线网络和手机都不需要进行任何修改,并且一旦实施将能够获取居民出行的实时数据。     

基于检测器脉冲数据的高速公路事件自动检测算法研究

提出了一种全新的高速公路事件自动检测算法,直接利用车辆检测器输出的脉冲宽度和脉冲间隔作为参数,运用LVQ神经网络对获得的脉冲宽度数据和脉冲间隔数据进行处理来判断是否有事件发生,从而大大减少了检测时间,为交通事件的快速处理提供了可靠的依据。此外,该算法利用神经网络的自学习能力,可以很好地确定各条道路发生交通事件的门限值。仿真结果表明:该算法具有较高的事件检测率(约为97%)、较短的检测时间和较低的误警率(约为0 41%),具有很好的应用前景。