路面检测技术综述

总结了路面检测重要研究成果, 分析了路面损坏、平整度、车辙、抗滑性能(构造深度) 和结构强度(弯沉) 检测技术的发展现状, 研究了路面检测技术的不足与发展方向。研究结果表明: 国内外路面检测技术的发展经历了3个阶段, 从早期传统的人工检测到20世纪末的半自动化检测, 发展到目前的无损自动检测; 无损自动检测的主要特点是快速与智能化, 采用多源传感器协同工作, 并且集成在多功能道路检测车上, 能够同时检测路面损坏、平整度、车辙、抗滑性能和结构强度以及道路线形与沿线设施等; 在路面损坏检测方面, 采用数字图像检测技术, 实现了路面裂缝的快速检测; 在路面平整度检测方面, 采用激光位移传感技术, 实现了快速自动化检测; 在路面车辙检测方面, 采用激光和数字图像技术, 实现了非接触智能化检测; 在路面抗滑性能和结构强度检测方面, 建立了铺砂法与贝克曼梁法检测结果的相关关系, 实现了基于激光技术的路面构造深度与弯沉快速检测; 为了减少外界因素对现有检测技术和检测设备的干扰, 提高检测信号的信噪比, 应该开发适合各种工况下的路面检测和数据处理方法, 实现路面检测高效化与智能化。     

基于椭圆拟合的隧道点云数据去噪方法

针对地铁隧道这一狭长密闭环境,激光雷达相较于传统隧道形变检测方法具有显著优势.由于受环境以及隧道中安装的大量设备的影响,数据中会包含大量噪声点,无法得到隧道完整内表壁数据,从而影响到数据在形变检测及三维建模等方面的应用.结合最小二乘法和拉格朗日乘数法对隧道点云模型进行椭圆拟合,并将其应用于圆形隧道点云滤波,利用各区域数...     

指挥台围壳雷达隐身性数值模拟

对潜艇指挥台围壳在水面航行状态和半潜航行状态下的雷达隐身性进行研究。基于高频法,应用CATIA和MATLAB软件对三元流线型指挥台围壳和传统的直壁式指挥台围壳的雷达散射截面积（RCS）特性进行数值模拟和对比分析,并在此基础上进行雷达发现概率的计算。研究指挥台围壳的探测概率随距离变化的关系和指挥台围壳在2种航行状态下各重点探测角域探测概率的变化关系。研究表明,对指挥台围壳进行三元流线型设计并配合低矮化设计后,能明显改善潜艇指挥台围壳的雷达隐身性。     

基于双视角学习原理的交通视频车辆事件鲁棒检测

提出了1种基于双视角学习原理的高速公路交通视频车辆事件鲁棒检测算法.针对道路交通结构化特点提出了分车道外极面图(Epipolar Plane Image,简称 EPI),以此反映交通断面车流整体特征.基于双视角学习原理,融合现有广泛应用的反映车辆独立行为的行驶轨迹特征,实现高速公路车辆事件鲁棒检测.针对多种典型车辆事件(包括交通拥堵,车辆逆行,车辆违规停车,交通事故等),本文算法总体检测率为94.09%,误检率为4.51%,漏检率为1.40%,其性能与传统单视角方法比较有较大的提高.     

Travel mode estimation for multi-modal journey planner

For route planning and tracking, it is sometimes necessary to know if the user is walking or using some other mode of transport. In most cases, the GPS data can be acquired from the user device. It is possible to estimate user’s transportation mode based on a GPS trace at a sampling rate of once per minute. There has been little prior work on the selection of a set of features from a large number of proposed features, especially for sparse GPS data. This article considers characteristics of distribution, auto- and cross-correlations, and spectral features of speed and acceleration as possible features, and presents an approach to selecting the most significant, non-correlating features from among those. Both speed and acceleration are inferred from changes in location and time between data points. Using GPS traces of buses in the city of Tampere, and of walking, biking and driving from the OpenStreetMap and Microsoft GeoLife projects, spectral bins were found to be among the most significant non-correlating features for differentiating between walking, bicycle, bus and driving, and were used to train classifiers with a fair accuracy. Auto- and cross-correlations, kurtoses and skewnesses were found to be of no use in the classification task. Useful features were found to have a fairly large (>0.4) correlation with each other.     

Identification of communities in urban mobility networks using multi-layer graphs of network traffic

This paper proposes a novel approach to identify the pockets of activity or the community structure in a city network using multi-layer graphs that represent the movement of disparate entities (i.e. private cars, buses and passengers) in the network. First, we process the trip data corresponding to each entity through a Voronoi segmentation procedure which provides a natural null model to compare multiple layers in a real world network. Second, given nodes that represent Voronoi cells and link weights that define the strength of connection between them, we apply a community detection algorithm and partition the network into smaller areas independently at each layer. The partitioning algorithm returns geographically well connected regions in all layers and reveal significant characteristics underlying the spatial structure of our city. Third, we test an algorithm that reveals the unified community structure of multi-layer networks, which are combinations of single-layer networks coupled through links between each node in one network layer to itself in other layers. This approach allows us to directly compare the resulting communities in multiple layers where connection types are categorically different.     

Assessing carbon emissions from road transport through traffic flow estimators

Carbon emissions from road transport are one of the main issues related to modern transport planning. To address them adequately, the acquisition of reliable data about traffic flow is an essential prerequisite. However, the large quantity and the heterogeneity of available information often cause problems; missing or incomplete data are one of the most critical aspects. This paper discusses how technology handles imperfect information in order to obtain more accurate quantification of CO₂ emissions. First, an analysis of single estimators and combination models is provided, highlighting their main characteristics. Then, the TANINO model (Tool for the Analysis of Non-conservative Carbon Emissions In TraNspOrt) is presented, jointly developed at the University of Seville and at the IUAV University of Venice. It consists of two different modules: the first is a combination model that optimizes the results of three traffic flow single estimators, while the second is a macro-model of carbon evaluation, which takes into account road infrastructure, vehicle type and traffic conditions. TANINO is then tested to calculate CO₂ emissions along the ring road of the Spanish city of Seville, showing its more efficient performance, compared to the single estimators normally adopted for such aims. Transport planning can benefit from the adequate knowledge of traffic flows and related CO₂ emissions, since it allows a more reliable monitoring of the progresses granted by specific carbon policies.     

基于交叉感应回线的磁浮车辆连续测速定位方法

分析了交叉回线区域空间磁场分布, 利用磁通密度纵向分布周期性特征, 将车辆位移、速度用感应电压包络信号相位角与角速度来表征; 建立了采用简单交叉回线的车辆测速定位状态空间方程组, 将车辆运行位置和速度作为状态变量在测试过程中连续输出; 考虑实际运行工况下的复杂电磁环境, 引入了噪声自适应算法, 提出了基于新息自适应的磁浮车辆实时连续测速定位计算方法; 在实验室条件下建立了交叉感应回线标定系统, 验证了方法的基本原理; 为了验证方法的有效性和准确性, 进了数值仿真算例分析, 考虑正常噪声和突变噪声工况, 并对比了包含和不包含自适应噪声处理过程的计算结果。试验结果表明: 不同间隔距离条件下, 感应电压包络线都接近于正弦波, 1次谐波是包络信号的主要成分, 相同阶次的谐波幅值与间隔距离成近似线性关系, 与理论分析结果一致; 在正常噪声区段, 速度误差不超过0.03 m·s^-1, 定位误差约为3 mm, 在突变噪声区段, 速度误差均值为0.027 m·s^-1, 最大值为0.130 m·s^-1, 定位误差均值为4.82 mm, 最大值为23.39 mm, 说明测速定位方法可以满足实际应用需求; 数值仿真中突变噪声区段的低信噪比信号在实际应用中是极端情况, 对比正常噪声区段和突变噪声区段的计算结果可知改善输入信号的信噪比可以明显提高测试精度。     

基于弦测法与密度聚类的三维结构光波磨检测

为解决钢轨波磨人工检测费时费力及惯性法检测精度较低的问题,综合利用三维结构光技术、弦测法和密度聚类算法进行波磨检测。首先获取钢轨点云,通过纵向平面遍历轨头点云得到钢轨的纵向截面簇,其次利用弦测法计算相应纵向截面的谷深和波长。最后利用钢轨发生波磨时产生的接触斑,对遍历计算的谷深和波长分别进行密度聚类,将相同或相似接触斑的波磨信息聚类成簇,对聚类后各簇的结果进行统计分析得到相应钢轨的波磨信息。本方法结合三维结构光数据量大、弦测法计算直接明确的优点,通过密度聚类将不同深度、大小的波磨接触斑进行区别,有效地将钢轨波磨不同谷深及波长成分进行分类计算。实验室样件试验及现场试验表明,本方法能够实现对钢轨波磨的精确检测。     

铁路道岔防跳结构优化建议

为提升铁路道岔防跳结构的可维护性、完善检测方法和标准,提出以下优化方案:(1)改变防跳顶铁顶头截面形状,减小修配面积;(2)改变防跳限位装置螺栓头部厚度,选择更高强度的材质,取消开口销安装孔;(3)增加防跳间隔铁安装面内侧避让空间。通过对比分析或受力仿真分析,确认优化方案的可行性,提升道岔防跳结构零部件的维修便利性的同时,增强其防跳功能,提高行车安全性。最后,给出防跳间隙设置的建议,并提出防跳卡铁的检测方法,为铁路道岔防跳结构设计、检测提供参考。