一个公路视频GIS的设计与实现

提出了一个新概念:公路视频G IS。即将公路地理信息与视频影像集成,为公路管理提供空间位置与视频影像相融合的超媒体信息。该系统的基本思想是将地理位置(XY)、公路里程(M)、视频时间或帧(T/F)之间建立映射关系,实现影像播放、地理位置、文字属性的同步显示和交互操作。系统设计和开发实践表明:公路视频G IS的基本思路和技术方案是可行的,本文提出的地理空间与视频影像集成的数据模型具有应用价值。     

基于GPS高速公路移动视频监控系统研究

根据高速公路中处理突发事件的业务需要,结合当前通信技术的发展,提出一种基于GPS技术的高速公路移动视频监控方法,研究了如何将GPS坐标信息与视频影像融合,及如何通过3G通信技术进行数据传输,并提出了该方法的系统组成和功能实现.     

基于ActiveX技术构建B/S模式的交通视频监控系统

基于ActiveX技术构建了B/S模式的交通视频监控系统,采用先进的H.264视频压缩算法和流媒体技术,很好解决了视频图像停顿、延迟和抖动的现象,实现对远程摄像头和云台的控制,实现多方位监控,并且大大降低了客户端的管理和维修费用.     

基于Labview的车辆跟踪系统

针对目前城市中交叉口智能化管理的迫切需求．设计了一种基于Labview的车辆跟踪系统。选用Labview非配套的图像采集卡，使用动态链接库技术开发了驱动程序，实现了视频采集。在此基础上，使用动态图像处理技术中的二维运动估计技术，结合背景更新模型提出了一种车辆跟踪算法。对采集的交通视频图像进行了多组试验．试验结果表明，该车辆跟踪算法的跟踪成功率可达90％～95％。     

多帧速度场估计方法及在交通视频监测中的应用

基于速度场的运动估计方法是进行运动物体分割的有效途径,提出了一种视频图像处理中基于多帧速度场的运动物体分割方法,针对简单速度场运动物体分割方法的不足,提出对多帧速度场图像提取的运动物体信息相融合的方法。试验结果证明:用此方法提取的运动物体核心点更完备,提高了运动物体分割的准确性。该方法在智能交通、视频监控系统中都有广泛应用。     

基于视频分析的车流量综合检测算法

车流量检测是智能交通系统中的关键技术之一。研究了多种基于视频图像处理的车流量检测算法,包括基于灰度图像的背景差分法、帧差法、边缘检测法和基于彩色图像的色彩跳变检测法。在分析了以上算法在不同检测环境中适用性差异的基础上,提出了1种修正的背景差分法,并在此基础上实现了1种通用性更强的综合检测法。综合检测法结合背景差分法,边缘检测法和色彩跳变法三者优点,可依据光线条件自动选择检测区域和检测算法,适用于多种检测环境,准确率超过90％。     

基于视频图像的车速检测研究

针对现有车速检测方法的局限性，提出了一种基于局部视频图像的车速检测新方法，该方法通过定位车牌的位置来确定车辆帧间移动的距离。讨论了车牌定位、如何将车辆帧间移动的像素行映射为对应的实际距离和最终实现车速检测等内容。经实验证明，本方法易于实现，具有很好的可维护性，车速检测的精度较高，平均精度为91．31％。     

汽车动态导航终端的研制

开发了基于嵌入式系统的汽车动态导航终端,经过对系统和算法的优化,降低了对嵌入式系统存储量和计算能力的要求。利用GPS进行定位,通过GPRS和服务器建立网络连接,终端从服务器获取根据实时路况计算得到的最优路径,在符号和地图两种模式下进行导航。     

基于DSP/CPLD的视频叠加系统设计与实现

设计了一种基DSP和CPLD的视频叠加系统，利用视频解编码芯片、DSP和CPLD对视频数据进行采集、处理，构成可以脱离计算机的视频叠加系统，同时它还可以根据需要叠加任意字符和图像。系统主要特点是并非基于通常所采用的专用的视频叠加芯片，而是通过DSP和CPLD来实现视频叠加的功能。     

基于出租车GPS定位技术的ITS共用信息平台实时路况信息采集及处理方法

以广州市ITS共用信息平台的建设为背景,提出基于出租车GPS定位技术的ITS共用信息平台实时路况信息采集及处理方法。针对ITS共用信息平台信息采集范围大、准确性和实时性要求高的需求特点,具体研究队列方式的道路拓扑存储方法,利用出租车计费器进行奇异数据剔除的方法,分区搜索和边界矩形相结合的GPS地图匹配方法和循环队列与A*算法相结合的路况计算方法等一整套基于出租车GPS定位数据的实时路况信息采集和处理的方法,并提出了基于J2EE架构的平台数据处理服务器的实现方案。广州市ITS共用信息平台示范工程的实际应用表明,该方法具有良好的效果和广泛的应用前景。     

高速公路相机自动标定及道路坐标系构建

为解决高速公路场景下利用视频监控系统正确描述车辆相对于道路的空间位置问题，通过引入Frenet坐标系概念，提出一种基于相机自动标定的道路坐标系模型。在相机自动标定阶段，利用线分段拟合方法从曲线车辆轨迹中提取平行于直线路段的轨迹点，并通过级联霍夫变换精确估计道路方向的消失点。然后,根据多车辆三维模型约束，对相机参数进行迭代优化。基于标定结果，将车辆轨迹映射到世界坐标系平面上，并用3次样条插值进行拟合。根据大量运动车辆在道路平面内形成的轨迹域分布特征，综合边界约束估计道路中心点。最后，结合道路中心线在各点处的法线向量与车道宽度信息确定平移量，并利用点平移运动拟合车道线，实现道路坐标系的自动建立。使用真实高速公路视频数据，在多种道路条件下进行试验。研究结果表明:在标定阶段，构建方法对不同高速公路场景的最大标定误差不超过11.55%;与最新的方法相比，直线道路平均标定误差分别降低6.68%和3.58%，弯曲道路平均标定误差分别降低7.43%和2.61%;在道路坐标系构建阶段，构建方法的平均投影距离为0.077 m，接近最新方法的0.069 5 m；而其平均精度为0.916，显著优于最新方法的0.663；所提道路坐标系能够自适应道路形态的变化，有效解决了从监控视频中描述车辆与道路之间相对位置关系的问题。     

基于Web的多路视频播放器及其在路产管理系统中的应用

针对基于视频的路产管理系统需要实时同步播放多路复合视频的特点,设计了一款基于ActiveX技术的多功能视频播放器,该播放器通过数据库关联技术实现了每一帧视频图像的精确定位,并采用多线程边下载边播放技术实现了在Web环境的应用。该播放器已经成功应用于某路产管理系统中,使用表明：该播放器使用简单、视频播放流畅、帧定位效率高。     

车辆道路试验数据实时采集系统研究

本文介绍了一种基于CAN总线通信技术、GPS全球定位技术、GPRS移动通信技术等为一体的试验数据采集传输系统,通过该系统在重型电控柴油商用车上的应用,解决了汽车道路试验中环境极端、工况复杂、里程长,数据繁杂、试验数据无法及时、准确获取等问题,重点讲述了车辆道路试验数据实时采集方法的实现。     

基于GPS/GIS/GSM的公路隧道运营管理系统研究

为了提高长大公路隧道的运营管理水平,通过分析长大公路隧道的运营特征,追踪GPS、GIS、GSM的最新技术,提出了采用基于GPS/GIS/GSM的公路隧道运营管理模式,实现长大公路隧道的现代远程监控与管理。论述了基于GPS/GIS/GSM的公路隧道运营管理系统的两大组成子系统,即基于GIS的隧道机电管理系统和基于GPS/GIS/GSM的车辆调度系统的功能与组成,同时采用软件系统设计的方法对该两大子系统进行了系统分析与设计。运用企业成本核算法进行了系统经济性分析,论证了基于GPS/GIS/GSM的公路隧道运营管理模式的可行性和科学性。     

Neural-network multiple models filter (NMM)-based position estimation system for autonomous vehicles

A highly accurate and reliable vehicle position estimation system is an important component of an autonomous driving system. In generally, a global positioning system (GPS) receiver is employed for the vehicle position estimation of autonomous vehicles. However, a stand-alone GPS does not always provide accurate and reliable information of the vehicle position due to frequent GPS blockages and multipath errors. In order to overcome these problems, a sensor fusion scheme that combines the data from the GPS receiver and several on-board sensors has been studied. In previous researches, a single model filter-based sensor fusion algorithm was used to integrate information from the GPS and on-board sensors. However, an estimate obtained from a single model is difficult to cover the various driving environments, including urban areas, off-road areas, and highways. Thus, a multiple models filter (MMF) has been introduced to address this limitation by adapting multiple models to a wide range of driving conditions. An adaptation of the multiple model is achieved through the use of the model probability. The MMF combines several vehicle models using the model probabilities, which indicate the suitability of the current driving condition. In this paper, we propose a vehicle position estimation algorithm for an autonomous vehicle that is based on a neural network (NN)-based MMF. The model probabilities are determined through the NN. The proposed position estimation system was evaluated through simulations and experiments. The experimental results show that the proposed position estimation algorithm is suitable for application in an autonomous driving system over a wide range of driving conditions.     

车载导航系统陀螺的自适应校正方法

分析了低成本压电振动陀螺误差及其影响因素,在实验的基础上得出采用温度补偿陀螺误差的可行性。建立了联合卡尔曼滤波方程融合GPS和INS信息,估计定位信息和陀螺误差。提出车载GPS/INS组合导航系统中陀螺零漂误差和标度因子误差的校正过程启动条件,当条件满足时,以估计的陀螺误差为输入,采用温度误差校正表学习算法对陀螺误差模型进行训练。用道路实验数据对提出的陀螺校正算法进行验证,结果表明该算法精度高、收敛快、可操作性好。     

道路交通安全管理与经济、社会发展关系研究

道路交通安全与国家经济、社会发展存在密不可分的关系。该文采用了上海市、广东省、吉林省处于不同发展阶段的三个地区的数据,通过对比可以衡量经济发展水平的GDP、人均GDP和公路通车里程、公路运输量等经济指标来建立它们与道路交通安全管理水平的联系。     

Effectiveness of enforcement resources in the highway patrol in reducing fatality rates

Motor vehicle crashes are a leading cause of death in the United States. Wyoming initiated a safety study to investigate the underlying causes of high crash rates since it has one of the highest fatality rates in the nation. Research has shown relationships between increased enforcement activity and road crash/fatality reduction. However, little research has attempted to quantitatively measure the impact of various forms of police enforcement, such as the percentage of enforcement time and the quantity of resources, on fatality rate. Therefore, this study was set forward to fill this gap. Data from the highway patrol in Wyoming and the surrounding states were used in this study. Although Wyoming and these nearby states have very similar features in terms of geography and weather, they are different in terms of road mileage and traffic. Therefore, the data was normalized based on highway mileage and miles traveled. Enforcement efforts were compared in terms of allocated enforcement budget, number of sworn officers, and time spent patrolling. The results indicated that there are negative relationships between fatality rate and budget, number of officers, and active hours on the field. This paper also investigated which variable is the best predictor of fatality rate. The results indicated that time spent on the field by highway patrol officers is the best indicator of fatality rate. It was found that although some states like Wyoming have a higher number of sworn officers, they spend less time actively enforcing highway safety. This study provides information needed for authorities to allocate more funding to the highway patrol, and for the highway patrol to spend more time on the road.     

A low-cost video-based pavement distress screening system for low-volume roads

This study investigates the use of consumer-grade video camera to develop a low-cost pavement distress screening system, with a particular focus on low-volume roads. Due to the oblique view of video data captured in the car front, existing crack detection algorithms that are tailor-made for nadir view cannot be used directly. Instead, we propose and develop a Video-based PAvement Distress Screening (VPADS) system, which includes an automatic data processing workflow by first defining a Region of Interest (RoI) through robust line fitting of the two side lanes. The pavement condition can be assessed within the RoI by implementing a multi-scale ridge detection filter followed by a boundary contour analysis. Since the proposed VPADS system is designed for preliminary screening purpose, each video image scene is examined if there exists any potential crack or distress feature(s). We tested the proposed system on video data collected for two low-volume roads (Highway 624 and 668) in Northern Ontario region, Canada. The overall accuracy of detecting crack and distress features yielded 80%. Instead of replacing traditional field inspection or high-end multi-sensor pavement evaluation system, the proposed VPADS system aims to provide a computer-aided screening solution for transportation authorities of a vast rural road/highway network and with limited inspection budget. The scope of the work can be further expanded by developing a crowdsensing inspection network built by any regular road user, who can also act as a data provider for the regional/municipal pavement distress screening system.