交通事故摄影测量中相机标定的扩展两步法

为了利用摄影测量技术提高交通事故数据采集的效率, 分析了交通事故与相机标定方法的特点, 提出了交通事故现场摄影测量的扩展两步相机标定方法。在扩展两步标定方法中, 首先对相机进行线性标定, 然后进行非线性修正, 最后进行图像校正, 并提出了完整的标定步骤和程序, 进行了相机标定实验。扩展方法标定的结果与线性标定结果相比, 最大绝对误差和相对误差分别为10.9和1.7%, 最小绝对误差和相对误差分别为4.1和1.0%, 表明扩展两步相机标定方法能够显著提高相机标定精度, 抗噪性能稳定。     

激光路面断面检测系统的功能与应用探讨

激光路面断面测试系统是先进的路面性能检测系统,它具有完善的路面性能指标采集和处理功能,能在不同行驶速度下检测各种干湿路面状况,准确、高效采集和处理路面状况性能数据.论文介绍了该激光路面断面测试系统的组成、构造及功能,并对其路用性能指标的标定和应用进行了探讨.     

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基于广州居民出行调查成果,本文从模型架构、效用函数基本形式、参数标定及校核等几个方面对交通方式选择模型的构建进行研究. 提出了方式划分的基本原则,并针对无车家庭、有小汽车家庭和摩托车家庭构建层次划分. 以小汽车家庭为例,阐述方式划分的基本形式. 进而,提出了方式划分参数标定的方法和基本步骤以及系数校核的关键点. 最后将预测结果和实际观测数据进行比较,验证模型的有效性. 本文提出不同层次交通方式划分模型,提高了模型的精度,并在效用函数中引入收入、车辆拥有和吸引量等因素,增强了模型的适用性,为其他类似城市交通方式选择模型的构建提供一定的参考.     

针对主辅路的Vissim仿真模型参数标定方法

微观交通仿真模型的参数标定是保证仿真模型有效性的基础和前提。针对车辆在主路和辅路运行特征的差异,提出了1种针对主辅路的微观交通仿真模型参数标定方法。该方法以进口道的车均延误的偏差作为评价指标,以遗传算法作为求解工具,分别实现了微观交通仿真软件Vissim中主路和辅路驾驶行为参数的标定。同时,结合工程实例将该方法应用于北京市朝阳路与高碑店北路交叉口、南苑路与久敬庄路交叉口仿真模型的参数标定中。结果显示,采用该方法标定后的主路和辅路延误与实测延误的平均偏差分别为2.1s和2.5s ;采用主路和辅路统一标定的方法,主路和辅路延误与实测延误的平均偏差分别为7.1s和7.5s。结果表明,仿真模型参数能够有效地提高参数标定的仿真试验效率与仿真精度,验证了该方法将主路和辅路仿真模型参数分开标定的有效性。     

双塔双索面稀索斜拉桥加固设计

以南阁大桥的主桥斜拉桥加固为工程背景,基于将挂梁与主跨相邻35m工字梁作为整体来计算桥梁结构损伤程度校验系数的研究现状,考虑将挂梁作为单独受力的简支梁置于两侧斜拉桥框架上来计算校验系数,并据此校验系数判定桥梁的损伤程度,对旧桥进行加固设计。     

快速路入口匝道瓶颈宏观交通流模型

基于入口匝道汇入方式与基本图形态, 提出了一种调整型元胞传输模型; 增加了入口匝道状态变量以追踪入口匝道交通状态, 定义了新的入口匝道汇入规则; 将双通行能力基本图引入到调整型元胞传输模型中, 以适应不同交通状态下通行能力的变化; 将单纯形法与遗传算法相结合, 提出了混合多目标参数优化方法; 建立了3个仿真场景, 评价调整型元胞传输模型与混合多目标参数优化方法的效果。仿真结果表明: 在预测入口匝道上游主线拥堵发生与结束时间方面, 与经典元胞传输模型相比, 调整型元胞传输模型将时间预测准确性分别提升了22.3、10.8 min; 在模拟入口匝道汇入段主线拥堵传播与消散方面, 调整型元胞传输模型模拟结果更加符合实际的传播与消散规律; 在模拟试验路段早发性失效交通特性方面, 调整型元胞传输模型对于拥堵前最大流量与拥堵后消散流量的拟合误差在4%以内, 小于经典元胞传输模型; 在模型仿真精度方面, 调整型元胞传输模型各项评价指标均优于经典元胞传输模型, 前者的仿真速度误差为10.42 km·h^-1, 较后者降低了25.4%;与传统的遗传算法相比, 混合多目标参数优化方法的总计算次数更少, 参数标定过程总耗时缩短了29.3%。     

Camera calibration and vehicle tracking: Highway traffic video analytics

We describe a real-time highway surveillance system (RHSS), which operates autonomously to collect statistics (speed and volume) and generates incident alerts (e.g., stopped vehicles). The system is designed to optimize long-term real-time performance accuracy. It also provides convenient integration to an existing surveillance infrastructure with different levels of service. Innovations include a novel 3-D Hungarian algorithm which is utilized for object tracking and a practical, hands-off mechanism for camera calibration. Speed is estimated based on trajectories after mapping/alignment with respect to dominant paths learned based on an evolutionary dynamics model. The system, RHSS, is intensively evaluated under different scenarios such as rain, low-contrast and high-contrast lightings. Performance is presented in comparison to a current commercial product. The contribution is innovation of new technologies that enable hands-off calibration (i.e., automatic detection of vanishing points) and improved accuracy (i.e., illumination balancing, tracking via a new 3-D Hungarian algorithm, and re-initialization of background detection on-the-fly). Results indicate the capability and applicability of the proposed system in real-time and real-world settings.     

基于深度约束的水下稠密立体匹配

  目的  针对水下双目图像特征点稀疏、极线约束模型失效等难题,提出一种基于自适应深度约束的水下图像特征匹配(ADC-UFM)算法。  方法  结合FAST算子与SIFT描述子,提高图像匹配精度;提出基于水下折射因子的特征匹配约束模型（MCM）,有效剔除误匹配点;提出自适应阈值选取（ATC）方法,最大限度地保留复杂水下环境下的图像特征信息。  结果  实验结果显示,ADC-UFM算法优于现有的SIFT,SURF和UCC-SIFT等典型方法,匹配准确率可达85.2%,满足实时匹配需求。  结论  研究成果可为基于双目视觉系统的水下三维重建提供关键技术支撑。     

A methodology for evaluating the performance of model-based traffic prediction systems

Model-based traffic prediction systems (mbTPS) are a central component of the decision support and ICM (integrated corridor management) systems currently used in several large urban traffic management centers. These models are intended to generate real-time predictions of the system’s response to candidate operational interventions. They must therefore be kept calibrated and trustworthy. The methodologies currently available for tracking the validity of a mbTPS have been adapted from approaches originally designed for off-line operational planning models. These approaches are insensitive to the complexity of the network and to the amount and quality of the data available. They also require significant human intervention and are therefore not suitable for real-time monitoring. This paper outlines a set of criteria for designing tests that are appropriate for the mbTPS task. It also proposes a test that meets the criteria. The test compares the predictions of the mbTPS in question to those of a model-less alternative. A t-test is used to determine whether the predictions of the mbTPS are superior to those of the model-less predictor. The approach is applied to two different systems using data from the I-210 freeway in Southern California.